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COMMITTEE PRINT
ANALYSIS OP HOME MORTGAGE
DICLOSURE ACT DATA
PROM THREE STANDARD
METROPOLITAN STATISTICAL AREAS
PREPARED FOR
FEDERAL HOME LOAN BANK BOARD
AND
FEDERAL DEPOSIT INSURANCE CORPORATION
PUBLISHED BT THE
COMMITTEE ON BANKING, HOUSING
AND URBAN AFFAIRS
UNITED STATES SENATE
W
JANUARY 1880
U.B. GOVERNMENT PRINTING OFFICE
WASHINGTON : 1080
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COMMITTEE ON BANKING. HOUSING. AND URBAN AFFAIRS
ALAN CRANSTON. California JOHN TOWER. T«ac
ADLAI E STEVENSON, Illinoli JOHN HEINZ. Pnnaj-lnnla
ROBERT MORGAN. North Carolina WILLIAM L. ARMSTRONG. C
DONALD W. R1EOLE, Jr.. Michigan NANCY LAN DON K ASSEBACM. Kanaaa
PAUL 8. SARBANES, Maryland RICHARD G. LCOAR. Indiana
DONALD W. STEWART, Alabama
PAUL E. THONG AS, Maaachuaetti
Kexkets A. MtLKiN. Staff Director
M. Disst Viu. lllnerltg Staff Dtrtttor
Steves M. Ruhpe. Projrtional Staff JTmfear
LlXDA C. ZlMII, Atr'itant Minority Counttl
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LETTER OF TRANSMITTAL
'SCrafcfe SAcAa* £>mttU
i Banking, Housing
I hereby transmit for the use of the Committee a
Committee Print consisting of papers contracted for by
the Federal Home Loan Bank Board and the Federal De-
posit Insurance Corporation for a study of various
aspects of the Home Mortgage Disclosure Act. This
Committee Print should be of immediate use to the Com-
mittee and the general public in the context of hearings
beginning next month on renewal of the Home Mortgage
Disclosure Act.
The study grew out of a request from the Committee
for compilation of Home Mortgage Disclosure Act data.
Data was compiled for three SMSA's. Included in the
Committee Print is a paper containing some analysis
of the data by the staffs of the Bank Board and the
FDIC.
Sincerely,
William Pro xin ire
Chairman
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Letter Of Transmittal
Special Report on Residential Mortgage Lending in the
Buffalo, Chicago and San Diego SHSA's, prepared by
the staffs of the FDIC and the Federal Hoh Loan
Bank Board ....................
Executive Sum iry. Submitted by JRB Associates, Inc. . . . .
Reports Submitted by Resource Consultants, Inc.
Project Hull iry Report ................
Description of the Senate Banking committee Report . .
Recosnendations for Changes to HMDA Reporting
Regulations
Costs of Processing BHDA Statements on a
Periodic Basis .... .........
Reports Submitted by JRB Associates, Inc.
Compliance Analysis ...........
Completeness , .
Double Counting
Accuracy of Disclosure Statement Preparation
Methods to Improve Geocoding Accuracy
Procedures to Assess the Accuracy of
Home Mortgage Disclosure Statements
Revisions to Regulation C ,
Enforcement of the Home Mortgage Disclosure Act . . . ,
Cost of Compiling Home Mortgage Disclosure Statements ,
Utility of the Home Mortgage Disclosure Act ....
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This special report Is In response to a request frcn the Senate
Conmittee on Banking, Bousing and Urban Affairs for a study showing the
correlation of mortgage lending activity to the nature of various kinds
of neighborhoods.
The staffs of the Federal Deposit Insurance Corporation and the
Federal ftroe Loan Bank Board prepared this special report using data fron
a broader, Mo-year study conducted by JIB Associates, Inc., of McLean,
Virginia, and Resource Consultants, Inc., of Phoenix, Arizona, and entitled
"Analysis of Bom Mortgage Disclosure Act Data from Three Standard Metropoli-
tan Statistical Areas."
Resource Consultants, Inc. used U.S. census data to classify kinds of
neighborhoods within each of three SMSAs - Buffalo, Chicago and San Diego -
according to location and age of housing stock and the income and ethnic
heritage of residents. Then Rd extracted mortgage lending statistics from
the RHDA disclosure reports submitted to the FDIC and FHLBB and matched
these figures with the neighborhood categories.
Both sources of data are izperfect: the U.S. census material because
it dates from the 1970 decennial census and the HMDA disclosure reports
(which are fron 1977) because they reflect considerable error of content.
This submission consists of a table each for the Buffalo, Chicago and
San Diego SMSAs presented In a format Intended to conform to the guidelines
of the committee's study request.
Each table shows nunber and amount of mortgage loans in 1977 for
oultifamily (five or more units) and one-to-four family structures in
various kinds of neighborhoods as they were composed in 1970. The first two
colunns of figures In each table show housing existing in 1970; the remain-
ing four colunriB show lending activity In 1377.
Following are the method and criteria by which the census tracts in
each of the three SMSAs aie classified Into kinds of neighborhoods according
to location and age of housing stock and Income and ethnic heritage of resi-
1. location Within SNSA
Each census tract within the SMSA is first assigned to one of four
location categories: Central City, Remainder of urban Area, Balance
of SHSA, and Hot Classified.
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ri> of the SB
(vtoiiy at partially) wttMn the ooroocate lftstts; of ths
afcrossntionsd cities; fix the Chicago 9Bh, this area la aw
xbat sore astsnsiwe than the corporate limits of the city of
Chicago. Sw rf^Tfl City tracts <—■■«■«»■« 1 " '
the BBD* Study Project «
Bousing an) tkbsn Cewelc
. ■— Iwdar of urban Hw aU nan tracts (not nctnaUy
OTntiquwMQ within the 5H» that ace not "**»'—< In the
antral City and wb Ich haw* a bousing density of «D0 or nor*
wilts pet square alls. a— Hng slightly ante than throe
persons pec household* this approslsstss the 1,000 persons
pet squats alls definition used by the Bateau of the Census.
. Balance of £■«*— all census tracts not Included in the Central
City lists furnished by the FBUB and for which both bousing
unit and tract area data were available.
age of Bousing Stock
Census tracts assigned to one of the first tan location groups
are further classified according to sedlan age of housing stock, as
obtained froa 1970 census data. The following categories are used:
Older — A census tract where the ssdlsn construction date of the
bousing Stock Is 1949 or before (1.*., the ssdlan age of the
housing stock was 28 years or older in 1977).
Income of Residents
The appropriate census tract subdivisions are again categorized
according to the income of residents. The sedlan income for faatU.es
and unrelated Individuals was coaputed for each tract using 1970
census data. The ssdlan lncoss for each tract was then compared
to that of the entire SMSA, and the tracts were classified as
fbllowai
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4. Ethnic Composition of Census Tracts
Finally, census tracts are categorized according to ethnic caspooition.
This category counts as minorities only Black and Spanish American
heads of household of either sex as reported In the 1970 census.
Each tract was classified according to its percentage of minority
heads of household, as follows i
. Minority— greater than 75% minority heads of household.
. Mixed— more than 10% but less than 75% minority heads of household.
. Men -Minority— less than 10% minority heads of household.
5. Outside of SMSA
The EMCft statement format suggested in Federal Reserve Board [emu-
lation C provides a space for the total mortgages made outside the rele-
vant SMSA. The Senate Banking Camittee Report format includes these
data where available as "Total - Outside of SMSA.*
Data Surces and Limitations
The data used to compile these tables were obtained from two sources;
1977 BMn statements supplied by subject banks and SKLs operating one or
more offices within one of the three study 9t5As and the Fourth Count 1970
Census of regulation and Housing.
The Bureau of the Census statistics represent the nest recent, official,
accurate and complete demographic data, but they describe the individual
census tracts as they existed in 1970, whereas the BMDA data describe mortgage
flows as they existed in 1977. Any distortion caused by analyzing 1977 flows
in terms of 1970 attributes may be minimized when dealing with a relatively
stable area (e.g., Buffalo), but could lead to erroneous conclusions In
rapidly changing areas (e.g., portions of Chicago) or rapidly growing areas
(e.g., San Diego).
Of more concern, however, is the quality of the BMDA data and the coverage
of subject institutions within the three study SMSAs. Overall, 76 percent of
the covered banks and S*Ls operating in the study areas submitted reports In
usable form; even on these, however, 10 percent of the loans could not be
assigned to the appropriate census tract. These are carried In the "TOtal-W»t
Classified* item in the tables for each SMSA.
With respect to the BMDA data that were tabulated , the HKDA Study portion
devoted to an assessment of accuracy concluded that geocoding errors (i.e.,
assignment of an Incorrect census tract Identifier to a property address)
coixiled with classification errors (i.e.. Inappropriate inclusion or exclusion
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locrxiAC. •smjmfXittKSOB. -r* ioac -^s* se :*— sua oc' ati ' t ■!■■• ■
m * 5» ,1/f. 4TMT EaW !nra C» 8BJKMJ 3j— .
Wiaw **t *» aeaparttoe oe an^ Lows jcigfagaa ty
two-CMC* lanfec* in ** anni ooucty of rt* stoev am
canal fc» a f.lqr. of 17.5 percent :sa 3fc»>r v a Iom of 12.1
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Population
The Buffalo SHSA la coapoaed of Erie and Niagara Counties la northwestern
Raw York Stata. The area had an overall population of 1,349,000 la 1970,
which reflects a 3.2 percent increase since I960. The rear-end 1977 population
was ostlastsd at 1,313,000. Tha City of Buffalo had 463,000 parsons In 1970,
but had declined to an estimated 396,000 In 1977. Tha city's population had
ellnbad froa 507,000 In 1920 to a high of 580,000 by 1950, but the next two
ten-year Intervals registered declines of B.2 percent snd 13.1 percent, respec-
tively. The nost recent estimate evidences a decline of neerly one-third *io«
the 1950 figure. While these population decrease* in the city were st lsast
partially offaet by gains In other portions of the SHSA. the area can only he
characterized in recent yearn as being stable, at bast, vith United periods
of nodsst growth outelde the city.
The Median housshold incons In the SHSA was reported as $15,229 In 1977,
slightly below the ststswida nsiHan of $15,305; In tha City of Buffalo alone,
the cosearabla figure was $11,817, or 77.5 percent of the statewide asdlan.
This represent e a subataotlal decline froa 1965, when the city's aadian lncowa
was 85. 7 percent of tha Hew York median. Other areas of the SHSA have farsd
bettor during that twelve year period, with the result that the SMSA's oedian
lncossi rose fron 96.5 percent of the statewide asdlan in 1965 to 99.5 percent
In 1977. Thsss lncowa figures are consistent with population trends cited
above, where declines In the city of Buffalo were largely offset by gains In
other portions of the SHSA.
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Retail cal.es In the Buffalo are* froa 1965 to 1977 »how ■ stability
which night be aonswhat surprising given the population and incoise trends.
Salaa In Buffalo were 36.5 percent of the SMSA'a total In 1965. and thla
ratio declined only slightly to 33.5 percent In 1977. The SKSA's retail
aalaa were 6.3 percent of the State total Is 1965, but grew to 7.1 percent
of the Haw Tort figure In 1977.
Computation
Of the 209,000 people working In Buffalo la 1970, 53.7 percent resided
In Buffalo, 42.2 percent realded elsewhere In Erie County and 2.4 percent
raaldad In Niagara County. Of the workers living In Buffalo, 68.4 percent
worked In Bufl
Financial Inal
located In
; 36.3 percent of the
worker
living
In other
part a of Erie
o Buffalo; and 5.9 pe
rent o
f Niagara
County-
a resident
to Buffalo.
ltutlon Struct
nd 1977, there v
s 13S offices of five mutual savings b
theae offices held IPC deposits
had the largest snare (42.8
of thirteen cosamrclal banks.
he $2.6 billion In local IPC
e Buffalo SHSA. At mid-y
of 54. 4 billion, of which Buffalo Savinga Bank
percent). The top two savings banks had a 76.6
At this tiiw, there were also 227 offices
The three largeat banks held 87.7 percent o
deposit*.
As of March 31, 1978 there were six ssvlngs and loan associations operating
a total of twenty-two offices in the Buffalo area. Thsse offices had deposits
of $323 adlllon, of which 42.1 percent waa held by the largest institution
and 75.9 percent was held by the three largest.
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Homing Stock
Butd oo 1970 Census data, the Buffalo SKSA contained an estimated
303,989 one- to- four family dwelling s truce urea. Of those. 29.6 percent
vara locatad In Cha central city, 47.2 percent vera located In the urbanised
area outside of Buffalo proper, and the reminder vara locatad In tha balance
of the SKSA (Table 1).
Within tha city of Buffalo, 47 uercent of tha 1-4 iseily dwelling
■tructurea vara In cenaua tracta classified aa lower Incase. Fifty-three
percent of tha 1-4 family structures, la Cunt, vara In aiddla-lncoaa tracta.
No 1-4 family dwelling structures vara locatad In tracta claaalflad aa upper
income. In tanas of race of head of household, aa reported In the 1970 Canaua,
9 percent of tha 1-4 family atructurea vara locatad In Minority canaua tracta,
16.4 percent vara In wlzsd tracta, and 72.6 percent ware locatad In uou-
mdnorlty canaua tracta.
Of the 143,273 eatinated 1-4 family dwelling structurea located In the
urbanised area aurrounding the city of Buffalo, 44 percent were located In
canaua tracta In which the median a|a of the housing stock In 1977 was 28 years
or more. Almost 90 percent of the 1-4 f sally atructurea in tha older urbanized
area ware located In non-minority , middle- and upper- income cenaua tracta.
With respect to tha 1-4 structures In urbanized area* where the median age of
the housing stock waa 27 year* or leas, all of tha atructurea were located
In non-minority cenaua tracts.
Aa retard* tha 1-4 family structure* In the balance of the SKSA, 59.2
percent were locatad in non-minority , middle-income canaua tracta. Tha
remaining 40.8 percent warn locatad in iiiiii minority, upper-income cenaua tracta.
Mora than three-fourth* of tha total aatlmated 1-4 dwelling atructuraa
in tha Buffalo SKSA ware single- family residences; 19.1 percent ware two-
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f sally rase 11 lull ; and 3.6 parent were unctmi honing 3-to-4 faai 111—
each. Of the 303,999 one-to-tour fmUy Mnctiru In the OS*. 84.8 pare*
id. All bat 3.3 parent of tba e
Tha Buffalo S»BA contained an eat lasted 422,104 total boning units.
Of thoaa unite, 35,785, or 8.5 percent, acta classified aa eulti-fandly. In
cam of geographic breakdown, 61.9 percent of tha sulci- fanlly onlta ware
located In Buffalo proper, 33.7 percent vara la tba urbanised araa aurroundlng
tba city, and 4.4 parceat were located In tha balance of tba SHSA. Lovar-
lneoae cenaua tract* contained S3. 2 parent of tba aoltt-fanllr nlta, ntddle-
lncoaa tract* cootalnad 33.6 percent, and upper-incone tracta cootalnad 13.2
percent. Aa regard* distribution by race of bead of household, 8.3 percent
of tha aulti-faaily unite vara In uinortty cenaua tract*, 13.7 percent vara
in nixed canau* tracta, and 78 percent vera In cenaua tract* classified aa
non-ninorlty.
Ajgafata BMDA loan Fiona
Table 2 sunarliaa tha percentage distribution of 1977 BMDA loan flows
tor tha Buffalo SHSA. Additional loan flow breakdowns are presented In
Tables 3 and 4.
Geographic Distributing
Tha geographic patterns of nortgage landing for 1-4 faally atructure* In
tha Buffalo SHSA In 1977 generally alrrored the geographic distribution of
1-4 faally dualling structures. The central city portion of tba SHSA, for
axaspla, contained 29.6 percent of the 1-4 dwelling structures and received
30.6 percent of tha total uunher of residential loana granted in 1977.
Similarly, tba older, urbanized araa outside of Buffalo contained 20.8 percent
of tha 1-4 dwelling structures in the SMSA nd received 22.2 percent of tba
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total nunbar of residential loans. Tha slight geographic bias evident In favor
of residential loana aada to Mil, urbanized araaa occurred at tha expense of
tha nonurbanized portion of tha SKSA rather than tha central city.
Tha average alia of tha residential loana aada In tha SMSA showed eon-
atdsrsbl* variation anong tha various canaua tract categories. For example,
the average residential loan aada In central city census tracts classified aa
older, lower Incoaa, alnorlty In 1977 was $4,017. Tha coaparabl* figure for
older, alddla Incoaa, nrm nrfnnrlry tracts was $10,723. Average loan alia* In
tracts located elsewhere In tha SMSA showed alalia? variation. With respect
to tha urbanized area outside of tha central city, for •uaple, average resi-
dential loan sis.* in tract* classified as older, lowar Incoaa, alnorlty was
54,667, whereas the average size in tracts classified as upper incoaa, oon-
■dnoritr was 411,013.
In terns of percentage distribution of bona Improvement loans Bade la the
Buffalo SMSA In 1977. survey DarticiDaot* favored the central city, larialv
at tha expanse of tha older, other-urbanized area* In tha SKSA. Of tha total
4,971 hoa* laprovenent loans Md* In 1977, 43. S parent went to central city
canaua tracts. Tracts In tha older, urbanized area outside of Buffalo, on
the other hand, received only 14.6 percent of the hoa* laproveaant loan* nade.
It Is interesting to note that the average sire of the laproveaant loana
aada In the SMSA showed reaarkabl* consistency. For exaapla, within tha central
city, tha average size of such loan* ranged froa $2,979 (alddla- Incoaa, minority
canaua tracts) to $3,242 (aid die- in come, non-adnorlty canaua tracts). In the
newer, urbanized area surrounding the central city, average hoa* Improvement
loan size ranged froa $3,140 (alddla- Incoaa, uon -minority canaua tracts) to
$3,203 (upper- incoaa, non- minority canaua tracts). The average for tha SMSA
overall was $3,303.
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laamm l«i«l categoric*
1> Tabla I. with wtKi
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-17-
■Irror tba distribution by Income categories of 1-4 family structures. This
finding does not bold, however. In the ease of aultl-famlly aortgages.
As regards 1-4 family residential loans, lower Income census tracts
received 11.7 percent of tha total number of auch loani. While thla percent-
age aight appear to be low relative to tba numbers presented for middle- and
upper-Income canaua tracts. It should b« kept In mind that less than 10 parcant
of tba single-family dwellings In tha Buffalo SMSA overall vara located la
lover-income canaua tracts. This percentage tehee on added significance given
that over throe-fourth* of tha total nunbor of 1-4 structurss in tha entire
Buffalo SMSA vera single-family dwellings.
Multi-family mortgag* loan flows, on tha other hand, did not correspond
to the distribution of mild-family units among tha three census tract Income
categories. Both the lower- Incoaa and middle-Income census tracts received
a sanller percentage number of multi-family mortgage loana relative to the
percentage of ■jlti-family units contained therein. Upper-income census
tracts, in contrast, received s disproportionately larger share of multi-
family mortgage loans relative to tha percentage of such units In those tracts.
Whereas only 13.2 percent of the multi-family units wars located In upper-
Income census tracts, those tracts received 31.5 percent of the aultl-famlly
loana In tha SMSA.
Head of Household lac 111 Composition Distribution
Canaua tracts classified as non-minority generally received over 90
percent of tha total number and total dollar amount of the loans shown in
Table 1. The aole exception was In the category of homo Improvement loana.
Two factors may help to explain the disproportionate share of loan flova to
households headed by non-minorities. First, slngls-fasdlv dwellings, the bulk
of Buffalo's housing stock, ware principally located In non-minority census
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-18-
ru» ■■ of 1970. Secondly, sttanTrlEy-neadsd haamm hnlde as of e
•sad only 3.3 percent of the owner-o*cnpied 1-4 fasrlly uraf
mall.
Table 4 aussBtrlaea the housing acock and loan £ Iowa within the Buffalo
MM by oaighborbood-typea. In order to identify loan How tnadi to ■pacific
naighborhood-tjpe*, ratloa relating number of lou to nosfeer of atTKtims
(or sultl- tastily units, la tba eaaa of multi-family nnpiu) vara cosspmtad
for aacb of tba neighborhood- type* In tba SM5A. Tba flndlnga are dlacuaaad
below. In tba aoalysla which follow, geographic location la held conetsnt,
both with respect to housing itock and loan flowa.
Kith respect to 1-4 family residential loan flowa to older cesaue tracts
la Buffalo proper, an analysis of tba data revealed a lending bias in favor
of alddle- income, minority neighborhoods. Whereas tba loan-to-atTuctare ratio
fot that neighborhood-type »•■ .150, tba comparable ratio for other nelghbor-
hood-typas ranged fton .050 (lower income, minority) to .144 ■■■'-■■..,
non-minority). Aa ragatda multi-family loan flowa to older cenaus tracta In
the cantral city, lower- income, non -minority neighborhoods vara favored over
other neighborhood-type*.
With raapect to loan flows (both 1-4 faolly and sulti -fanlly mortgages)
to census tract* in the urbanised sree surrounding Buffalo and the remainder
of tba SKSA, upper-income , non-minority neighborhoods ware favored over all
other nelghborhood-typoo-
Con elusion
The bulk of the housing stock In the Buffalo SMSA In 1970 consisted of
•lngla-faarfly dwelling* located In middle- and upper-income census tracts
outside of the cantral city. Based on the demographic and HMDA loan dsts
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several aggregate trsnds emerged. First and foremost, th« geographic
pattern of residential and nultl-famlly mortgage landing In 1977 generally
mirrored Ch« geographic dietribution of 1-4 family drolling structures and
■ulti-feully unite In the SMSA. Second, Che dlatrlbutlon of 1-'- faadly mort-
gage loans by lncone level categories generally reflected the geographic
dlatrlbutlon of the housing stock located In Che specific lncone categories.
Third, with the exception of hose laprovenent loane, non-nlnorlty census tracts
received over 90 percent of the total number and dollar amount of the BHDA
loan flow* In the Buffalo SMSA In 1977.
In addition Co the general resides cited above, loan flowe Co apeclflc
neighborhood-types were examined. With reepect to 1-4 family residential loan
flows to older cenaos tract.
borhoode were favored over
minority neighborhoods, on
mortgage loan flowe to oldei
dmca for cracte outalde of
of upper-Income, non-ninorli
In Buffalo proper, middle- Income, minority nelgh-
ither nelghborhood-typea . lower-Income, non-
:he other band, were favored as regards multl-faadly
ins tracts In Buffalo. An analysis of the
;he central clCy revealed a lending bias In favor
7 neighborhoods, both with reepecc to 1-4 family
md multi-family mortgage loans.
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CHICAGO
Populat Ion
The Chicago SHSA la conposed of Cook, DuFage, Kane, Laka, HcHanry and
Kill Counties, tc 1970, Ita population was 6,979,000, which ahowa a 12.2
percent increase over I960. The City of Chicago had a 1970 population of
3,367,000, having declined 5.2 peccant in the preceding ten yearn. By the
and of 1977, the population of the SKSA vu eotlmted at 7,022,000 and that
of the city at 3,045,000. In 1930, Chicago had 3,376,000 peraone, or about
tha ana figure recorded In 1970, but by 1977 the nevaa-year decline waa
estimated to be 10.6 percent, with rapid growth In portions of the SKSA ont-
alde Chicago (35.3 percent fron 1960 t
U slightly ahead of chat of Illinois
1970), the SMSA's overall growth r
■ a whole.
In the SHSA, aedian houaehold inc
figure for the city alone wae $13,552.
« wai $19,468 In 1977; the comparable
In 1965, the and Ian Incoaa tor Chicago
■ea 98.1 percent of the Illinois median, but by 1977 Chicago's median wet
86.0 percent of the statewide aedian. Each of the alx county conponentn of
the SHSA had a 1977 aedian household incoaa in excess of the state aedian,
ranging as high as 147. 8 percent in DuPage Coimty ($23,821).
Retell Sales
In 1965, 55.5 percent of the SMSA's retail sales vara recorded in the
City of Chicago. By 1977, that percentage bad declined to 18.7 percent.
Overall, sales in the SHSA improved allghtly relative to Illinois. In 1965
area sale* vera 65.2 percent of the atate total, increasing to 66.1 percent
by 1977. That Increase was even greater in portions of the SHSA outside
Chicago.
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In 1970, chare vera 1,337,000 persons working In Chicago, of vhon 71.9
percent alio resided In the city. The percent of workers residing In other
parts of the SMSA who nocmited Co aaploynent In Chicago were aa follow* :
Cook County outside Chicago, 31.3 peccant; DuFaga Comity, 22.1 percent; lane
County, 4.0 percent; Lake County, S.7 percent; McHenry County, 7.5 percent;
and Will County, 6.S percent.
financial Institution Structure
At year-and 1977, there were 439 bank* operating 586 offlcea in the CUcee.
SMSA. On June 30, 1977 theie banks had IPC deposits of $38.9 billion, of
which 34.2 percent was held by the two largest banks and 4S.3 percent by the
As of Match 31, 1978 there were 197 laving* and loan association* with
529 offlcea in the Chicago metropolitan area. The SSL's had local deposits
of 321.3 billion. The largest in the area held 8.9 percent of these deposits,
and th* four largest held 26.6 percent.
Homing Stock
Th* six-county Chicago SMSA contained an estimated 1,276,247 one-to-four
family dwelling structure* a* of 1970. Almost two-fifth* of th* structures
war* located In the central city, 46.7 percent ware located In the urbanised
area outside of Chicago, and 14 percent were located In the balance of the
SMSA (Table 5).
Of th* estimated 502,930 ona-to-four family structures in Che city of
Chicago, 22.6 peccant war* located In census tract* classified as lower-iocom ,
56.4 percent were in middle- Income census tracts, and 21 percent war* located
In upper-lncone tract*. A* regard* distribution of housing stock by race of
head of household, about an equal p*rc*ntag* of the 1-4 family ■
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Chicago (IT to L8 percent) were locatad In minority aod nixed canaua tract*.
The remaining 65 percent of tba 1-4 family structures ware locatad Id non-
ainority canaua tracts.
With respect to the aatlaatad 594,956 one-to-four family *truetura*
locatad In the urbanized area aurroundlng Chicago, over TO percent of tba
e median age
ant of the 594
ua tractaj 35.
the housing stuck
956 (1-4 family)
In 1977 wa» 17 years or leaa. Only 4.3 p
structures ware located In lover -Income c
middle-income census tracta; and 60.3 percent were In upp
tracta. About 90 percent of the 1-4 family structures In
aurroundlng Chicago ware locatad In non-minority canaua t
Aa of 1970, tba balance of the Chicago SMSA contained 178,361 (1-4 family]
Less than one percent of these structures vara locatad In minority
Almost 83 percent of the total estimated dwelling structures In the
Chicago SMSA were single-family residences; 11.9 percent were two-family dwel-
lings; and 5.6 percent were dwellings housing 3-to-4 f anile* each. The aatl-
aatad 1.18 million (1-4 family) availing structures in the SHSA represented a
total of 1.6 million (1-4 family) dwelling unlta. Of the 1.2* million struc-
tures In the SMSA, 88. 2 percent were owner -occ up lad. About 7.8 percent of
the owner-occupied 1-4 family structures were owned by minorities.
Of the total
percent ware class:
77.1 percent of thi
percent ware In thi
In the balance of
2 Million aatlaatad bousing unit* la the Chicago SMSA, 29.2
fled a* multi-family. In terms of geographic distribution,
multi-family unlta were located In Chicago proper, 19.2
urbanized area surrounding Chicago, and 2.0 percent were
ha SHSA. Aa regard* Income distribution, 48.6 percent of
* ware located In lower-Income canaua tract*, 38.8 percent were In
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The average size of the residential loans Bad* In Che Ch.
between $32,400 (older census
cenaua tracts In the central el-
size In the Chicago SMS A In 1!
In term of percentage d:
tracts located In the central
ids In the central city) and
r). Overall, the average
KM S 37, 100.
in of hone improve!
the urbanised area
;rlb.
seeived an almost equal share of such loana— 41.9 percent and
i geographic distribute
a different pic tun
celved 27.4 percent
(Teble 6). The 1
of loproveaen
.cage SMSA ranged
$41,400 -(neater
.dentlal loan
oundlng Chicago
40.1 percent.
dollar anount
i surrounding
is supported
s vaa generally higher
latlve to other parts of
nt of improvement loana
city was $4,600 and $6,200,
respectively- In looking
of home Improvement loans,
census tracts In the central cli
Chicago received 53. 3 percent ('.
by the fact that the sveragt
for the urbanized area outside of the central city
the SHSA. For example, while the average dollar ai
for the older and newer censua tracts In the centr
respectively, the comparable average for the older and newer census tracts In
the urbanised area outside of the central city was S3, 000 and $10,700, respec-
tively. The avaraga for the SKSA overall was $7,500.
The geographic lending pattern for multi-family mortgage loana In the
Chicago SHSA in 1977 did not mirror the geographic distribution of such units.
Whereas census tracts in the central city contained 77.1 percent of the sulti-
family units in the Chicago SHSA (Table 5), thoae tracts received only 46.4
percent of the total Dumber of multi-family mortgages and 42 percent of the
total amount of auch loana In the SHSA overall (Table 6). In contrast, the
remaining cenaua tracts outside of Chicago proper contelned 22.9 percent of the
multi-family units, but received over 50 percent of both the total number and
dollar amount sf mil ti- family mortgagee written in 1977.
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TttcBmm Distribution
The BOA loan distribution by Income level categories for the Chicago
MSA la ■boon In Table 6. The results generally do not mirror the composition
and geographic dlltrlbutlon at the housing stock In the Chicago SMSA.
As regards 1-4 fully residential loans, lover-Income and middle- lu cos*
census tracts appear to have been shortchanged vis -a- vis upper-Income, census
tracts with respect to the porcentsga number of 1-4 family mortgages received.
Whereas lovar-inconm census tracts accounted for 10.9 percent of the 1-4 family
structural In the SMSA, the former received less than 6 percent of the 1-4
(■ally mortgages granted. By Ilka token, middle-Income tracts accounted for
Over 40 percent of tha 1-4 family structures In the SMSA, but received 35.9
parcent of the 1-4 family loan* written. Upper-Income census tracts, on the
other band, received 58.3 parcent of the 1-4 family mortgages written la the
SMSA, even though those tracts contained 43.9 percent of the 1-4 family Btruc-
Laatly, the pattern of multi-family mortgage landing did not correspond
to tha distribution of multi-family units for two of tha three Income cate-
gories. Although lower-Income census tracts accounted for 49.6 percent of tha
multi-family units in the SMSA, those tracts received less than 20 percent of
tha number and dollar amount of loans secured by multi-family units. In con-
trast, upper-income census tract* received a disproportionately larger share
of multi-family mortgage loans; although thosa tracts contained only 12.6
percent of tha multi-fanily unit), they received over 40 percent of the loans
secured by multi-family units.
Head of Houethold Composition Distribution
As shown in Tsble 6, census tracts classified as non-minority generally
received over 90 percent of the total number and dollar amount of tha loans
,d by Google
written in che SMSA, with the exception of non-convent load loans and bom*
Imyror— at loinn. As van the cue for the Buffalo SMSA, two factors ™y
help to explain the disproportionate ahara of loan flova to uon -minority
cmiui tract* In the Chicago SHSA. First, 86.2 percent of the elngle-faally
dwellings In the SMSA, which. In turn, constituted 83 percent of the SKSA'a
1-4 family housing stock, were located In non-alnorlty cenaua tracts. Secondly,
nlnor it y- headed houaeholda owned only 7.8 percent of the owner-occupied 1-4
family structure* In the SKSA overall.
Mortgage Flows to Neighborhood-Type ■
Table 8 summarizes the housing stock and loan flows within the Chicago
SMSA by neighborhood -types. As was the caaa in the analysis of th* Buffalo
SKSA, loan-to-structure (or mult i- family units) ratios were computed for each
of the neighborhood- typea in the Chicago SMSA in order to Identify loan flow
trends at the neighborhood level. The findings are discussed below.
An analysis of the 1-4 family loan data revealed a lending bias in favor
of non-minority neighborhood* within each of the three income groupings (lower,
middle, and upper) throughout the SMSA. For example, the loan-to-structure
ratio for minority, mixed, and non-minority, lower-Income neighborhoods In
older census tracts in the city of Chicago was .01, .05, and .14, respectively.
By like token, the loan-to-structure ratio for minority, nixed, and non-
minority, middle-Income neighborhoods in older census tracts in the city of
Chicago was .02, .03, and .06, respectively. This trend was repeated through-
out the SMSA.
In view of the 1-4 family mortgage lending blaa In favor of non-minority
neighborhoods, it was possible to isolate the effect of income on 1-4 family
loan flows in the Chicago SMSA. The data showed two trends: (1) a lending
bias In favor of lower-lncon* neighborhoode In Chicago proper; and (2) a
Digitized by GOOgk
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Wf* rffr.: 'A ■iltl-faadly loan flow* at the a
•r«4a «n»r«M. rim, the date eboved a leading blaa In favor of appai
;*"-■•, v*k~tt*rtrUr nai(hborhoode In tha city of Chicago. Second, eba land
*•:** v*eMa vf %fja> proper ma la favor of nlsed neiijiBorficDde. tbdK,
•M e'r«*' *f lajyvat on aulti-faadlj 1
^ 'M-mW mrtml. Fir eitaacla. la tha oldar, urbanized c
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re*l* ear*! 'he -hree Intone groupings (lover, Middle, and upper). Is the
-••a *,f Mwr, 'irhaflliad ™iia tract a outild* of Chicago, laiwiai. nppcr-
(*-•■*•, aj/*d nalgtiWhonde had tha hlghaat loen-to-unlt ratio. Ota tha ochax
•-**4 , If, >ba **lmnrn it tha 3M3A, alddli-- Interna, aliad neighborhoods bad tba
'.)»-«• I'.Mfi'-finlt ratio.
Tha gaifgraphl'; pattern of no rt gage lending la r.ha Chicago SMSA In L977
raflciad lha gaographlr dlatrlbutlon of 1-4 availing structures only with
raapa'i n, tha •irhenliad araa surrounding tba central city. In general,
lending InWIlMllMia favored tha balaaca of tha SMSA In Baking residential
fnan* vr in- 'Ipsll t at tha expanse of tha "oldar" caaaua tracta In tba central
•Hf. At r»*»rd« aultl-faaUT aortgagas, tha distribution of euch loana did
(ha geographic distribution of miltl-fanHy unlta. An exaalnatloa
t •)•(> ravaalad Chat tha loan dlatrlbutlon vlthln specified lncoaa
■Slrrorad the distribution of tha houalng atock contained therein
imlr >n a United extant.
* respect to loan flow* to apaclflc neighborhood-types, several trende
An analysis of tha 1-4 fanily loan data revealed a leading biae In
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favor of noa-nJnnriry neighborhoods within each of the three Income grouping*
(lower, fflldule, and upper) throughout the SMSA. When the possible effect of
incoee on 1-4 family loen flows wu examined, the date Showed the following:
(1) a lending bias In favor of lower- Income neighborhoods In Chicago proper;
end (2) a landing blaa In favor of upper- income nalghborhooda outalda of the
central city. Aa regards aultl-famlly loan flows, the data ravealed a landing
bias in favor of upper-lncoa* , non-ainoricy neighborhoods in the city of
Chicago. Outside of the city, the lending blaa was In favor of nixed neigh-
borhoods. Lastly, the effect of Income on nultl-fsBily loan flows at the
neighborhood level outside of Chicago proper varied.
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Tha Chicago SHSA is coopoaed of Cook, DuPage, Kane, Lake, HcHenry and
Hill Couutiee. In 1970, lea population vaa 6,979,000, which ahova a 12.2
percent Increase over 1960. the City of Chicago had a 1970 population of
3,367,000, having declined 5.2 peccant In the preceding ten year*. By the
end of 1977, the population of tha SMSA una estimated et 7,022,000 and that
of the city et 3,045,000. In 1930, Chicago had 3,376,000 persona, ot about
tba same figure recorded in 1970, but by 1977 the savan-yaar decline ma
estimated to be 10.6 percent. With rapid growth in portlona of the SHSA out-
aide Chicago (33.3 percent free 1960 to 1970), the SKSA'a overall growth rata
la slightly ahead of that of Illinois a* a whole.
In the SHSA, median household income wee $19,468 In 1977; the comparable
figure for the city alone waa $15,552. In 196S, the median lncona for Chlcego
was 98.2 percent of the Illinois median, but by 1977 Chicago's median was
86.0 percent of the statevide median. Each of the six county componenta of
tha SHSA bad a 1977 median household lncoae In excesa of the atate median,
ranging aa high as 142.6 percent In DuPage County ($25,821).
Retail Salea
In 1965, 55.5 percent of the SKSA'a retail aalaa ware recorded In the
City of Chicago. By 1977, that percentage bad declined to 38.7 percent.
Overall, sale* in tba SMSA improved Slightly relative to Illinois. In 1963
area salea were 65.2 percent of the state total, increasing to 66.1 percent
by 1977. Thet Increeee wea even greater In portions of the SHSA outside
,d by Google
Id 1970, than mt 1,337,000 persons working la Chicago, of vnoa 71.9
percent also resided In the city. The percent of workers residing la other
part* of the SKSA who conauted to eaploy— nt Id Chicago were aa follows:
Cook County outside Chicago, 31.3 percent; DuPags County, 22.1 percent; Ease
County, 4.0 percent; Lake County, 8.7 percent; McBenry County, 7.5 percent;
and will County, 6.S percent.
Financial Institution Structnra
At year-end 1977, there ware 439 banks operating 586 offlcaa In the Chicago
SKSA. On June 30, 1977 these banks had IPC deposits of $38.9 billion, of
which 34.2 percent was held by the tvo largest banks and 43.3 percent by the
four largest.
As of March 31, 1978 there were 197 savings snd losn sssociations with
529 offices In tha Chicago netropolltsn area. The s&l'b had local deposits
of $21.3 billion. The largest In the area held 8.9 percent of these deposits,
md the four largest held 26.6 percent.
Housing Stock
Tha alx-county Chicago SMS*, contained an est ins tad 1,276,247 one-to— four
fanily dwelling structures as of 1970. Alsnet two-fifths of tha structures
were located in the central city, 46.7 percent were located In tha urbanized
area outside of Chicago, and 14 percent were located In the balance of tha
SHSA (Table S).
Of tha estimated 502,930 ona-to-four faally structures In the city of
Chicago, 22.6 percent were located In cenaua tracts classified as lower-lncoan,
56.4 percent were In middle- in come census tracts, and 21 percent were located
In upper-lncoae trscts. As regarda distribution of housing stock by race of
bead of household, about an equal percentage of the 1-4 family structures In
hi* Google
Chicago (17 to IB percent) war* located In minority and mined census tract*.
TIM remaining 65 percent of the 1-4 finally structures were located In non-
Minority canaus tract*.
With respect to the tatlnated 594,956 one-to-four family structures
.ocatad In the urbanized area aurrounding Chicago, over 70 percent, of the
b in cenaua tracta In which the median age of the homing stock
In 1977 wa* 27 years or leaa. Only 4.3 percent of the 594,956 (1-4 family)
were located in lower-income canaua tracta; 35.4 percent were In
middle- in cone cenaua tracta; and 60.3 percent were la upper-Income ceniua
about 90 percent of the 1-4 family atructures in the urbanized area
surrounding Chicago ware located In non-minority cenaua tracta.
<f 1970, the balance of the Chicago SMSA contained 178,361 (1-4 fanily)
Leas than one percent of theae structures were located in minority
Almost 83 percent of the total estimated dwelling structures In the
Chicago SMSA were e Ingle-family residences; 11.9 percent ware two-family dwel-
inga; and 5.6 percent ware dwelling* housing 3-to-4 familes each. The eatl-
aeted 1.28 million (1-4 family) dwelling structures In the SKSA represented a
otal of 1.6 Billion (1-4 family) dwelling units. Of the 1.2S million a true -
urea In the SMSA, SB. 2 percent were owner-occupied. About 7.8 percent of
mer- -occupied 1-4 family strueturae were owned by minorities,
)f the total 2.2 million eatlmatad housing unit* in the Chicago SKSA, 29. Z
it war* classified aa multi-family. In terms of geographic distribution,
7.1 percent of the multi-family units ware located in Chicago proper, 29.2
it ware in the urbanized area surrounding Chicago, and 2.0 percent ware
In the balance of the SKSA. Aa regards Income distribution, 48.6 percent of
the units were located In lower-Income census tract*, 38.8 percent were in
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alidl e-lncome traces, and 12.6 percent were In upper-Income census tracta.
Lastly, with respect to distribution by race of head of household, 56-4 percent
of tha multi-family units vera In non-minority census tracts, with tba remainder
of tba uolta alaost squally divided between minority and nixed tracts.
Aggregate HHDA Loan Flogs
Tabla 6 suamariaas the percentage distribution of 1977 EMDA Loss flam
for tba Chicago smsa. Additional loan flow breakdowns ara preaantad In
Tsblea 7 and 8.
Geographic Distribution
the geographic pattern of 1-4 family mortgage lending In tha Chicago
SMSA In 1977 reflected the geographic distribution of 1-4 dwelling structures
only with respect to tha urbanised area surrounding Chicago. That area, which
contained 46.7 percent of the dwelling structures as of the 1970 Census,
received an almost equal share of tha total number of 1-4 family residential
mortgages made in 1977 In the SHSA - 47.6 percent. The same was not true for
either the older census tracts In the central city or tha census tracta located
In tha balance of the SHSA. Whereas the older cansua tracts In the central city
contained 30.4 percent of tba 1-4 family dwelling structures In tha SHSA, they
received only 17.9 percent of tha total number of residential mortgagee made.
Convaraaly, while tha census tracte In the balance of the SMSA accounted for
only 13.9 percent of the dwelling structures In tha Chicago SHSA, 26.1 percent
of tha total number of residential mortgage loans written In the SKSA In 1977
want to those census tracts. Baead on tha foregoing, survey participants
favored the balance of Che Chicago SMSA at the expense of tha older census
tracta in the central city In granting residential mortgage loans.
Survey participants In the Chicago SHSA also wrote 10,750 loans totaling
$417.6 million on 1-4 family properties located outside of the SHSA.
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The average alia of tha residential loans made In tha Chicago SMSA ranged
between $32,400 (older census tracts In tha central city) and $41,400 -(newer
census tracts In tha central city). Overall, the average residential loan
alia In tha Chicago SHSA Is 1977 was $37,100.
In tens of percentage distribution of hoen Improvement loans, csnsus
tracts located In the central city and the urbanized area surrounding Chicago
received an almost equal share of auch loans — 41.9 percent and 40.1 percent,
respectively. In looking at tha geographic distribution of the dollar amount
of hone improvement loans, however, a different picture emerges. Whereas
census tracts In tha central city received 27.4 percent of the dollar amount
of tome improvement loans -In 1977, tracts In the urbanized area surrounding
Chicago received 53.3 percent (Table 6). Tha latter statistic Is supported
by the fact that the average size of improvement loans was generally higher
for the urbanized area outside of the central city relative to other parts of
the SMSA. For example, while the average dollar amount of Improvement loans
for the older and newer census tracts In tha central city was 54,600 and $6,200,
respectively, the comparable average for the older and newer census tracts In
the urbanised area outside of the central city waa $8,000 and $10,700, respec-
tively. The average for the SMSA overall was $7,500.
The geographic lending pattern for multi-family mortgage loans In the
Chicago SMSA In 1977 did not mirror the geographic distribution of auch units.
Whereas census tracts In the central city contained 77.1 percent of the multi-
family units in the Chicago SHSA (Table 5), those tracts received only 46.4
percent of the total number of multi-family mortgagee end 42 percent of the
total amount of auch loans In the SMSA overall (Table 6). In contrast, the
remaining census tracts outside of Chicago proper contained 22.9 percent of the
multi-family unite, but received over 50 percent of both the total nuaber and
dollar amount of multi-family mortgages written In 1977.
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Income Distribution
The HMDA loan distribution tiy income level paregorics for the Chicago
SMSA ii shown In Table 6. The raaulta generally do not alrror tha composition
and geographic distribution of tha housing stock In the Chicago SMSA.
Ab regards 1-4 fully residential loans, lower -In come and middle-income
cansus tracts appear to have bsan shortchanged vis-e-vis upper-Income census
tracts vlth respect to tha percentage number of 1-1 family mortgages received.
Whereas lover- Income census tracts sccounted for 10.9 percent of the 1-4 family
structures In the SMSA, tha former received less than 6 percent of the 1-4
family mortgages granted. By like token, middle-Income tracts accounted for
over 40 percent of the 1-4 family structures In the SMSA, but received 35.9
percsnt of the 1-4 family loans written. Upper-income census tracta, on the
other hand, received 58.3 percent of the 1-4 family mortgages written In the
SMSA, even though thoae tracts contained 43.9 percent of the 1-4 family struc-
Lastly, the pattern of mult i- family mortgage lending did not correspond
to the distribution of multi-family units for tvo of the three Income cate-
gories. Although lover-Income census tracts accounted for 48.6 percent of the
multl-famlly units In the SMSA, those tracts received less than 20 percent of
the number and dollar amount of loans secured by multl-famlly units. In con-
trast, upper-Income census tracta received a disproportionately larger Share
of multl-famlly mortgage loans; although chose tracts contained only 12.6
percent of the multl-famlly units, thsy received over 40 percent of the loans
sscured by multl-famlly units.
Head of Household Composition Distribution
Aa shown In Table 6, census tracts classified as non-mlnorlty generally
received over 90 percent of the total number and dollar amount of the loans
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written In the SHSA, with the exception of non-conventional loans and home
imyrovene.it loans. Aa was the cue for the Buffalo SHSA. two factors ray
help to explain the disproportionate share of loan flows to non-minority
census tracts In the Chicago SHSA. First, 86.2 percent of the single-family
dwellings In the SHSA, which, In turn, constituted 83 percent of the SHSA's
1-4 family housing stock, were located In non-minority census tracta. Secondly,
■Inorlty-headed households owned only 7.8 parcsnt of the owner-occupied 1-4
family structures in the SHSA overall.
Mortgage Flows to Melahborhood-Typea
Table 8 suonsrlz.es the housing acock and loan flows within the Chicago
SHSA by neighborhood- types. As was the case In the analysis of tha Buffalo
SHSA, loan -to-at rue ture (or multi-family units) ratios were computed for each
of the neighborhood- types In the Chicago SHSA in order to Identify loan flow
trends at the neighborhood level. The findings are discussed below.
An analysis of the 1-4 family loan data
of non-minor ity neighborhoods within each of
middle, and upper) throughout the SHSA. For
ratio for minority, mixed, and non-mlnority
older census tracts in the city of Chicago wai
By like token, the loan- to-struc ture ratio foi
minority, middle-income neighborhoods in oldei
Chicago waa .02, .03, and .06, respectively. This tread was repeated through-
out tha SHSA.
In view of the 1-4 family mortgage lending biaa In favor of non-minority
neighborhoods. It was possible to Isolate the effect of income on 1-4 family
loan flows In tha Chicago SHSA. The data showed two trends: (1) a lending
bias in favor of lower-Income neighborhoods in Chicago proper; and (2) a
'evealed a lending bias In favor
irae income groupings (lower,
ixemple, the loan-to-structure
iwer-income neighborhoods In
.01, .05, and .14, respectively,
minority, mixed, and non-
cenaus tracta In the city of
Digitized by GoOgle
34
-3*-
lendlng bias In favor of upper-Income neighborhoods outside of ths central
city.
With respect to oultl -family loan flows at the neighborhood level, aeveral
trend* emerged. First, the data ahowed a landing bias In favor of upper-
Income, non-ninorlty neighborhoods In tha city of Chicago. Second, tha landing
bias outside of Chicago proper was In favor of mixed neighborhoods. Third,
tha affect of Income on mult 1- family loan flows to mind neighborhoods outslda
of Chicago varied. For eiasplfi. In the older, urbanised census tracts outside
of Chicago, lower- Income, mind neighborhoods had the highest loan-to-unlt
ratio among the three Income groupings (lower, middle, and upper). In tha
case of newer, urbanized census tracts outalde of Chicago, however, upper -
Income, mixed neighborhoods had the highest loan-to-unit ratio. On ths other
hand, In the balance of the SHSA, middle- Income, mind neighborhoods had the
hlghast loan-to-unit ratio.
Conclusion
Ths geogrsphlc psttern of mortgage lending In the Chicago SHSA In 1977
reflected the geogrsphlc distribution of 1-4 dwelling structures (July with
rsspect to the urbanized sres surrounding the central city. In general,
landing Institutions favored the balance of the SHSA In asking residential
loans principally at tba expanse of the "older" census tracts In the central
city. As regards multl-fanily mortgages, the dlatributlon of such loans did
not mirror tha geographic distribution of mult i -family units. An examination
of tha data also revealed that the loan distribution within specified income
categories mirrored the distribution of the housing stock contained therein
only to a limited extent.
With respect to loan flows to specific neighborhood -types, several trends
emerged. An analysis of tha 1-4 family loan data revealed a lending bus In
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favor of non-minority neighborhoods ulthin each of the three Income grouping!
(lower. Middle, and upper) throughout the SMSA. When the possible effect of
Incase on 1-4 family loan flow* was examined, the data showed the following:
(1) a lending bias in favor of lover- income neighborhoods in Chicago propel;
and (2) a landing bias in favor of upper-income neighborhoods outside of the
central city. Aa regards multi-family loan flows, the data revealed a lending
blaa In favor of upper- income, non-ednority neighborhoods In tha city of
Chicago. Outside of tha city, tha lending blaa waa In favor of mixed neigh-
borhoods. Lastly, tha effect of Income on multi-family loan flowa at the
neighborhood level outside of Chicago proper varied.
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SAM DIEGO
Population
Su Dlago County, the aola component of the Sen Diego 5HSA, bed a 1970
population of 1,358,000. Thl* figure above ■ 31.* parent growth elnce 1960,
aoosvhai higher Chan rim 27.0 parcant lacreaaa reglatared by California aa a
■hoi*. The Clcy of San Diego hul 697,000 paraone In 1970, a 21. 6 peccant
increaae over I960. That la tha aaallaac ten-year growth recorded for tba
city alaca 1900, with the caneua ahnvlng an average dacannlal increaae of 72
percent over that aevanty year apan.
Tha 1977 nadlan houaahold Incona wea $14,101 In San Diego County and
513,691 In tha City of San Dlago, both of which figure, ara halov tha Cali-
fornia nadlan of 31.1,629. Slnea 196S, lncoa* in other areaa of tha it.te
baa baan rlaiag Inter than la the San Dlago araa- In 1963, tha San Dlago
City aadlan Income una 103.3 parcant of tha atatavlda nadlan, while by 1977
It had declined to S7.6 peccant. Tha decline for San Diago County wan not
quite ao large: from 100.1 parcant to 90.2 parcant.
In 1965 retail aalaa In tha City of San Map) repreaanted 53.9 parcant
of tha county'a total. In 1977, that percentage had declined to 49.1 parcant
Salaa In cha city Improved, hnuavet, when compared to thone of tha atace. In
1965. 2.S parcant of Callfocnla'a retail aalaa occurred In San Dlago, but
that parcantaga gee* to 3.8 parcant by 1977. Similarly, tba County'a aalaa
lnccaanad froa 5.3 parcant to 7.7 parcant of tha atatavlda total.
Commutat Ion
In 1970, tbara vara 305,000 panose employed In tba City of San Dlago
and 505,000 alloyed In tha whole county. Of time working In tha city,
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t tboaa mUif III the e
«i of Ja Oiegn rMty. Only 1.4
There mi tblriy-foor cnwirlil bob operating 29* off 1cm 1b tfw
fa DU(S Mt 4i of DSLlttli 31, 1477. At aid-rear 1*79, the** nfftcw. held
11.9 billion Is IPC depoilti. of which the four largest banks bald 74.2 pareaat.
Ob March 11, 1978, twentr-alae savings ana loao associations operated •
total at 189 office* In tba San Diego area. The SiL'a had local deposits of
15. 1 billion. The Urg.it of tba SiL'i had a 29.7 parent deposit share, with
tha four largest holding 64.9 percent.
Houslns. Stock
The limit- county San Mago SMSA contained an
four faally itructuras as of 1970. About 56.9 peri
Euros wsre located In the centrsl city, 12 percent were local
of the SMSA (Tsble 9).
Only 10. S percent of the estimated 188, 628 (1-i fully)
the city of Sea Dtsgo w«r« In lover-Intone census tracts. Al
of tha 1-4 structural vara Id middle- lacoaa tracts, and 51.1 percent
Bated 311,481 one-to-
of the 1-4 family struc-
t 11.9 p
cited 1
i dlst
t of t
■pact to the astlaatad 106,616 (1-4 family) atructun
area surrounding San Diego, 90 percent of tha 1-4 itcu
sue tracts In which ths aedlan age of the housing .
t 1st*. All of the 1-4 iirar.imii vera locstsd In
t tracts. Lower-lncoas census trscts In tha urban
-minority t
a In tha
tock In 1977
ilther ulnd
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aurrouadlng San Dlagu accounted for 3.5 parcant of tha 1-4 atructuraa; aiddla-
lacoaa tract* accouutad (or 28.6 parent; ad upper- in cow tract* accoimtad
far 67.9 parcaat.
A* of tba 1970 Cimiui, tba balanca of cha San Dlago SHSA contained aa
aatiuatad 36,23V fl-4 f.ally) dialling atructura*. Of tUi auabar, oaa-fourth
■raa located la miMd canaua tract*, aula th* balaaca vaa locatad Is uon-
■inorlty canao* tracta. In tara* of lacea* breakdown, 5.9 parcant of tba
Income canaua tracta, and 55.6 parcant vara locatad lo uppar-lncaae canaua
About 9S parcant of tba aatlaatad 1-4 availing atructuraa la tba San Diego
SKSA vara alngla-fanlly raaidaacaa; tvo-f«mily availing* coaatltutad 3.3
parcant of tba total; and 3-4 family dvellinga accoimtad for only 1.7 parcant.
Tha 331,481 (1-4 faally) dwalllaia (tructuraa la tba San Dlago SHSA rapraaantad
a total of 334,809 (1-4 faally) unlta. within tba San Dlago SMSA, alnorlty-
haadad bouaabolda owned only 2.7 parcant of tba 1-4 atructuraa that vara elaa-
• if lad "ounar-occup lad . "
Of tba total 414,301 availing unlta la tba San Dlago SHSA, 79,492, or
19.2 parent, vara claaalflad aa "anltl-faally. " Savanty-ona parcant of tha
miltl-faally unlta vara locatad In San Dlago propar, 27.6 parcaat vara locatad
In tha urbanized araa aumundlag tha cantral city, and only 1.4 parcant warn
locatad la tha balanca of tha SMSA. Aa ragarda lncoaa braakdovn, 21.9 parcant
of tha unlta vara in lowar-incona canaua tracta, 49.1 parcant vara In nlddla-
Incoaa tract*, and 29 parcant vara In uppar-lncoaa canao* tract*. U*tly,
aixad and aon-alaority tract* accouatad for 29.2 parcaat and 69.6 parcaat,
raapactlaaly, of tba aultl-faally unlta la tba SHSA; minority1 tract* cootalaad
only 1.2 parcaat of tba units.
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Tibia 10 )oaultM the percentage dl*tributIon of 1977 MM loan fleam
within the Su Diego smsa. Additional breakdowns ere abawD In Table* 11 aad
12.
Geographic MatrlbuClon
In general, cli* geographic pattern of residential eortgege lending In
Ibc In Dlago SHSA la 1977 reflected tha geographic distribution o( 1-4 family
structure* only with respect to canaua tracta In tba central city. Tha city
of San Dlago, which contained an estimated 56.9 percent of tha 1-* atmcturaa,
received about 54.7 percent of the total number of 1-4 f mall 7 residential
1 in the smsa In 1977. Thia altuatloo did not hold for tha
area ovtalda sf San Dlago proper. Unerea* tba urbanixad area outalda
■rated for 32.1 percent of tha SMSA'e 1-4 family structure*,
■ad only 2'..1 percent of tba number of residential mortgage
a written. In contraat, cenaua tracta In tha balance of tba SMSA received
la tha percentage of loane relative to the percentage of 1-t family
ailing* contained tha rain-
In addition to tha foragolng, survey participant! la tha San Diego SMSA
16,068 loan* totaling $894 million on 1-4 family structure* located
da of tba SHSA.
Of tha three SHSA* studied, San Dlago claimed the high*. at average value
1-4 fanlly residential loan* written in 1977. Tha average dollar value
raaldantlal loana in tba SMSA overall ma 51,900, aa coopered to 117,100
$14,700 for Chicago and Buffalo, respectively.
The geographic landing pattern for Bultl-f emlly loan* In tha San Dlago
A ganarally corraapondad with tha geographic distribution of multi-family
ta. For tuspla, older canaua tract* In both the central city and tha
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urbanised area surrounding tlm city, u well ■* die tract* in th* balun of
th* SJtSA, received approximately the earn* percentage nmAnr of xultl-faally
mortgage loan* w th* pu»oU|i of ml ti- family unit* contained therein.
Ilia aula aireptlou to thl* pat: tarn Involved aavar canaua trace* In both
th* cantial city and tli* urbaulied area unrounding tbe city. Vbaraaa never
conaua tract* Is San Diego proper contained 44.7 parcant of tlia multi-family
unit*, thoaa ttaet* received 37.1 parcant of tha multi-family loan* written
In tha W In 1977. Haawr census tract* In th* urbaniaad area sin-rounding
San Diego, on tha other hand, received a higher percentage of mulli-famUy
luan* (29.9 parcant) relative to tha percentage ouabar of *uch unit* In thoaa
tract* (23.) parcant).
■ Distribution
labia ID above t.
cantag* distribution by Income level of th* loana
by survey participant* la th* San Diego SHSA.
e geographic distribution of the hauling
reported on BKDA atatassuit
Tha result a fane rally do n
stock In tha SMSA,
In comparing tha distribution of 1-4 family structural by income level
with tha r«*ld*ntlal loan distribution. It appears that turvay participant*
favured uppar-lacoae canaua tract*, priaarily at tha expanae of middle- In con*
canaua tract*. Specifically, up oar- in com* canaua tracta accounted for 39. S
parcant of tha 1-4 family residential structure* In th* SHSA, but received a
much high*! parcaatag* at th* total ouabar of raaldantlal loana written — 73.2
parcant. Kiddle-lacoa* canaua tract*, on tha other band, received only 21. 9
pcrcaat ef th* nuabar of reeidential loan* written even though tho** tract*
contained 31.7 parcant of tha 1-4 fanlly dwelling itnirtmni la th* SHSA.
Th* pattern of multi-family nortgaga landing alao did not corraapond to
tha distribution of nultl-fanlly unite eang all of th* lacea* categories .
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Hbereae lwn-liiiH emu tutu cnuiiid 21.9 percent of the nltl-InU;
units in the So Mego SHSA, they nulnd 1S.Z ptnat of th* Bulbar and 8.5
percent of th* dollar Mount of th* oultl-fanlly mortgage loan* vrittm. Th*
•hin of lueh loan* to adddla- and uppar-lncoaa census tracts. on tha cither
haod, generally approximated or axeaadad Ib« percentage of mil r (-family units
Head at Household CJapea
celved about 90 percent or worn of
ha Buffalo and Chicago SHSA*, this
a tabla 10 show that
JS percent of the fund flovs
nsus tract* received batman
ty tracts received 0.3 parent
[ tits cuss ton.
non-ndnority census tract*
ctutaa, but received 74.6
an In 1977. Minority and
a aaallai percentage of audi
foully structure* to thoae tno
eanaua groupings. A* regard* wltl-fanily nortgagaa, th* reapecttre percentage
loan flow* for th* thraa racial eanaua tract grouping* corraapoedad cloaaly to
th* actual parcantag* dl»trlbutlon of aultl-feaHly unlta contained tharaln.
WortK*** flows to Neighbor hood -Type*
Tabla 12 *u*jaarlxe* tba homing stock and loan flow* within tha San Diego
SHSA by neighborhood- type. Aa was tba cue for tha two other SHSA* studied,
ratio* relating Dunbar of loan* to number of structure* war* coaputad for each of
tha neighborhood-type* In the San Diego SHSA. The finding* are praeantad halo*.
did not hold true for th* San Dlago SHSA. Th*
noo^alnorlty cenau* tracts recall
for the aajor loan catagorla* reported. Mixed c<
20 and SO percent of tha fund flows, while
to 2 percent, dapendfng on tba loan eatagor
In tha cae* of 1-4 faanMy residential
accounted for 65.1 percent of tha 1-4 faall
percent of th* 1-4 fanlly residential loan)
niied cenius tract*, on tha other hand, rec
hi* Google
Uitb mpict to 1-4 f tally loan flam at tba neighborhood 1ml, the
data shoved ■ general lending blu In favor of non-minority, uppnr-lnee«n
neighborhoods. Tin exceptions to this trend van observed, hovevsr. Writ,
In the never, urbanlted tracca outalda of San Dlago, non-minority, lover-Income
neighborhoods exhibited the hlgheet loaa-to- structure ratio among tha ualgb-
borhood-typea represented. Secondly, mind, upper-Income neighborhoods had
the hlgheet loan-io-atrueture ratio among neighborhood-typea In tba balance of
tha SMSi.
Ae regard* ■ulti-famlly loan flova at tha neighborhood level, no trend(e)
emerged. For example, nou -minority, upper-Income neighborhoods bad tba blghaat
loan-to-unlt ratio In tha oldat canaua tracta In San Diego proper. In tha
case of nearer census tracta In San Dlago, however, elnority. lover-income
neighborhood* had tha hlgbeat loan-to-unlt ratio for nit 1- family loans. Tba
raaulta for nalthborbooda outalda of San Diego vara equally dlveree.
Conclualon
In gaaaral, tba geographic pattern of 1-* family raaldantlal nor t gags
landing In tha San Diego SKSA raflaetad tha geographic distribution of l-'t
family structures only with napact to tba cantral city. Raaldaotlal 1-*
■ortgage flova ahoaad that aurvmv participants tended to favor tha balance of
tba SMSA, principally at tba aipenae of tba urbanlied area outalda of tha
- aultl-faaaUy unlta In tha
itrlbutioe of auch unlta in
llatriboxlon of 1-4 family
cantral city. Tha geographic landing pattern
San Dlago SMSA corresponded to tha geographic
several araaa of tha SMSA. With respact to th
raaldantlal loana by income level, survey put
Income canaua tracts. Tha Ian Dlago SMSA van
nun-minority canaua tract* received laaa than
reported on 9fU etateaeats. Laatly, of tha three SMSA* axaadaed, loan flova
to apaclflc neighborhood -type* vara tha anat varied In tha San Dlago SKSA.
rcent of tha loan flova
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COWCLDSKW
Thin atudy focuaed on SOU lorn (Iowa In the Buffalo, Chicago, and
San Diago SHSAa. Difference* axlatad both within and eaong tha three uetro-
polltau area* with raapact to hollaing atoek charactarletlce and HMDA loan
flow pat tenia.
Tha bulk of tha houaing atock la tha Buffalo SWA In 1970 emulated of
■Ingla-femlly atructuraa located In noo-edaorlty, middle- and intper-lncaae
canaua tract*. Of tha three SMSAa atudled, tha Buffalo SHSA eontalnad tha
lowaat percentage of 1-4 fanily atructutaa la central city canaua tract* and
tha hlghaat parcantaga of auch attuctnraa In canaua tracta locatad In tha
balanca of tha SMSA. Additionally, tha Buffalo SMSA clalaad tha lowaat par-
cantaga of nultl-famllT unit* ralatlva to total availing unita and tha oldaat
housing atoek overall anong tha thraa SKSAa ezaalned.
Tha houaing atock In tha Chicago SMSA dlffarad fron that of tha other
SHSAa In oaveral reapecta. Flrat, alnoat 30 percent of tha total dwelling
units In tha Chicago SMSA war* claaalfiad aa "multi-family" — Che hlghaat auch
parcantaga anong tha thraa SKSAa eraninad. Second, with raapact to 1-4 family
atructuraa, tha Chicago SMSA had a higher ovnar-occupeiicy rata than a) char of
tha other two SHSAa.
Aa of tha 1970 Canaua, tha San Dingo SMSA waa charaeterlied by tha newaat
houaing atock anong tha three SKSAa and tha hlghaat percentage of alngle-
faally atructuraa. Additionally tha San Diego SMSA eontalnad the hlghaat
percentage of 1-4 fanily atructutee In both upper-inco** canaua tracta and
nixed cenaua tracta. Convereely, the SMSA eontalnad the eanlleet percentage
of 1-4 family etructurea la lower-lneone ceneui tracta and uon-ednority canaua
,d by Google
In addition to differences In housing stock characteristic* among tin
SHSA* studied, the three metropolitan irui exhibited different aggregate HU
loan Clow patterns. Based on the surrey data analysed, aggregate BMDA loan
flows Id r.ha Buffalo SHSA generally paralleled the geographic and deiwgxapalc
distribution of the houalng stock contained therein. In the eaaa of the
Chicago SHSA, however, the aggregate HMDA loan flows, for the Most part, did
not mirror the distribution of the SMSA's housing stock. Kith respect to tin
San Diego SHSA the results ware aixsd; the aggregate loan flows parallalad
the houalng stock distribution In some instances, but diverged In other casea.
Loan flow trend* to specific neighborhood- type a In each of the three
SHSAa alao ware examined. Again, the results varied greatly both within and
among the netropolltan areas analysed.
Baaed on tha analysis undertaken, several general conclusion* emerged
from this atudy. fleet, analyses of HMDA loan flow pattern* for Indi-
vidual SHSAa should Include consideration of relevant housing, demographic,
and other date. To cite an obvious example, mult 1- family loan flows should
be easassed In tha context of multi-family houalng data for any given area.
Second, Che results of the atudy Indicate that, for purposes of analyzing loan
flows, sach SHSA should be examined separately inview of differencea between
SHSAa with respect to houalng stock characteristics and Other factore. Third,
the results of tha atudy alao danonatrata the need to gather additional housing
and demographic data for those SHSAa In which poaaible distortions In RHDA
loan flows exist. tfbnrea* the methodology employed In this study focused
on quantitative houalng stuck characteristic* bas*d on the 1970 Census, nor*
recent data, if available, need to be considered. Additionally, attention
should ba directed to qualitative factors, not axanlnad In thi* atudy which
night help to explain poeelble distortions obaerved with respect to KHDA
loan flow patterns.
hi* Google
ANALYSIS OF SOKE HDKTGACt
DI3CLOSU1E ACT DATA
FtOH THREE STAWDAID
HFTBOrOLITAH STATISTICAL AUA
Inaucaic* corporation
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te caaalT ultli tba let aaa la|alatlaa C.
:C *7T0*O. All «BiT ta|H oo ll|raaa« >
Tka aBtlrala ™ lulttataa •• a raaolt at a nanaat at tba taaaf
■It [*• am 1.0*10, ■nil Urban Ulllll
collate** Is cbt<* Staadars Hatraaal.lt— It
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napond to a ttmtf n^olnaatt arlfluttat (con tks Inui rnjlim os laakliaj
ud Cthaa Mfalia. TfcU taaulrsa.nt iu clue tka ■Hlpti alac ta.r, data
coLlactsd and prsctaasd *t>Ua
1 af cha .!i«. far aaeh af tba thra* ntUs
b* Jariera phi call) arrayad Id
iccotdanca -let. >arl»i taaclflad mlahborliood
uumM, Ik. c.t.iorl.i ii
ft based oo [he fell* lot. fbaraccailetlcai
lacatlaa «... canlral city
™i»«. or urban «ru. caat of SKS*.) saa
of «™iM, ■lnrltr populatl
a, and Ii.com. la art" [o danlep aualiifal
"celibbortiood" rataiorlaa (or
lha.. .arlablaa la ddek af tka Itoaa DDUa.
dis-ijripkk data (TallaMa at
tk* «aaas (net leial far eack Bl dan
obtalDad aad analyiao la data
dlaldad IK* *7.'aalakasta*>ar)
cstaeorlu fat us la Faaaa 1 aad at bar pan.
of to* at adj.
TbU »«tl<. MQ i. «.
af art*, raasr,. prd^d -adar ruau 2. ,.
ud * of tad *»dj. Tfcud raa
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(a It at asset Prspeistlan
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tka sxeai-acT of sa Maniaes Maelsasn
Fkddd ] C^HMW
a C^.t.s...'
• Doubl* Co. aim*
• A Cnaeastnal rrasasnrt to Asanas Dtacrlalaatlen did taallalai Is
Jlaliaborhood M»rtt»(. L.ndi a» ■sttsrdS
Fhaaa « Haaaaassst lavsns
* CadBllaaaa daalrala*
• Coal si Coselllna. Km
■a Bartajass Dlaelaeara ateteaaaca
d Urt.i™ to kaiulat
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d Utility a* Ikd »osa
k»naas Maclaaata del'
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■as HsrtH«a D la donate dct10
d Natbeda t* iBfKr** 6 dan-adit scctitacj
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i t» d,p<,titon Institution dud]«c t» Faunl or uiu <l.cl— w
.■(• Ikll •iul>ll> .ltd prgtldld Imllhll Into |ll II 111 Ml r*Mltla|
— |»OiiiJ malar "■ttataiclallr ■Im11«(" iuii Ian.
• Malrlvn CO vraMdlna rh. sacs Mill J ta uoaact tha accuracy aa*
.j.1.,1 dapoaltorr luatllutlana pmiKitd Information -oS tha aacheda
< )UH» tfcait dl.clo.ur. liataaanta, tha HBfctr of public c.qo-.ti
iJ by li|itlt«T laatltotUaa Id aiaaan
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11* oil lent chdlacfa* '
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utljltlM pnilM tl» broW hi
mmttM th. riDdiap of th* its*; tn tk* loinwin
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oaa of tha eoarllaaca aaaljala «aa te dal.raiaa tba «staat to
•t.t.d aaaar tba aoaa Monmi Dl ■< I •■■ .:. Arc ara aaafal la
* eaafltaaca of raiulatad :,.;■;■;,;. lutlulliu "It* Ktla
HI Uckta act at 1MB (Miulur rafarraa to at Tltla fill).
i. dlCtaKIlClal p
a f lndlnaa at tba ci
aaaa mm ratlaei
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i Iw aorta. *. Uielmii data do amid* a •l.rtlni
•o alttralln nana fsi Dtt.inin, .nilir data. s>«M
h* mdui m mm
ImmnutHm
ra ■( ■>«■■(■ lHdiaf b» dtpaaltoiy
il.t 170 HSU. and thaaa imp. b.il... ■Itoaflr chat
In LdanHfyloa. and diitnlnlnt [tJllnin, and dlierlai-
argaaa'la (ail claKlr aatlaad,
. 1 alialf Icar-t parcast ■«• at too ■■»■••■ dlacloaura
•litlt raqaaat Ira a cltlian let tbalr 1*T7 d
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Ceoatj, Mm Taik aaj to fwntal tba («cuU|i at tba total v
•i wih as off lea li
i aaaai UO am lot
:a aartlai (••!•■ ••Uar-dMKlna,).
n aatalt la a atal? r.pi.rt aatltli
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Il oacom of M xroH of too .(l.rt »■ tfco |1 I I mml,mlM «.
itiofi ta K^sintua, lalUatlaa, obi orarooo Il a* tko lut* ilau of
■MM luitai f« too tana hsIm. UI«UatgC««i M.»]mt-
Mf 1o«m ntlk ■ odM *■!■* of inruiialili SI billion •»!• lilljllj.
In IrU Coa«7 IS, 'IU oortii[t loom «ttk • ccsMatd tiIu al iniulmttl'
I* il « llloi «ntt *aalr»4- In Cook Comer, 1U.W urtooi looo* wtxb o
■oklfoltLoa li noxtuii loaa don
of brii.iiv c. Hum* of in.,, i
r tbaaa liti (mo (Uclmmo ototoa
'E COOMrtOOl BOOiOBt cbo loaolm.
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dl>el»>4 t>r Jtpo.IIOtT Inat lint loo. 1» tht rhra* SHSAl tMcau* at «*f tlgaa
lapori.nl In. one -rr< liirnad during "» pTocan at Knotting, nlldaclni.
ind pror.ii.ing aorrE«£< loin IUI la •ccolJlEC* •[Id !••»!• t lOO C erlt«rl«.
* Oh ■ notional btlll, depository lootltut lor* (iccludlc^ thMv
net .ubjoet 14 dioclBanrt rtportiui ItDNII of ■*■■! nil* or
lo.n. In 5.n Dto.o, Ztla, .rd'cooV tCHllI, ro.n«tl«ly
it. MMrt w— nlwlj.
■ Th. potent... of aorta.,. l»a. .ri,l-tio«. ay KR|M*
to Cook County to 12.T ptrcant In K*n Dl.io County.
■ccouncad for •pproxlxttly ona-thlrd of loin orlelnatad
oj- th... In. cm.. loo.. uao»d toon. MM not i.port.d In «-lacloni»
■UUHim pttpaioc by to. Stilt of California, and dapoaltoty
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rpc.. of tU ttmtj of dtontl* CWKtlg m» to ■>
1(1(11 Inn Hand W mtdanciAl ptop*rtl« 1
■tady wn dn.hJ.iJ mttad <!.«., vtr* ■..!.■:.
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>• MJu. Ceanqiiaiitly. '
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4 o*rlat tin aaoa (lacal J'
or la taalr Byrvev EupoAdal. tT>« depositor* tfottllutioaa In £aa D1»id
rnportao1 la tbalr dladoaan atataoaati J40.S alUtoa ill abrchaaaa at aortj
loda* liawd by raaldaotlal Baal plop*! tf it fu Bloso. and oar uvlflia
aart|oga laamlBa foaortad1 In tba oMacloaan ataEaaaata of t
Tb« :■-.:<:-: . ■.- :. ,■.--,-( ■ dopoajtoij INUMI** tl
fit loan putchaau at Jil.7 allllea In 1
■ nt at tW taut nart»a»» laadlao, raaartaa on tlw ttaclowa mu
a*** if itMl laMiiattoaa.
Althomth tk* Tolana at iilaa aad putduiu at aartaita Isoaa aao
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IMaU* ttnllii Iim i ■■)« Mare
Tfcl* lr*> of lap!
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4 p«rf oraad bj Contract KaMarch Curpata
ctaalt it Ika mttbborboo.
-ftu b.iiC tub. f OilOKKf 1
arlsatlnf Md' for bona nortfafn
apaclfr ■ nalfnboTbood dVHRd
MBtlMi Io.ti otliluilom In n.lSht»rh
but (aeaoanieallr) unanplaiwd h
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cttntr) !■ altfanK ■
Btaful to aaalru two oboarrabl.
u coapared 10 the Ire: Id* net aaa aaaaltaaa o( loan dtf iullt
whether uruUlbriuB Bare ti** laadJLRa; patlana fc7 net ahh-orhood
Iba *ta«l palntld Out I list toll tjaaaU, iMlt conceptually "cartel' »*■ ■
practical drawback, and th..t it aheaU doc ba u.ei il>« to amlj.a aalak-
Dorhood heat Hit|i|i laaaiaa. aattaraa. The ptrttlnd difficulty Ml chat
or poltntlilly Hiatal col literal and tort out r tliitttniiititi lntha loan
■taclalon -procaaa. Hanca, an Equlllbrlira Hartat Nodal oat dtv*Euptd to
laaaMat rxttana juruat naUnfcorliood. ti] financial lnacltutlpaa. Iba aaxaaaa
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Th* teemej at inulln •*■ aaaa I aaaa • rutlatlcal la^la aailja aUca
la I1H tuffalo. Saa Ql**o, all CllcaflO — j»i laaaanlwly, Ht H aa^allag
atocwfliaj ariora. Taia aaalrtla *aakl«4 atatlattullr »aln aatia
i at taa laval at laocolltl accuracy Kkfn*d b» all Iramcatlsaa
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W »rea« "tjpa at loan1, or *<»»• "I
iiraey of afgrafatlaa totallad '-!'■■ I
icli. Ttiaaa lata hh toafaraa i|ilin tha data la Iba di.clo.
Accordlmlj, CHsiJdt Iodic, rartnid aa parcaata«aa, i
■I arran aa4a p.( uum tract niacin (a tt» aaakar ef
4 ariapt aid*, an anor lawl bnam 10 ai
wrcant aaa Ja*<ai» ta nadir tba ai^aptaUltt-r of a
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b* Im^inrui)- A^ta|irlDA it th* ::■.-■■■■■■
MN tn» ot loan, tjp. at pmp.ttj, H
aalacEad, ?roc«»d, and Taportad >■ diacloanra .uhwiii. aaaaaiaant of
ol hov IMMA ,h* 'IxC'iiu" ilitran!.. prapand aj aaajatt lna tlMlHI
raflaet thai! actual l«Unt pUHna.
nuapar of laacodtnt irroTi. Thla aru
kuibj H aora coaplai tan tba aataaa
' tba in«t wilt I at aayi In aUck
i* trait caa ba uU bj: a) iacludioa.
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Um. » t-ctaiiia. i» «w tucK—
ui.tio. c mum «) t»CWll*| ■ J
-err* ** a™uin«" «1bh la tin 41
t llsu (ma tho Jl.clo.
In <Ut« turn tin !!1« of tha ..poiltoij laitl
it of tba au i*ii 1 10 d
(■—Uaf UBlt of 15 M
According!;, two aajn
ralatli* to rn. MUr mac o
irnd .iiriKiii.m ■itbi Imli o
1 )u*iaant mi Hdi ttut aim lntU ti
10 tiKW h* ]■*■»< to taaaar th* accaptaallltr of ■ UielmN •ut«u
to aa ui|lal. Id orror Unl of !■• tan 10 aarcaat OH frlaaa to malt
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atatlatlcal* ™u«l •■
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■uffalo
ItaUaao
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Haaa Tatcaataaa of Iuukt
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a 19 aarcaac caatlaaac
7b. 1 - M.i tenant, raaaactlnlji.
•rod to ba ■arflsal.
Iremat.l to 7» pan.
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nctr patcatt •* tha MtlntlM la tha iaff •!• aad In du«o (KMa
and M ■ treat at tka laatltatlaaa li <ha ctUeate (MIA incurred .ui»t.rior.
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4 fludlniB oi> accuracy Cf
ila of mtfftlm leaner Ktliw4 br ID paraat of tka
lun. in th« lefCala nd tan Dl«,o MM* tat M p«c«i
mtltollo™ la (ha ChlcM° *MU oaca ooacciptablj lew.
ad ta iak» ta laattlfr tnaittniinn. nth ■aaceaatabl;
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4 •( tklm part 1 tta ttmtf •
• tsrlln at tk* «t-*j Imlnl tk* inniitlii ol f<
InaAim to *•••■■ tk* i«mtj of ha *•»(•(•
.».;... ^.i t? tta n^latair wmXmt, mt tba w»b4i ud
mlsiois IP hicvt^TiOk C
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97
PROJECT SUMMARY REPORT
Prepared For
Federal Home Loan Bank Board
Federal Deposit Insurance Corporation
In Partial Fulfillment of the Requireaenta
of the FHLBB Contract #677043
June 1979
RESOURCE CONSULTANTS, INC.
730 E. Highland Avenue
Phoenix, Arizona 85014
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it* -«f:.fl«i sr tte
- ?-jwi a=e «js
2 'tS5-T»ST', Phase • '^:a;
:ir.?s :si» r*7«r: i**ls vi;= =£2* at»t*a*=ts prtfirw! tc ;oofora
»itf*r-*i t=a; t=s r*»2er s;j£t rte let »=; S*gul»ticn -> Si'iog
sptfial e^seatiss ;e rae C*fiaitis3s ;T ttrss jrcrided in both
*;; statist!:* j»*c i=
i*v*l5?ta as a b7-prei-«
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TABLE OF CONTENTS
FOREWORD
I. MANAGEMENT SUMMARY '
II. SUMMARY OF TASKS PERFORMED 2
A. Introduction 2
8. Task 0 Project Management ''
C. Task 1 HMDA System Development
0. Task 2 System Data Files 3
E. Task 3 Conduct System Tests '
F. Task 4 HMDA Data Collection 3
G. Task 5 Senate Banking Committee Report *
H. Task 6 Management Report *
1. Task 7 J8B Coordination
J. Task 3 Project Progress Meetings '
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, MMODtOT 21W«*
In famaral all injsr uid on coaplatad alt tela tit* -— *T*,"""f ]
aaeiai.sas*'! ti** trta*. 7h* Maslatlao of BTO* $-jim«i
jr3c*»»iBir **t*flii«s sayaad ci* -is* orl^lsalLf sctedslad, ^tle!
r«»ult*4 1ft « 1«L*7 la producing it* final uaa;««-. r*pa«*.
TK* 1*La/» aneountar *J to-^r/ar , pror iia*J TaLuaal* la*i**S iau
eft* proc*»» of wUaetim Mil *«».
In iiir ojlatan, wr* on ib.i» arajtct grafr— — i < •«rj urT ' . ±3*
part M tB* assailant laoparatlon r*e*i»*tl frow *■. Saaart
'tmrvlax mat Bla aussaaaar. "ir - BlcSari Tuclcar af etx* F3L33, is
Or. tfilll** '. Vataon at tn* F3IC. '** partlcuIarLj :nm: -=■
4tli**Ot i»«L»t*.ii* ill fuidaac* rtnlsrtd tSroua;3cat :t» ?r3**<
97 Mr. Ia3*r-. lisMn* jnrt >iia staff, particularly *■- 'daily
Jttllar. KitBaut tBair afforta aur aork irauld aara jtjik iucH
■or* 4iffl*ult.
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II. SUMMARY OF TASKS PERFORMED
Introduction
Resource Consultants
, Inc. 's contract for work on the
Study Project was dl
vldtd Into the following tasks:
Task Dumber
0
Project Management
1
HMD* System Development
2
System Data Files
3
Conduct System Tests
4
HMD* Data Collection
5
Senate Baking Committee Report
6
Management Reports
7
JRB Coordination
3
Project Progress Mn*ting
i performance of each of
■ laaK 0 — Protect Hana«eient
The Project Management task included
effort, bi-weekly progress reporting,
review meetings with FHLBB and FDIC staff members ai
coordination of all other project task work. This t
active from the start of projeot work on October 1,
project completion on July 30, 1979.
■ laaHJ HMD* 3vatew Development
This task Included the development and programming t
Reporting System for the FHLBB computer. The work i
completed in the following stages:
.The System Requirements Manual was completed and delivered
to the FHLBB on November 16, 1977 along with a management
briefing.
.Delivery of the System Specification Manual was made on
January 9, 1979. Revisions to systea run diagrams were
delivered January 23 to comply with FHLBB specification
refinements. Final system specification revisions were
completed and written approval of specifications was
received on February «, 1970-
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0. Task S Senat* Banking Committee Report
Cue oT three major management reports written by RCI, this
report described the data classifications and content of the
data tabulations produced by the HMDA Reporting System for the
Senate Banking Committee. This management report was
corapUr.su in draft form on April IS, 1979, and following FHLBF
and r'EIC comment, was submitted in final form on July 31,
1979.
evel reports were produced under this task:
.Recommendations. Tor Changes to HMDA Reporting
Regulations
.Costs of Processing HMDA Statements or a Periodic Bnlj
.Project Summary Report
These reports were based on our experience gained during the
processing of HMDA statements for the three study SMSAs, and
on the statistical data produced by the HMDA Processing
System. Drafts of the reports were submitted for comment on
April 18, 1979, and final reports were delivered on July 3'.
'979.
■ Iaak ? JBB Coordination
Due ta the complex nature of the study project, substantial
coordination was required between RCI and JRB Associates,
Inc., the other study contractor. This was accomplished
throughout the duration of the project via meetings in McLean,
VA and Phoenix, correspondence, and telephone communication.
The RCI project staff received a very high level of
cooperation from the JR3 Project Manager, Mr. Janes
E. Russell, and his staff. This cooperation contributed
significantly to the timely, successful! completion of the
. Task 3 Pro lect Program Meetings
The FHLBB arid FDIC conducted several progress meetings during
the Initial phases of the study. The meetings were attended
by the contractors, agency representatives, congressional
staff and interested consumer advocates. Substantial
communication and an understanding of problems faced by
contractors and agencies resulted from the meetings.
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105
DESCRIPTION OF THE
SENATE BANKING COMMITTEE REPORT
Prepared For
Federal Home Loan Bank Board
Federal Deposit Insurance Corporation
In Partial Fulfillment of the Requirements
of the FHLBB Contract 0677OO3
June 1979
RESOURCE CONSULTANTS, INC.
730 E. Highland Avenue
Phoenix, Arizona 9501U
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*icn *,!■,* p»TJlrv«*fi';» if '.I* 3cm ■^sr^fijs SljeLssurai Ac::, Is id
*ugff**t»4 that tn* r»s4*r j-.jd/ -,n« lei »r.i a*f-J-a£ia« C, ji.»;=s
*p*«tal iee»nei'»n •» *n* lifinltiaflu =r ;*ru prcridwd in 3a:s
All statistics 'js*4 In trt* ;r*?ar*tian of Wis r*pcrt w*r*
l*tf*l9P*4 U ■ ftz-pratfuct of tK% Has* ^rt^age Ciaeloaur*
Reporting SyjtMi.
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TABLE OF CONTENTS
FOREWORD
I. MANAGEMENT SUMMARY
II, DESCRIPTION OF THE REPORT
A. General. Description
B. Categories of Data
C. Data Tabulated
III. INTERPRETATION OF THE REPORT
A. General Coutenta on Interpretation
B. Levels of Institutional Participation in The Study
C. Possible Sources of Error
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:i. DESCRIPTION OF THE REPOHT
A. General Description
The Senate Banking Committee Report is a two page
tabulation Of Selected Home Mortgage Disclosure Act
(HHDA) and 1970 census data for a specified Standard
Metropolitan Statistical Area (SMSA). Figure II- 1
presorits an example of the Senate Banking Committee
Report for the study project 1977 fiscal year period.
The Report is produced by the HHDA Reporting System
using data that originate from HMDA statements prepared
by financial institutions in the 3MSA. These data,
after careful editing and summarization, are combined
with Census Bureau demographic data to produce the
reports.
HMDA data are organized into a total of «7 categories
within the report. Each category has associated with
it housing and loan data for both 1-4 family and
multi-family housing.
b. aiaiflcliajLJim
The reports are organized into categories reflecting
four major classifications of data; location within
the SMSA, age of housing stock, income, and minority
status of residents. Bach of these classifications are
further divided as follows:
1. Location Within SMSA
Each census tract within the SMSA is first assigned
to one of four location categories: Central City,
Remainder of Urban Area, Balance of SMSA, and Hot
Classified.
Central City— -the contiguous census tracts which
comprise the core city (i.e., city for which the
SMSA is named) of the SMSA as defined by the
Bureau of the Census. For Buffalo and San
Diego, this area corresponds to the census
tracts contained (wholly or partially) within
the corporate limits of the aforementioned
cities; for the Chicago SMSA, this area is
somewhat more extensive than the corporate
limits of the city of Chicago. The Central City
tracts included in this category for the HMDA
Study Project were furnished by the FHLBB.
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■r :? :~~a- irea — ill census tract* (not
■U.r ;;T;;.e_;^*- -nttta th* SHSA that are
iiTtf i= -:« r*^;rml City and which have
; :«T*i.-» ;f -" rr sore units par
-Xv. i*»_=^=jf slijitl" more than three
=•- r^ _*.-;::. -=is approximates the
rscss ser s;^ir* xil* definition used br
Nc-. riissifi*; — all lezsus tracts not included
i= -.=• Tesira-. :*.;? lisis f-jrnisbed by tha FHLBB
»=i f?r .rtisr. ei'iitr M'-aisj unit or tract araa
Z. A5e =: =?^;=( ftJS*
After ceases :ri::j uv, ;tea asaiened to on* of
furs star iuSrsiviz*: :ijc: pa ;a*> -cdian aje of its
bousisj a;ac* is s*:iia*= frca 1970 census data.
The follows ;a:ecariea are used:
Slier — A stasis tra=: wiser* the aedian
ponssruetian ia:a or tSse r-.ousin; stock is 19B9
or before .i.e.. tha aediaa age of the housing
stock is 2S years ;r aider, in 1977).
.ons of the SMSA's census
in and aje of housing stock
j the lncone of the
h tract. The aedian incon* for
elated individuals uas computed for
; 1970 census data. The median
tract was then compared to that of
tracts vers classified as follows:
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Minority Composition of Census Tracts
The final subdivision of 0«nsus tracts used In
producing the report categories Is Resident
Minority Status. This status is based on the Race
of Head of Household is reported in the 1970
census, and Includes Slack and Spanish American
(only) as minorities. The tract was classified by
computing the percent of minority heads of
household of all heads of households, then
assigning categories as follows:
i 75* minority heads of
i 75* minority heads
105 minority heads of
5. Outside of SKSA
The HMDA statement format suggested in federal
Reserve Board Regulation C provides a space for the
total mortgages made outside the relevant SHSA.
The Senate Banking Committee Report format includes
these data where available as "Total - Outside of
SHSA" .
Data Tabulated
Six data items are tabulated for each of' the 47
categories of census tracts included In the report.
These data Include base housing counts obtained from
1970 census, and the actual loan counts and dollar
1. Number of Housing Units
Two counts of housing units were derived from the
1970 census for all tracts in each category;
-multi -family and 1-4 family units. Note that these
counts Include both rental and owner occupied and
vacant housing units (not structures).
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'I. MANAGEMENT SUMMARY
TFiia report oreaenta a aunmary t
Reaourcs Conaultanta , Inc., dur:
In general all major tasks were completed within the originally
anticipated time Crane. The completion of HMDA statement
processing extended beyond the time originally scheduled , which
resulted In a delay In producing the final nanageaent reports.
The delays encountered however, provided valuable Insight Into
the process of collecting HHDA data.
In our opinion, work on this project progressed very wall, due ti
part to the excellent cooperation received from Mr. Robert
Warwick and his successor, Mr. Richard Tucker of the FHLBS, and
Dr. William R. Watson of the FDIC. We particularly commend the
diligent assistance and guidance rendered throughout the project
by Mr. Robert Gibbons and his staff, particularly Mr. Wally
Miller. Without their efforts our work would have proven such
more difficult.
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SUMMARY OF TASKS PERFORMED
. Introduction
Resource Consultants, Inc. 'a contract Tor work on the HHDA
Study Project was divided Into the following tasks:
Task Humb.r Task Description
0 Project Management
1 HHDA System. Development
2 System Data Piles
3 Conduct System Teats
» HHDA Data Collection
5 Senate Baking Committee Report
6 Management Reports
7 JRB Coordination
8 Project Progress Meeting
■ rformanee of eaet
B- Task 0 Project Management
The Project Management task Included a continuous scheduling
effort, bi-weekly progress reporting, technical and status
review meetings with FHI.BE and FDIC staff members and the
coordination of all othar project task work. This task was
active froaj the start of project work on October 1, 1977 to
project completion on July 30, 1979-
C. TasK 1 BBDJ System Development
This task included the development and programming of the HHDA
Reporting System for the FHLI3B computer. The work was
completed in the following stages:
■The System Requirements Manual was completed and delivered
to the FHL8B on November lb, 1977 along with a management
briefing.
■Delivery of the System Specification Manual was made on
January 9, 197B. Revisions to system run diagrams were
delivered January 23 to comply with FHLBB specification
refinements. Final system specification revisions were
completed and written approval of specifications was
received on February 4, 1978.
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.System pr»(rmln( was completed sy !*my 27, T978.
.Final system documentation manuals jer» lalivered to the
73L3B on Jul 7 ", '973.
Considering ■.-.« complex nature of E9(3A Statement processing
requirement*, the efficient and timely completion of this task
was materially aided 57 the timely cooperation of the FHLHB's
Information System* Division Staff.
. ^a.i> > tot— B»t» EilM
The »7Jtea requirement* included furnishing several data files
for us* in controlling trie processing of BMDA statements as
well as preparing the final reports, curing this task, census
lata files vera obtained and processed, geographic data files
»ara constructed and edited, and demographic catagariea were
constructed for use with the Senate Banking Committee 9aport.
: for
i ware developed and specified in the System
Test Plan, which was dallvered in revised form on January 27,
1978. The foraal syste-o testa were conducted Jointly by the
PHLBB and BCI June 6th and 7th. On June S, 1973 the FKL3B
gave foraal approval for the processing of KMDA statement*
using the HMD* Reporting Systaa.
. Tasic * *HEi Data Collection
HMD* statement* Ppm toe tnree study SMS As ware obtaload b7
the FHLBB and FDIC, and were then sent to HCI for processing
through the HMDA Reporting Syatea. The first documents ware
received by HCI in eaarly May, 1973 and processing was started
iaaedlstely. Documents were received for processing through
the end of Deceaber 1973. Correction and replaceaent of
documents received continued until early April 1979, with the
final SMSA reports being produced on April 11, 1979.
The collection effort Included 671 institutions in the three
study SNSAs . 578 inatltutlon*' reports were received, and
usable data was obtained for 510 institutions. A total of
52,595 census tract lines of data were processed of which
13,151 were valid for use in the final reports.
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. Task 5 Senate Hapklng Comal r.t.*.« Report
Cne of tnree najor management reports written by RCI, this
report described the data classifications and content of the
data tabulations produced by the HMDA Reporting System for the
Senate Banking Committee. This management report was
completed In draft Torn on April 18, 1979, and following FHLOF
and FDIC comment, was submitted in final form on July 31,
1979.
■ fa ale 6 Management Reporta
Three management level reports were produced under this task:
.Recommendations for Changes to HMDA Reporting
Regulations
.Costs of Processing HMDA Statements on a Periodic Basis
■Project Summary Report
experience gained during the
□r the three study SMSAs , and
d by the HMDA Processing
coordination was required between RCI and JRB Associates,
Inc., the other study contractor. This was accomplished
throughout the duration of the project via meetings In McLean,
VA and Phoenix, correspondence, and telephone communication.
The RCI project staff received a very high level of
cooperation from the JRB Project Manager, Mr. James
E. Russell, and his staff". This cooperation contributed
significantly to the timely, successful! completion of the
Task 3 Project Progress Meetings
The FHLBB and FDIC conducted several progress meetings during
the initial phases of the study. The meetings were attended
by the contractors, agency representatives, congressional
staff and interested consumer advocates. Substantial
communication and an understanding of problems faced by
contractors and agencies resulted from the maetings.
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hi* Google
105
DESCRIPTION OF THE
SENATE BANKING COMMITTEE REPORT
Prepared For
Federal Home Loan Bank Board
Federal Deposit Insurance Corporation
In Partial Fulfillment of the Requirements
of the FHLBB Contract S6770U3
June 1979
RESOURCE CONSULTANTS, INC.
730 E. Highland Avenue
Phoenix, Arizona 35011
hi* Google
106
FOREWORD
This -report was written by Resource Consultants, lac, Phoenix,
Arizona, for the Federal Hose Loan Sank Board and the Federal
Deposit Insurance Corporation in partial fulfillment of FHLBB
Contract 6770U3.
The purpose of this project was to collect and evaluate Hose
Mortgage Disclosure statements prepared by financial Institutions
in three standard metropolitan statistical areaa (SHSAs);
Bufralo, NT; Chicago, IL; and San Diego, CA. The evaluation
portion or the project included an analysis of the Hone Mortgage
Disclosure Act and Regulation C, the processes used to coaplle
the statements required by the Act, and the usefulness of the
statements. Project work started on September 30, '977, and was
completed in early 1979- The work included four phases and was
performed by two contractors.
Resource Consultants, Inc., was responsible for Phase 1:
Developing the Home Mortgage Disclosure Reporting System,
collecting and processing disclosure statements from the three
SMSAs, and writing Tour projects reports:
. Recomnendaticns for Changes to HMDA Reporting Regulations
.Costs of Processing HMDA Statements on a Periodic Basis
.Description of the Senate Banking Committee Report
.Project Summary Report
JR3 Associates, Inc., McLean, Virginia, is
2 (Accuracy), Phase 3 (Completeness), and
Reports) .
Since this report deals with HMDA statements prepared to conform
with the requirements of the Hone Mortgage Disclosure Act, it is
suggested that the reader study the Act and Regulation C, giving
special attention to the definitions of terns provided in both
documents.
All statistics used in
developed as a by-produ
Reporting System.
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TABLE OF CONTENTS
FOREWORD
I. MANAGEMENT .SUMMARY
II. DESCRIPTION OF THE REPORT
A. General Description
B. Categories of Data
C. Data Tabulated
III. INTERPRETATION OF THE HEPOFT
A. General Comments on Interpretation
3. Levels of Institutional Participation in The Study
C. Possible Sources of Error
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Part III ,-f ts»
cif Jata pr»»»ai»
an.i a atumary ,»f
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aja of
i within the SHSA,
.=Sl£iM i»3*line housing data aa
"»* rni'.i loan nuabars and dollar
; litesory. Ill catajoritis and
it* 3aai:iaf Co-salttee Report art
■a =aamenta on Interpretation
■o-jaaian of possible errors,
s* SV.rA institution a
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I. DESCRIPTION OF THE REPORT
a. flmai BMBciatlaa
The Senate Banking Committee Report is a two page
tabulation of Selected Home Mortgage Disclosure Act
(HHDA) and 1970 census data for a specified Standard
Metropolitan Statistical Area (SMSA). Figure II- i
presents an example of the Senate Banking Committee
Report for the study project 1977 fiscal year period.
The Report la produced by .the HHDA Reporting System
ualn; data that originate from HHDA statements prepared
by financial institutions in the SHSA. These data,
after careful editing and summarization, are combined
with Census Bureau demographic data to produce the
reports.
HHDA data are organized into a total of *7 categories
within the report. Each category has associated with
it housing and loan data for both 1-4 family and
multi-family housing.
B. Categories of Data
The reports are organized into categories reflecting
four major classifications of data; location within
the SHSA, age of housing stock, income, and minority
status of residents. Each of these classifications are
further divided as follows:
t. Location Within SHSA
Each census tract within the SHSA is first assigned
to one of four location categories: Central City,
Remainder of Urban Area, Balance of SHSA, and Hot
Classified.
. Central City — the contiguous census tracts which
comprise the core city (i.e., city for which the
SHSA la named) of the SHSA as defined by the
Bureau of the Census. For Buffalo and San
Diego, this area corresponds to the census
tracts contained (wholly or partially) within
the corporate limits of the aforementioned
cities; for the Chicago SHSA, this area is
somewhat more extensive thin the Corporate
limits of the city of Chicago. The Central City
tracts included In this category for the HHDA
Study Project were furnished by the FHLB3.
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he tract* wars classified as follows:
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Minority Composition of Census Tracts
The final subdivision of census tracts used in
producing the report categories is Resident
Minority Status. This status Is baaed on the Race
of Head of Household is reported in the 1970
census, and Includes Black and Spanish American
(only) as minorities. The tract was classified by
computing the percent of minority heads of
household of all heads of households, then
assigning categories as follows:
Minority— greater than 751 minority heads of
household.
Mlxed--Over 101 but less than 75*. minority heads
5. Outside Of SHSA
The HMDA statement format suggested In Federal
Reserve Board Regulation C provides a space for the
total mortgages made outside the relevant SHSA.
The Senate Banking Committee Report format Includes
these data where available as "Total - Outside of
SMSA" .
C. Data. Tabulated
Six data items are tabulated for each of' the 47
categories of census tracts included In the report.
These data Include base housing counts obtained from
the 1970 census, and the aotual loan counts and dollar
volume from the HMDA statements for i-'i and
/multl- family housing.
1. Number of Housing Units
Two counts of housing units were derived from the
1970 census for all tracts in each category;
-multi-family and 1-1 family units. Note that these
counts include both rental and owner occupied and
vacant housing units (not structures).
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Hulti-Fa^ily Prsperty
Included the unbar aud dollar volua* of loans Tor
sulti-faaiLy prapartiaa aaie 5y the institutions
and reported far the census: tracts included In *acti
category.
1-» Fiaily/^ftt4r--0dc:JAiV3
Includes the naber and dollar volume of loans Tor
on* to Tour unit structures awl reported by
institutions for th* census jfacts included in each
category.
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INTERPRETATION OP THE REPORT
This section Includes Itiforaation and background data
pertinent to the use and evaluation or the Senate Banking
Committee Report. It la organited in three sections;
General Comments on Interpretation, Levels of Institution
Participation in the Study, and Possible Sources of Error.
A. General Consents on Interpretation
The following comments are made to assist in
Interpreting the data presented in the Senate Banking
Committee Report. No attempt has been made to justify
nost of the comments in depth since several other Home
Mortgage Disclosure Act Study Reports present the
pertinent details.
1. State Reporting Regulations and HMDA Data
The hone Mortgage Disclosure Act and Regulation C
allow financial institutions located in states
which have enacted State Disclosure Laws to furnish
tiie State Disclosure Statements in lieu of the
Regulation C specified statement. This may be done
only if the state institutions concerned have been
granted an exemption to HMDA reporting by the
Federal Reserve Board. All three states involved
in the 1977 study have been granted such an
exemption, covering part of the institutions and
data included in the Senate Banking Committee
reports. Other than the need to convert the
California State SSL computer tape data to be
compatible with the HMDA Computer System, little
problem «aa noted in processing state reports from
either California or Hew York institutions.
Although the Illinois State Disclosure Act was
invalidated during the study, the HMDA Study used
the available State Disclosure Reports supplied by
the State of Illinois. The Illinois State reports
provided a substantial amount of questionable data,
due in large part to vague reporting Instructions
and lack of clear labeling of reports. Illinois
required reporting of loan applications,
disbursements, and total loan portfolio. The
persons processing these reports suspect that, in a
large percentage of such cases, the institutions
were not sure what data were in fact represented by
the unclear reports. Errors in the Senate Banking
Committee Report caused by questionable data
obtained from Illinois State reports can be best
estimated by referring to the accuracy and
completeness studies performed during the HMDA
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106
FOHEWORD
This report was written by Resource Consultants, Inc., Phoenix,
Arizona, for the Federal Hon* Loan Sank Board and th« Federal
Deposit In aura net Corporation In partial fulfillment of FHLEE
Contract 6?7C»3-
The purpose of this project was to collect and evaluate Hone
Mortgage Disclosure statements prepared by financial institutions
in three standard aetropolitan statistical areas ( SMSis) ;
Buffalo, HI; Chisago, ILi and San Diego, CA. The evaluation
portion of the project included an analysis of the Hone Mortgage
Disclosure Act and Regulation C, the processes used to compile
the statements required by the Act, and the usefulness of the
statements. Project work started on September 30, 1977, and was
completed in early 1379- The work included four phases and was
Resource Consultants, Inc. , was responsible for Phase 1 :
Developing the Home Mortgage Disclosure Reporting System,
collecting and processing disclosure Statements from the three
SMSAs, and writing four projects reports;
.Recommendations for Changes to HMDA Reporting Regulations
.Costs of Processing HMDA Statements on a Periodic Basis
•Description of the Senate Banking Committee Report
.Project Summary Report
JRB Associates, Inc.
2 (Accuracy) , Phas
Since this report deals with HMDA statements prepared to conform
with the requirements
suggested that the reader study thi
special attention to the definition:
documents.
All statistics used in the pre
developed as a by-product of th
Reporting System.
,d by Google
TABLE OF CONTENTS
FOREWORD
I. MANAGEMENT SUMMARY
II. DESCRIPTION OF THE REPORT
A. General Description
S. Categories of Data
C. Data Tabulated
III. INTERPRETATION OF THE REPORT
A. General Comments on Interpretation
B. Levels of Institutional Participation in The Study
C. Possible Sources of Error
^Google
MANAGEMENT SUMMARY ,_
Selected Hone Mortgage Disclosure Act Data Tor an SH5A is
presented In the Senate Hanking Committee Report, organized
In 47 categories based on location within the SHSA, age of
housing stock, resident income, and concentration of
minorities. The report includes baseline housing data as
well as nulti-family and 1-0 family loan numbers and dollar
volume for each reporting category. All categories and
data included in the Senate Banking Committee Report are
explained .
Fart III of the report includes comments on interpretation
of data presented, a short discussion of possible errors,
and a summary of the response by HHDA Institutions
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DESCRIPTION OF THE REPORT
A. General Description
The Senate Banking Committee Report la a two page
tabulation or Selected Home Mortgage Disclosure Act
(HHDA) and 1970 census data for a specified Standard
Metropolitan Statistical Area (SHSA). Figure II- 1
presents an example of the Senate Banking Committee
Report for the study project 1977 fiscal year period.
The Report is produced by .the HHDA Reporting System
using data that originate froa HMDA statements prepared
by financial institutions in the SHSA. These data,
after careful editing and summarization, are combined
with Census Bureau demographic data to produce the
reports.
HHDA data are organized into a total of 17 categories
within the report. Each category has associated Kith
it housing and loan data for both 1-4 family and
multi-family housing.
B. Categories of Data
The reports are organized into categories reflecting
four major classifications of data; location within
the SHSA, age of housing stock, income, and minority
status of residents. Each of these classifications are
further divided as follows:
1. Location Within SHSA
Each census tract within the SHSA is first assigned
to one of four location categories: Central City,
Remainder of Urban Area, Balance of SHSA, and Not
Classified .
. Central City — the contiguous census tracts which
comprise the core city (i.e., city for which the
SHSA is named) of the SHSA as defined by the
Bureau of the Census. For Buffalo and San
Diego, this area corresponds to the census
tracts contained (wholly or partially) within
the corporate limits of the aforementioned
olties; for the Chloago SHSA, this area is
somewhat more extensive than the corporate
limits of the city of Chicago. The Central City
tracts included In this category for the HHDA
Study Project were furnished by the FHLBB.
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Remainder of Urban Area — all census tracts (not
necessarily contiguous) within the SKSA that art.
not contained In the Central City and which have
a housing density of 400 or more units per
square mile. Assuming slightly taore than three
persons per household, this approximates the
1,000 persona per square mile definition used by
the Bureau of the Census.
tracts within the
. Not Classified — all census tracts not included
in the Central City lists furnished by the FHLBB
and for which either housing unit or tract area
data were not available.
Age of Housing Stock
After census tracts have been assigned to one of
the first three location groups, each tract is
further subdivided based on the median a;e of Its
housing stock as obtained from 1970 census data.
The following categories are used:
Older— A census tract where the median
construction date of the housing stock is 1919
or before (i.e., the median age of the housing
stock is 28 years or older, In 1977).
Income of Residents
Each of the six subdivisions of the SMSA's census
tracts made using location and age of housing stock
is again subdivided using the income of the
residents of each tract. The median income for
families and unrelated individuals was computed for
each tract using 1970 census data. The median
income for each tract was then compared to that of
the SMSA and the tracts were classified as follows:
Middle Income — tracts where the median Income is
801 to 1201 of the SMSA median income.
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Minority Composition of Census Tracts
The final subdivision of census tracts used In
producing the report categories Is Hesident
Minority Status. This status is based on the Race
of Head of Household as reported in the 1970
census, and Includes Black and Spanish American
(only) as minorities. The tract was classified by
computing the percent of minority heads of
household of all heads of households, then
assigning categories as follows:
Minority — greater than 75< minority heads of
household.
i 75t minority heads
Hon-Mlnorlty— less than 10' minority heads of
5. Outside of SMSfl
The HMD* statement, format suggested In Federal
Reserve Board Regulation C provides a space for the
total Mortgages raado outside the relevant SHSA.
The Senate Banking Committee Report format includes
these data where available as "Total - Outside of
SMSA" .
C. Data Tabulated
Six data items are tabulated for each of' the »7
categories of census tracts included in the report.
These data Include base housing counts obtained from
the 1970 census, and the actual loan counts and dollar
volume from the HHDA statements for 1-1 and
/kulti-f tally housing.
I. Number of Housing Units
Two counts of housing units were derived from the
1970 census for all tracts in each category;
-mul.ti-faaily and 1-H family units. Note that these
counts Include both rental and owner occupied and
vacant housing units (not structures).
,d by Google
Hulti-Famlly Property
Includ&s tho nuaber and dollar volume of loans for
multi-family properties made by the Institutions
and reported for trie census tracts included in «ach
category.
1-fl Family/ Cfr*itA-04cwflIva
Includes the number and dollar volume of loans for
one to four unit structures and reported by
institutions for the census tracts included in each
category . /
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INTERPRETATION OF THE REPORT
This sde t ton includes information and background data
pertinent to the use and evaluation of the Senate Banking
Committee Heport . It la organized In three sections;
General Comments on Interpretation, Levels of Institution
Participation in the Study, and Possible Sources of Error.
A. General Comments nn Interpretation
The following comments are made to assist In
Interpreting the data presented In the Senate Banking
Committee Report. Ho attempt has been made to Justify
most of the comments In depth since several other Home
Mortgage Disclosure Act Study Reports present the
pertinent details.
1. State Reporting Regulations and HMDA Data
The Home Mortgage Disclosure Act and Regulation C
allow financial institutions located in states
which have enacted State Disclosure Laws to furnish
th* State Disclosure Statements in lieu of the
Regulation C specified statement. This may be done
only if the state institutions concerned have been
granted an exemption to HMDA reporting by the
Federal Reserve Board. All three states Involved
in the 1977 study have been granted such an
exemption covering part of the Institutions and
data included in the Senate Banking Committee
reports. Other than the need to convert the
California State SAL computer tape data to be
compatible with the HMDA Computer System, little
problem was noted in processing state reports fro*
either California or Hew York institutions.
Although the Illinois State Disclosure Act was
invalidated during the study, th* HMD* Study used
the available State Disclosure Reports supplied by
the State of Illinois. The Illinois State reports
provided a substantial amount of questionable data,
due in large part to vague reporting instructions
and lack of clear labeling of reports. Illinois
required reporting of loan applications,
disbursements, and total loan portfolio. The
persons processing these reports suspect that, in a
large percentage of such cases, the Institutions
were not sure what data were in fact represented by
the unclear reports. Errors in the Senate Banking
Committee Report caused by questionable data
obtained from Illinois State reports can be best
estimated by referring to the accuracy and
completeness studies performed during the HMDA
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Study Project.
Dwelling Unity and Loans
Mortgage lending concerns property, not necessarily
living or duelling units. Thus one loan on an
apartaent house night cover 50 duelling units,
while a single faiily loan applies to one dwelling
unit. The Senate Banking Committee Report
tabulates loans, not dwelling units. Therefore,
the validity of comparing the number of loans made
to the number of housing units available la
questionable.
Senate Banking Committee Report Data Categories
The report, as shown on Pages 3 and 0 of this
report, presents loan data in 47 categories. These
categories have been developed to allow examination
or Loan data at a level finer than the 5HSA total.
In many cases, a small change in the criteria for
developing the categories could have a marked
efT&ct on the data distribution presented. For
this reason, it is strongly suggested that the data
for specific categories be viewed only as
Indicators or loan activity rather than absolute
statistical evidence of any specific lending
conditions within the SMSA.
Data Errors
Several possible errors could cause distortion of
individual data within the reports. The analyst is
referred to a following part or this report as well
as other HMDA study reports for aore details
regarding errors in the data.
Completeness of Mortgage Data
The HUD Gross Flow Survey indicates that between ?Q
and 30 percent of the dollar value of residential
mortgage lending originates outside of the
financial institutions whose data the Senate
Banking Committee Report presents. The absence of
these data could cause a highly distorted view of
th« availability of Mortgage financing in Many of
the reporting categories. The effect of these
mortgage lending data at the SMSA level are
addressed as part of the completeness portion of
the HMDA Study Project.
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B. Lavels of Institutional Participation In The Study
Participation by institutions in the HMDA Stud; was
voluntary, follow-up contact was msde by th« FHL8B and
PDIC to Invite participation by institutions.
In spite of the concerted effort to obtain HMDA data
from all institutions In each Study SHSA, a substantial
nunber of institutions failed to furnish the requested
reports. Figure Ill-i shows the response of
institutions in each SMSA.
* HMDA Institutions
* Institutions Reporting
f Institutions Proeessable
% Institutions Reporting
1 Institutions Processed
Summary of Institute
Possible Sources of Errors
Several possible error sources could have a major
effect on the data presented in the Senate Banking
Committee Report. Since many of these errors cannot be
predicted or even identified, their effect upon the
data presented cannot be ascertained with any
reasonable degree of accuracy. The following list is
provided to aid in describing the nature, not the
degree of the problem. Error sources include the
following :
1. Misclassification of loans by reporting institution
2. Errors in assigning census tract codes to loans
3- Errors in tabulating loans (Institutions)
iurin?
>n's reports
Completeness of HMDA data; to what extent do they
represent actual lending or credit available in any
census tract or SMSA
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RECOMMENDATIONS FOR CHANGES
TO HMDA REPORTING REGULATIONS
Prepared For
Federal Home Loan Bank Board
Federal Deposit Insurance Corporation
In Partial Fulfillment of the Requirements
of the FHLB3 Contract J677043
RESOURCE CONSULTANTS, INC.
730 E. Highland Avenue
Phoenix, AZ 850 U
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HETOHTIHO REGULATIOHS
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128
TABLE OF CONTENTS
FOREWORD
I. MANAGEMENT SIMM ART
A. Major Recommendations for Changes to Regulation C
a. Re conn end at Ions tfhi.cn Involve Regulatory Procedures
II. DEVELOPMENT OF ANALYSIS AND RECOMMENDATIONS
A. HHDA Processing Objectives and Policies
B. Scope of Collection and Processing Effort
C. Developing Recommendations
III. RESULTS OP HMDA PROCESSING
A. Report Format
B- Report Header Data
C. Loan and Dollar Totals
D. Non-Occupant Loan Data
E. Census Tract Format
P. Census Tract Value
IV. RECOMMENDATIONS FOR CHANGES TO HMDA REPORTING REGULATIONS
A. Purpose of Recommendations
B. HMDA Statement Format
C. HMDA Statement Content
D. Gaographlo Coding
E. Financial Institution Response
P. State Reporting Regulations
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BAHiflEHBU simmpy
A major portion of tha HHDA Study Project w*a the collection
and processing of HMD* statements froa ST1 financial
Institutions In tha three Study SHSAa . During this
processing, statistics vara compiled for the purpoaa of
reviewing tha HHDA reporting, regulations and recoaaending
changes In the regulations.
The analysis of data froa the collection effort only
considered factors which could tie obaervad directly fro* the
HHDA statements themselves. Care una taken to avoid asking
reooamendatlona baaed on opinion or suspected conditions not
supported by the data obtained during processing. Thus,
findings could he presented regarding the use of non-ex 1st ant
cansua tract codes, but no comment could be aade regarding
the proper assignment of existing tract codes to specific
loans.
A. Tha aajor reconaendations for changea to Regulation C
1. A standard KHDA stateaent foraat should be required.
The standard should specify the physical alze and
arrangement of the stateaent.
2. Tha exact content of the hmda stateaent should ba
specified, not left optional. Content includes tha
aannar in uhlan data are reported, for example dollar
amounts should be reported In rounded thousands.
1. Censua tract scheae base year should be specified for
each SMSA and should be conslstant with the scheme
used in the latest Decennial U.S. Census of
Population and Housing.
5. If SMSA wide HHDA atatlatloa are to ba collected on a
regular basis, the regulations should require tlaely
submission of stateaents to the regulatory agencies.
Two reconaendations I
procedures rather thi
1. Exempt ions baaed on state law should be exaained to
insure that tha state regulation and instructions are
clear and un-aabiguous, and will result in data
clearly coapatible with HMDA data in both contant and
foraat .
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An axtanaivs effort should ba nade to educate
financial Institutions about census tracts and census
tract coding.
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II, OEVELPPHEHT Of AHALTBIS AND P.EC0HNBHDATI0H3
The purpose or this report la to milyte the experience
gsined In processing HMD* and related atata disclosure
statenenta, and the atatlstic* obtained fron the processing,
and to nak* reooaaendatlons Tor changes In tha HNDA
regulations.
A. HMD* HfoCBSSTKC OBJECTIVES AMP POLICIES
1. PROCESSING OBJECTIVES
Tha following objectives war* established for
processing US DA statement a during the study project:
■to evaluate tha (
or processing HNDA data.
I record foraat
2. PROCESSING POLICIES
Two policies uare followed during the processing of
HMD* data:
■to us* a reasonable level of effort to enter
non-atandard HNDA statement data into the
processing svstea but no atteapt to reconstruct
unprocessable stateaents, and
.to use production, clerical and processing
techniques slaller to those which would be
necessary if large nuabers of stateaents were being
processed on a continuing basis.
Thasa policies were dictated in part by coat
constraints, and in part by the need to obtain data
on produotlon techniques and coats.
SCOPE ar COLLECTION AHD PROCESSING EFFORT
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5TB Institution's reports were received for processing,
with usable data obtained from 5 10 institution*. The
510 processable institutions save rise to 53,595 census
tract lines of data, of which US, 161 wore valid for us*
In the final reports.
Since furnishing reports was voluntary on the part of
the financial institutions a substantial Mount of time
was required to obtain and, in lone cases clarify HHDA
data. The original 3 month processing schedule had to
be extended to over 6 months, due primarily to
difficulty in obtaining the HMDA Statements.
DEVELOPING ReCOHHEHDATIOHS
Prior to the initiation of HHDA processing, several
questions were identified for evaluation during the
processing effort. These questions Included:
of state regulations on HMDA
requirements i
msus tract numbers
Many of the statistics recorded by the HMDA Reporting
System, furnished a direct answer to these questions.
Other, more subjective questions were answered only by
discussion with the personnel Involved directly in the
actual processing of statements.
A review of the original questions, the statistical
results of processing and the observations of the
processing staff produced the recommendations made in
Part IV of this report.
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HESULTS OP HMD* PUflCRSSIHC
At HHDA statements ware received and processed the HHDA
Reporting; System recorded many of tha attributes or tha
atatenent* and their contents. This section of tha raport
presents a a unitary of tha statistics accumulated us wall as
pertinent ooanents.
A. REPORT FORMAT
Ttirae possible "standard" formats were Identified prior
to processing. These vera HHDA (Parts A J, B) , Illinois
State format { combined Parta A a B) , and Haw York State
rornat (ooobined Farts A & B reported on sue for*).
Durln| processing several other non-standard formats
ware encountered and ware processed under tha ganaral
category "Other".
HHDA Part A HI 17 42
HHDA Part B - 0 19
Total HHDA 11 21 61
Illlnola State - ■ 63
Haw Tork Stata 13
Other HA 16 39»
■California computer tape reports included in "ether".
The identification of report format is one Of tha naji
tlae-conaualng tasks associated with HHDA processing .
Standardization of format would have a substantial
probabilty of lowering HHDA processing costs and
incrtislns tha reliability of the statistical data
obtained fron the stateaenta.
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REPORT HEADER DATA
Several items were Included In this classification of
data.
1. Reporting Parlod:
The following labia illustrate* that most study
institutions reported, or could have easily
reported on a 12 month calendar year basis. The
Illinois State Disclosure Act required a 6 month
reporting, explaining the high percentage of such
documents fron Illinois.
REPORTING PERIOD
CALENDAR FISCAL
12 MONTH REPORT
6 MONTH REPORT
Enforcement Agency:
Regulation C requires that the appropriate
enforcement Agency name and address be included on
each HMDA statement. 79* of Buffalo, 97* of
Chicago, and 901 of San Diego institutions complied
with this requirement.
Statement SMS A
Most Institutions included the appropriate SMSA
nana on their disclosure statement. With the
exception of Chicago, all institutions who did not
include the SMSA name did Include the correct SMSA
code designation. It is suspected that incomplete
Illinois State regulations and Instructions were
the reason that 15 Illinois documents included an
Incorrect SMSA code or no identification of SMSA.
SMSA IDENTIFICATION
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4. Method or Preparation
Tha mathod used to prepare each document was Judged
during the statement screening operation. Since
statements could have been extracted from a
computer report then typed, the observed method of
preparation provides only an approximation of the
use of computers in statement preparation. Many
computer generated statements proved difficult to
work with due to the Inclusion of zeros in fields
where no data were present and the large physical
size of some documents.
PERCENT OF DOCUMENTS
HOW PREPARED BUFFALO CHICAGO SAB DIEGO
TYPED 56 85 29
COMPUTER PRINTED « 8 71
HANDWRITTEN - 7 -
Dollar Amount Representation
Conslstancy in dollar amount representation would
materially assist anyone attempting to work with
statements from several institutions. The
thousands of dollars format, rounding to the
nearest 1000 dollars and omitting the last three
zeros, proved by far the easiest representation to
work with.
DOLLARS 1 CENTS - 1
WHOLE DOLLARS 69 21
THOUSANDS 31 78
TABLE III-5
Dollar Representatlt
LOAN AND DOLLAR TOTALS
Regulation C requires the loan data to be totalled for
the shsa (Section I) and for loans -lade outside the
SMSA (Section II). The regulation does not clearly
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specify whit to Include In Section II Tor Institution;
Mho report for sore thin on* SHSA. In general, both
Section I and Station II totals war* not Included in
the majority of disclosure statements. Checking of
data for error* in addition ma rrt possible in •
Substantial number of statements due to the absence ol
Section I totals.
CONDITION OF TOTALS
SECTION I
INCLUDED
HISSING
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NON-OCCUPANT LOAN DATA
Non-occupant loan data have apparently been the subject or
widespread a launder. standing on the part of reporting
institutions. These data should be included In the four
1-4 residence columns of the statement. That la, a first
lien or home improvement loan on a non-occupant owner 1-4
family property should be reported twice: once la Its
primary loan classification, and again in the non-owner
occupied classification. Only in a snail number of
statements could the treatment of this item be clearly
discerned. Note that the Illinois State reports did net
include this classification in the report format. This
subject is analysed in detail in a project report by JIB
Associates, Inc.
PERCENT OF DOCUMENTS
BUFFALO CHICAGO 3AH Dlt
NONE REPORTED
CENSUS TRACT FORMAT
Two Institutions In Buffalo and one institution in San
Diego improperly included zip codes along with census tract
numbers. In Chicago S5J of the statements included both
icts and sip codes, probably the result c
itlstics and comments regarding
.ear errors in census tract numbers reported are included
i Section IV, Paragraph Di of this report.
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TV. RECOHMKHDATTOHS FOB CKAKGES TO HHDA HEPORTIMO FEOIILATIOHS
L, PURPOSE OF RECOKMENPATIOHS
tf HMDA reporting la to serve Its purposes, ■■ stated In
Public Law 94-200, to "provide depositors with information to
judge If depository institutions ire fulfilling their
obligation to serve the housing needs of the communities and
neighborhoods where they art located and to aid public
officials In tho distribution of public Investments In a
aanner that Mill improve the private investment environment",
the HHDA statements oust contain data which can bo used
affectively by the public, is this study project has clearly
demonstrated , the currant HHDA stataaants produced In
compliance with Regulation C are difficult to interpret and
The purpose of the following recommendations for changes in
tho reporting regulations is to produce HMDA statements that
may be identified and interpreted clearly, and can be used in
the aggregate to study landing patterns within a community.
B. HHDA STATEMENT FORMAT
In general, trie statement format suggested by Regulation C
appears to be workable. The major problem encountered is
that the format is recommended, not required. Slight
variations in format do not create significant problems when
analysing on* or two institutions' statements. However, when
attempting to compile and analyze stataaants for an entire
SHSA, even slight variations in format causa substantial
problaas In identification and us* of tha data. These
problems in turn inflate tha time and cost Of collection and
analysis by a substsntial factor, perhaps aa auch as two or
three times, in addition, tha data will generally be less
reliable.
If tha economical collection and analysis of HMDA stataaants
on a national basis la contemplated , standardised formats sra
an absolute necessity.
It is recommended that tha regulations require tha use of a
standard HHDA statement format. The standard foraat should
include the following attributes:
I. SIZE
Tha atataaent should be produced on 8-i/2"xii" paper.
This allows for copying en standard office equlpaent for
inexpensive distribution to the public. This standard
sisa permits easy handling and filing if several
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Institutions' statements are being examined or compiled
for analysis.
STATEMENT LA TOUT
The layout of the statement Corn should ba pra-prlnted so
that all data always appear In the saaa place. Free fora
computer layouts should not ba permitted. A pro-printed
fora has been produced and used successfully In both
aanual and coaputer (continuous fora) statement
preparation. A sample pas* of such a preprinted fora Is
attached In Appendix A.
A standard, pra-prlntad layout offers several advantages:
ius tract numbers is made less
.loan amount re presentation/ standard! cat ton baooaes less
of a problem by identifying and allowing space for
thousands of dollars only.
.full report and reporting Institution Identification on
each page Is encouraged by providing appropriate spaces
on the stateaent Torn.
.rapid, accurate data transcription fron printed
statements Is encouraged, leading to aore economical
analysis of stateaents for an SMSA or group of SHSAs.
C. HMDA STATEHEHT CQHTEHT
The existing six classifications of loans Included on the
HHDA Stateaent are assumed here to be necessary to meet the
purposes of HMD*. The regulations do not, however, clearly
define what relationships (if any) exist between these six
classifications. Further, since no "negative report" is
required if an institution did not purchase loans (a report
part aarked "no data in this category"), the completeness of
□any stateaents la queationable. These and other probleas
encountered with statement content are addressed in the
following recommendations:
1. TOTAL RESIDENTIAL LOANS
Approximately 11 of the study Institutions did not report
either VA-FHA or conventional loans, but did report total
residential loans. Since the first two classifications
are added to produce the last, no statements regarding
the distribution of loans between the VA-FHA and
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conventional classes can ba sad* using data collected
fron these HHDA statements. For this reason. If any
entry is made In tha total residential classification,
equal antry should be made in on* of the proceeding two
columns. If no ?1-FHA loans are Included In the report,
this night be cheeked in an appropriate space in tha
statement heading, allowing one column of numbers to ba
entered In tha total residential classification and
avoiding the redundant entry of the conventional
classification.
ADDENDUM ITEM ( HOD -OCCUPANT OWNER )
This classification has apparently caused a substantial
amount of confusion to the reporting institutions. 731
of the documents processed did not Include non-occupant
owner loans. After adjusting for Illinois State reports,
which did not include this category or data, T"l of
regaining documents did not include such loans. Analysis
of the HHDA statements shows that in several cases
non-occupant loans were tabulated and reported entirely
as a separate classification. It is suspected that the
sane error was made in other statements. Since this
Classification was not consistently reported, its value
In any '..'.■■■-.■ .te analysis is suspect. The treatment of
the classification must be mare clearly handled, possibly
including examples, in the Regulations.
REPORTING PERIOD
851 of the institutions reporting use a calendar fiscal
year. Although odd fiscal year reporting periods
probably have little effect on the evaluation of one
institution's data, such odd periods cause substantial
confusion when statements for an entire SMSA are
collected. This confusion is compounded by the practice
of dating reports with the issue date and not showing the
period involved. It is recommended that a one year
calendar reporting period be required for all HHDA
statements, and that the period year be clearly narked on
each page of the statement. Since HHDA reporting does
not (or need not) depend on the institution's fiscal
year, this requirement should not pose a problem to the
reporting institutions.
REPORT TOTALS
Loan columns ware not totalled on 6«l of the statements
processed. This omission makes it difficult for the
public to easily evaluate the total lending of an
Institution within an SHSA. Further, a valuable cross
check for statement accuracy Is lost. Such report (not
page) totals should ba required.
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5. LOAM OUTSIDE THE RELBVAsT SHSA
Th* regulation's intent in Including this aggregate total
seems reasonable, since It appears to allow reporting or
volume of loans outside the SHSi. towtur, In branching
states where an institution Is operating in multiple
SM513, tb* figures to b* reported are not clear. On*
solution is to summarize tba totals Tor each SHSA, than
raport th* total aggregate lending outside Of all SHSAs.
6. DOLLAR REPRESEMTATION
All dollar aaounts should be shown consistently,
preferably in even thousands, omitting zeros. Hundreds
of dollars have little Meaning given tba relatively large
values of tbe reported lending. Further, substantial
space is saved on tbe report for", tb* report becomes
visually less confusing, and consistent treatment of
amount apeeda comparative analysis.
P. GEOGRAPHIC CODIHG
The following recommendations regarding geographic codes are
limited only to those aspects observed directly in tb*
processing of BMDA statements during this phase of tb* BMDA
CENSUS TRACT VALIDITY
During computer processing of tb* BMDA Statement data,
each census tract number was compared with a list of all
valid 1970 census tracts for tbe appropriate SHSA. ir a
valid tract code could not bo identified, tbe loan data
associated with the failing tract number was rejected.
Th* following tabl
validity tests.
.e summarizes the results of the treat
BUFFALO
CHICAGO
SAN DIEGO
Report Lines Reje<
S All Unas
:ted 70
3
1,605
336
5
Loans Rejected
I Mortgages Loans
271
17,072
12
6B9
2
1 Value Rejected*
I Total Value
3,323
2
397,153
7
12,826
2
■Thousands of dollars
TABLE
: IV-1
Tract
Validity
Test Result
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An examination or the census tract related rejections
suggests that race value tract nunber errors do not
constitute a serious problem In either Buffalo or San
Diego. The Chicago error rate must, however, be regarded
as very serious In comparison to the two other SHSAs.
Further investigation of the Chicago data shows that 91
of the loans representing 5% of the value failed because
the census tract number was not even within the proper
range of numbers. An additional 1$ of loans and value
railed because ZIP codes, not census tracts were
reported. The balance of errors was primarily caused by
tract numbers in the proper range, but not valid tracts.
Visual examination of the rejected tract numbers leads tc
the suspicion that many of the tract number failures are
the result of poor formatting of the tract numbers and
the Inclusion of data from other SHSAs in Illinois.
Examination of the Illinois reports does not provide
sufficient information to identify the precise cause of
these errors. It Is anticipated that field work
performed as part of the HHDA study will provide factual
explanation of the sources of these errors.
>bably j
i of cl.
i for the Illlr
The Chicago tract edit failures, and to a such smaller
degree, those In Buffalo and San Diego, demonstrate a
general lack of knowledge of census tracts and SHSAs on
the part of financial institution employees. Before
accurate data reporting by census tract is realized, more
education and experience on the part of those coding and
preparing reports must b* gained. This education extends
even to the proper way of writing tract numbers.
TRACT SCHEME BASE TEAR
One of the major values of using census tracts as the
geographic unit for KHDA data aggregation is the
nationwide availability of baseline demographic or
housing data. Such data permit the evaluation of lending
with reference to many of the characteristics of the
population of each census tract.
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to subdlvisl
; numbers and boundar les are not pemntnt.
ict changes seldoe occur aore frequently then
'tars, it is probable that soae changes will
I SHSAs in conjunction with each decennial
irly ill changes In census tracts are Halted
txlstlng tracts. Thus, data for new
■ nay usually be 'collapsed* back to the original
tract. An examination of erroneous census tract numbers
from the 5HDA sti-.tien-.s indicates the presence of post
1970 tract numbering schemes, la more changes to 1970
tractlns schemes are approved in preparation for the 1930
decennial census, sore such occurences auat be expected,
making HHDA statements sore difficult and costly to use.
Census tract splits securing between each decennial
census will usually not effect the areas of interest to
an anlysls of lending patterns, since such split tracts
are usually located in high growth suburban areas.
It is recommended that BMDA reporting be based on the
tracting acheie used in the latest decennial census or
that the scheme to be used be collapsable to tbat scheme.
FINANCIAL INSTITUTION RESPONSE
Participation or financial Institutions in the HHDA Study
project was voluntary. The Home Mortgage Disclosure Act only
requires that HHDA statements be made available for public
examination. It does not require or suggest that statements
be filed with or furnished to the regulatory agencies. Host
institutions responded to the request from the FHLBB and FDIC
The following t
ble dl:
• HHDA Institi
t Institution:
He porting
f Institution:
Processable
1 Institution:
Reporting
1 Institution:
Processed
BUFFALO CHICAGO
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Although treated elsewhere In the HMD* study, the net loss of
data and resultant incompleteness of SMSA tabulations due to
non-response cannot be estimated or evaluated In this report.
However, if regular collection and SMSA wide processing of
HMDA statements is anticipated, the regulations must be
changed to require reporting and establish penalties Tor
non-compliance. To do otherwise would produce incomplete and
therefore unreliable data.
STATE BEPORTTHC RggULATIOHS
One of the objectives of the HMDA study was to use
supplemental data available in the study SMSAs as a result of
state disclosure laws.
The Home Mortgage Disclosure Act provided that exemptions
could be granted to institutions reporting under state law
where reporting under such laws was found to substantially
meet the requirements of HMDA. Disclosure statements from
state chartered Institutions In each of the three study SMSAs
were processed during the study.
The California SAL Regulations meet the HMDA requirement
Insofar as the data collected (the California Regulation
does not apparently require a HMDA statement, however, the
State Department of Savings and Loan la producing
statenents In HKDA format from data supplied to It by the
state chartered S&Ls), and
The Illinois Regulations ware extremely vague and resulted
in confusion in report content and geographic definition.
(These regulations were ruled invalid by the Illinois
Supreme Court during the study.)
It is recommended that axeaptlons to HMDA be granted only
after a careful review of state acts and the Implementing
regulations or instructions to Insure that the statements
produced will be comparable In form, content and data quality
with HMDA stateaents.
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Mortgage Loan Disclosure Statement
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Ml
COSTS OF PROCESSING HMDA STATEMENTS
ON A PERIODIC BASIS
Including a Description
of Processing Components
Prepared For
Federal Home Loan Bank Board and
Federal Deposit Insurance Corporation
In Partial Fulfillment of the Requirements
Of FHLBB Contract #677013
June 1979
RESOURCE CONSULTANTS, INC.
730 E. Highland Avenue
Phoenix, AZ 85011
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142
FOREWORD
This report wag written by Resource Consultants, Inc., Phoenix,
Arizona, for the Federal Hone Loan Bank Board and the Federal
Deposit Insurance Corporation In partial fulfillment of FHLBB
Contract 6T70U3-
The purpose of this project was to collect and evaluate Boa*
Mortgage Disclosure statements prepared by financial institution*
in three standard metropolitan statistical areas (SMSAa) ;
Buffalo, NY; Chicago, IL; and San Diego, CA. The evaluation
portion of the project Included an analysis of the Hob* Mortgage
Disclosure Act and Regulation C, the processes used to compile
the statements required by the Act, and the usefulness of tbe
statements. Project work started on September 30, 1977, and was
completed In early 1979- The work included four phases and was
performed by two contractors.
Resource Consultants, Inc., was responsible for Phase 1:
Developing the Home Mortgage Disclosure Reporting Systea,
collecting and processing disclosure- statements from the three
SMSAa, and writing four projects reports:
.Recommendations for Changes to HMDA Reporting Regulations
.Costs of Processing HHDA Statements on a Periodic Basis
■ Description of the Senate Banking Committee Report
■Project Summary Report
JRB Associates, Inc., McLean, Virginia
2 (Accuracy) , Phase 3 (Completeness) ,
Reports) .
Since this report deals with HMDA statements prepared to conform
with the requirements of the Hone Mortgage Disclosure Act, it Is
suggested that the reader study the Act and Regulation C, giving
special attention to the definitions of terms provided in both
documents.
All statistics used in
developed as a by-produ<
Reporting System.
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TABLE OP CONTENTS
FOREWORD
I MANAGEMENT SUMMARY
II HHDA PROCESSING REQUIREMENTS AND COSTS
Introduction
Processing Step*
Assumptions
Cost of Processing BHDA Statements
Estimating BHDA Processing Costs
Cost of National HHDA Processing
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MANAGEMENT SUMMARY
This report presents an analysis of the coats of processing
Hob* Hortgage Disclosure statements using tb« HMDA
Reporting System.
Processing costs are presented In unit work Torsi and say be
applied to any SMSA using readily available SHSa related
data. Final estimates say then be derived using labor
rates developed to Include direct and indirect overhead
costs.
The estimator is cautioned that the continuity of work will
have an extraordinary effect upon the cast of HMDA
processing .
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HMDA PROCESSING REQUIREMENTS * COSTS
A. Introduction
The purpose of this report is to evaluate the cost of
processing Home Mortgage Disclosure Act statements on a
periodic basis using the HMDA Reporting System. The
report is based on an analysis or RCI's experience in
processing the HMDA statements for the fiscal year 1977
froct the three project SMSAs: Buffalo, Hew York;
Chicago, Illinois; and San Diego, California.
The statements required by the Hone Mortgage Disclosure
Act of 1975 were requested from the financial
institutions In each project SMS* . The statements were
received by the FHLBB and FDIC and forwarded in batches
to RCI for processing. The processing was done on the
computer reporting system developed by RCI as part or
the project. Operating on the FHLBB's DEC-10 computer,
this system was used to record, check and summarize
approximately 300 HMDA statements; 20 from Buffalo,
729 fron Chicago, and 57 from San Diego.
Each HMDA statement was identified, screened, entered
Into the system, and checked for possible errors by the
computer. All statement data from each SMSA was
consolidated to produce a series of SMSA-wide
statements. Finally, RCI evaluated the results of the
computer error checking and production figures.
Written reports were produced based upon these
evaluations.
B. BEflfiUatM 2&MM
The following is a brief summary of the steps involved
in processing HMDA statements using the HMDA Reporting
System. Detailed step by step operating instructions
are contained in the Clerical Procedures Manual and
other System documentation.
Prior to actual processing, several tasks must be
performed to establish the management basis for the
project. These tasks include:
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it a^&a •■ (m Zaatitusica Llatiag* ar« aTailabla,
• f^fl l*tt*r raquastlsf ;-.* «;i Stitwntt is
Mint (4 ail MM loatltotioaa in aach 3H5a. Tha
lattar r »-,-•■■.* tii* atataajants chosen for
aroaaaalOf It la la para t It* this b* den* as soon
• « ;.mi^.,, »■', that It raqulraa "— ullil n raspons*
hi th* Institution. To ainlslz* turn-around and
141* tlsa, th« lnstltutlooa auat eoaply aa quickly
•■ peaaibl*.
Valnc th* HKD* ayataa projraaa, all (6)
ManUfloitlon lab*ls are prlntad for aach
Inatltutlon within the SM3A. Tha dark than sat a
ayataa for aach St
i folder for each
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institution within th* SMSA. The files ir« used to
retain the remaining label*, all statements, and
any other material relating to that specific
institution.
Meanwhile, the supervisor obtains the required
Census data files. Using this Information, the
G*o-Validatlon Pile is created. This is checked
against the Census Bureau PHC-1 and HC-3 maps for
each shsa to verify the accuracy of th* tract
lists. He also obtains the Senate Banking
Committee Demographic and Geographic Data and adds
it to the Geo- Validation File. This work must be
completed prior to processing HMDA Statements
through the computer system.
The supervisor then reviews the screening and
keypunch forms and instructions for possible
changes due to the nature of reporting in a
particular SHSA.
The supervisor must then train the HMD* statement
screening clerk and arrange for keypunch services.
The supervisor is responsible for reviewing the
keypunch procedures with the keypunch supervisor
and personnel.
Receive I Screen HMDA Statements
The clerk receives the requested HMDA statements
from the various institutions and prepares them for
processing. The statements are identified, matched
with th* institution folder, and verified for the
prescribed content. Each statement Is carefully
examined by the clerk to confirm that all
information is acceptable to the system.
Extraneous documents or Irrelevant information
1 ■■ column subtotals, incorrect cstegorles) are
deleted The clerk then completes the Document
Transmittal Sheet for each statement.
Computer Processing of HMDA Statements
The HMDA statements are now entered into the
computer. The statements are alphabetically
batched according to SMSA in groups of
approximately forty-five (15) documents. Each
statement in the batch is then logged Into th*
computer system. Each document is assigned a
sequential control number by the system. Brief
identification data is registered in the system
files under this control number.
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After hntry In the HMD A syste-a, the keypunch
Instructions art completed on the Document
Transmittal Sheet . Tbti batch la then sent to
keypunch for transcription onto aagnbtie tap* and
returned to the supervisor.
Edit Review and Correction
The final processing step verifies the form and
reasonableness of the indorsation entered Into the
system. The magnetic tape containing the HMD* data
Is read into the DEC- 10 computer files. The
supervisor then initiates system programs which
edit the HMD* reports. The supervisor reviews the
reports froa the computer edits. He determines the
cause of any errors and decides what corrective
action is required. The clerk purges and
reprocesses those statements that require change.
A certain number of reports are entered as
unprocessable because of incomplete or Biasing
information (these will remain so unless further
action is taken). Once all problems are Identified
and resolved, all institution statements will have
been accounted for or entered into the system. Jtt
this point, the suoervisor runs the consolidated
SMSA-level tMDA reports.
i the following
The HMDA regulations will remain unchanged.
The HMDA reporting system will remain unchanged.
: done froa a steady flow of
A daily record of institutions reporting will not be
required. This will allow one-step processing or
Individual tWDA statements.
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Key entry estimates ire based upon approxiamtely 000
HMDA statements. All others-are based upon 950
statements received (600 were processed, TO were
screened as unprocessable and 80 ware identified as
not on institution ID rile).
Cost of Processing HHD* Statements
HMDA processing oosts are presented In the order in
which they win most probably be encountered. They are
baaed on the assumptions listed above in Section IIC.
sognized: set-up oosts
Set-up Coats
Set-up costs say be classified Into three
categories, project related, SHSA related, and
institution related.
a. Project related aet-up costs
In general, project level costs include those
items which are not directly related to the
number of SHSAs or the volume of reports being
processed, or which nay be estimated baaed on a
rough approximation of volume and processing
Project organisation: includes selection of
project management, familiarization with the
HMDA Reporting System, project planning, and
project budgeting. The size and cost of the
project management function will depend on the
volume of work in process. The minimum size
project management function will include half
time of a Junior level project manager. A
nation wide collection effort would require a
very senior project manager plus as many as
four production managers. The cost of project
management can only be determined after the
number of supervisors and clerks to be employed
has been determined.
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Th« following tl»e should be allowed for
project set-up for the Manager familiarisation
and training of personnel:
Project Manager
Production Manager
(If used)
Supervisor 10 aan hours each
SHSA related set-up costs
Ibis category of set-up costs depends primarily
upon the number and six* of the SHSAs to be
processed.
Census data used for establishing the
Geo-validatloo File «ust be obtained, usually
from a commercial source. A budget figure of
12.00 per census tract will usually cover the
raw data cost. Additional costs to extract,
process and check the data will include (per
SHSA):
Supervisor 8 aan hours
Clerical Worker 2A nan hours
Computer Tiae $ 1.00 par tract
Haps 1 Materials J200.00 per SHSA
Institution related set-up costs
These costs include obtaining the HMD*
statements from each Institution and preparing
the clerical files to accoaodate the statements
when they are received .
File folders must be established using
system printed labels for each HMD A
Institution in eacb SHSA.
Clerical Labor .05 aan hour per
institution
Supplies A Materials 1.40 per institution
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Mailings oust be aade to each Institution to
Obtain HMD* Statement*. Since this work was
performed by the FHLBB and FDIC, we have no
cost experience resulting froa the HHDA
Project . Commercial nailing costs for form
letters would indicate a minimal coat of
$.50 per institution Tor this task.
Proceaalng Related Coata
This category or coats includes project related and
volume related charges. Although unit processing
costs may be estimated under continuous, regular
processing conditions, our experience is that such
conditions will probably not prevail.
For example, although the aetual processing for the
three HHDA Study Project SMSAa night have been
accomplished in approximately two months of
continuous work, nearly six months were required to
process all the statements received The
substantial difference was due to several factors,
including delay in the receipt of statements and
the need for sending requests to institutions Tor
clarification of statements.
The net effect of sporadic processing is a
significant increase in processing oosts, for
although the supervisor and clerks aay be provided
with non-project related tasks during lnterlsi slack
times, their efficiency drops substantially.
Project management related processing oosts
Project management includes scheduling,
progress reporting, problem solving,
supervision, budget and cost reporting, and
other similar tasks. The level of effort will
depend on the experience of the project
manager, the scope of the project, and the
support of senior management within the
organisation In our experience, HHDA
processing requires a fair amount of management
effort, possibly due to the level of financial
institution cooperation, the number of agencies
Involved, the non-standard form or HHDA
statements, and the polltioal nature Of the
subject.
^Google
A s-lnlmun project oanageaent effort will
require 20 aanhours per project week with no
production manager. A proceaaalng load
requiring five supervisors and clerks Is
probably the limit or on* project manager's
ability to control without aaalatance. On*
production aanager should ba added to the staff
for each combination or five supervisors and
claries aaslgnad to tha project.
The processing related project aanagaaant costs
can only ba astiaatad by first determining tha
nuabar of supervisory and clerical aan daya
required, than dividing by tha nuabar of
project days to obtain the number of
supervisors and clerks needed.
Volume related processing coats
Processing volume is expressed by two factors,
the number of HMDA stateaents processed and the
total nuabar of report tract lines processed.
A reasonably accurate estimate or these two
quantities is necessary if dependable
processing cost estimates ar* to be aad*.
Costs per HHDA statement. Depending upon
the existence of state level reporting
requirements, the number of stateaents to be
processed aay be estimated froa the number
and type of institutions In each SMSA. For
HMDA reporting inatltutlona the Part A
(Originations) and Part 3 (Purchases)
portions of the HHDA submittal are each
counted as one statement since they auat ba
processed separately. If state regulations
call for seai-annual reporting, than tha
institutions subject to such regulations
will have two reports to process, not one.
Once the number of stateaents is astiaatad,
tha per stateaant oost can be estimated
using the following factors:
Fantor ajj Statement
Supervisor aan hours .30 Han hours
Clerical aan hours .50 Han hours
Keypunch hours .11 Hours
Coaputer oonneot hours .30 Connect hours
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Cost p«r tract Una. Estimating the nuaber
of tract lines to be processed is difficult.
Based on our Initial experience, we
recommend the following method..
Note tbat this method is based on a rather
crude relationship that appears to exist
between the growth in an SMSA, its fori of
banking, and its number of owner occupied
duelling units. The aethod works reasonably
well with the three study SMSAs. It is not,
however, more that an educated guess at a
passible way to estimate the number of tract
lines to b« processed.
- Obtain the number of owner occupied
housing units for the SMSA from the 1970
Census PHC(I) Reports.
- Multiply the number of owner occupied
units by the appropriate value from the
following table to Obtain the estimate of
tract lines.
FINANCIAL INSTITUTION
STRUCTURE IN SMSA
FACTOR, TRACT LIKES
PER DWELLING UNIT
Statewide
Branching
Stable or
Declining SMSA
.01
Area SMSA
.03
Unit
Banking
Stable or
Declining SMSA
.025
Growth
Area SMSA
.035
Table II- 1
Tract Line Factors
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f*4* *mf §+»eifl+t SKSA. TS* m er :ui fan is
; . . *«*.f»t*4 57 *«iMtt3f tBS pTOCVSsis sosu foi
•-«•* s-,j«Jt 3KKU.
Krwt Isaor costs includ* ofTie* spscs sad
•qjlpstnt ma all ossrnssd charges.
Ceapvtsr Connect Tla* lO.OO/hr
Project Mensfer 3 5- 00 /tar
Supervisor 20.00/br
Clerical 15.00/hr
Keypunch 10.00/nr
?. rrfjeedure
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. The number of owner occupied dwelling units within
the SHSA: Source: U.S. Bureau of the Census;
Census of Population and Housing: 1970; Census
Tracts; Final Report PHC(i) - (for the subject
SHSA).
The number of census tracts In the SHSA. Source:
U.S. Bureau of the Census, Geography Division,
Washington, D.C.
Uslni the forms, the basic quantities obtained above,
the factor in Table II- 1, and the appropriate labor
rates, the estimating form may be completed.
Note that the coat of the project management function
depends In large part on the estimator's judgement of
how the project will be organized.
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SOB TOW. « »tfl.
TOTAL (TT-OT COSTS; - t »,*J4
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HMD* PBOCFSSINC UTHUTI
SHU HJLMEl_
PROCESS IB G COSTS
1. PROJECT MANAGEMENT! [Project Duration ■
.Pro] not H
B TOTAL * «.ano.
VOLUHE RELATED COSTS i
.8ap«rvitor< i.»» x .30 - 384 I
t eteteoents tot. bra.
■Clarloali 1.17S X .50 - 5B» MIS. - I »,e3i.
f etateaents tot. En. rata
1.1TB x .44 - • 519 M10. ■ 9 5. HO.
X -30 - u. Mln. ■' - » 3 -MO.
totThriT xmta
b. TRACT I.TNE RELATED: I
-Suparriaor: 40,429 X .004 - 162
tract line* tot. turi
■Clerical i 40,429 X .0X2 - 415
tract line* tot. ore.
40,429 X .007 • »3 |$10.
SOB TOTAL | 13 ■ 3*5.
TOTAL PROCESSING COSTfll-l <J.Ho,
TOTAL SET-UP AMD PROCESSING COSTS! - « SO ■ J**
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' J * « *»• "^.g^, • t^j - * am.
fP0«i 1 MSA tro)«eti 1/1 to Ola MM - »,l».)
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•C—C graphic Datai J73 X M-W - » m,
-Haya/datariala. , t (200. par mu - 9 am.
.tuptrrltnri • hra. ( I 20. - « i«#.
-ClarleaK 2* hra. I tn - » m
SOB TOXAJ. t l.SM.
]. INSTITUTION IET-DPi
""'"" i csfcgga " " h*-/""- " afcHH.' jfe " ' "•
.foppliaa, Matorlala,
TOTAL SET-UP COSTS: - t 3,70f
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BMDA PROCESSING ESTIMATE
5MSA NAME. Bottalo, W.K.
sue totae I a. loo.
VOLUME RELATED COSTS 1
a. STATEMENT RELATED i (
.Sup.rvl.ori 5" _. . X .30 - » , I* 30. - I W-
t iCBtenents tot. hra. rata
. clerical t so x .so - 35 It »■ - * "5.
( statesients tot. hra. rata
.Keypunchi 50 x .44 - 3 J if 10- - « »°-
.Ccciputar
aj 10. . I 150.
SUB TOTAL f 1,045.
.snparviaori Jt30 x .004 > 11 if io.
tract lines tat. bra. rat*
.Clerical 1 2630 X .013 - 33 if 15.
tot. hra. rata
X .007 - IS if 1C
> tot. hra. "ri
rata
SDB TOTAL f__
TOTAL PROCESSING COSTS ■ -$ *,0-
TOTAL SET-UP AMD PROCESSING COSTS) * S_
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HMDA PROCESSING ESTIMATE
SMSA HAWK; Sin Piano, CA
. 8CT-OP COSTS
1. PROJECT NANAGEMEBTi
■ Project Manager: 160 hra. • 35
rmS
■Production Managexa: - X 120 hra. »
noabar to
■Snparviaorai 1 X 40. hra. - an I | 2J ■ * U
mSn tot. bra. rata
SOB TOTAL > n.jn
(NOTE! 3 SMSA Project; 1/3 to this SMSA - 12,130.)
2. SMSA SET-DP:
■Danographic Data! in X S3. 00 ■ 1 M
f txacts
-Mapa/Natarlalai . I (200. par SMSA - 1 Jo
•Suporvlaoryi a hra. • I 20. m ( n
■Clarlcal) 24 hra. t I IS. > f a*
rata
SOB TOW. * 1,«S
3. INSTITUTION SET-UP:
Clarlcal: 57 x
t institution!
TOTAL SET-UP COSTS I - I l.mt
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8MDA PROCESSING ESTIMATE
PROCESSING COSTS
1. PROTECT MANAGEMENT: (Project Duration - \ Montha)
.Project Manager: 90 • ! 31.. ' ■ S vm
■ Production Manager: - t ■ - IS ■ S
paraoni hra/paraon tot. bra. rata
1 TOTAL
3,150.
2. VOLUME RELATED COSTS:
a. STATEMENT RELATED: ( 5T X 2 - 1H )
( inatitutiona I atatanants
.Suparviaon H) X .30 - JJ , . IS ?n
I statements tot. hri. rata
. Clarical i 114
tot. Eral rata
-Keypunch: 114 X -** - 51 II 10.
.Computer
X . 30 • 35 ag 10.
b. TRACT LIKE RELATED: I 238.900
I oiatr os
a factor t
. Supervisor: 7170 X .004 - j> || 20.
tract lines tot. lira, rata
-Clarical: 7170 X .012 - 96 II 15.
tract linea tot. bra. rata
•Keypunch: 7170 x .007 - 50 || 10.
TOTAL PROCESSING C0ST3:-S_
TOTAL SET-DP AND PROCESSING COSTS: - $
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F. Coat of National HWDA Processipa
At the request or the FHLH3 the cost or processing all HNDA
statements for all S-HSla was estimated. The estinattr la
baaed on the coat figures developed during the HHD1 study
project. Since the scop* and eo»ple*ity of a nationwide
project would bo such greater than the study project, and
since aany of the work quantities are extreaely difficult
to eatlnate, it is important to reallie that the actual
costs could vary substantially fro* the estimate- as much
as - 301 or to * 50».
383 SMSAs
8,138 HNDA reporting institutions
Processing would require on* year.
Project xanager 35.00 per hour
Production aanager 26.00 per hour
Supervisor 2C.00 per hour
Clerk 15.00 per hour
All costs are based an 1979 dollars.
Costs if no changes in reporting regulations:
. Set-up costs
- Project aanagenent 1 33,000
- SHSA set-up 32*. 000
- Institution set-up Ljjflflfl
Total set-up costs i 376,000
^Google
Proc&aaing coats
- Project management $ 220,000
- St at anient related 341,000
- Tract line related 30S.000
Total prooeaalng coats 766,000
Total project cost $ 1,142,000
Changes In HMD* Heoortlng Regulations, produced by
Resource Consultants, Inc., as part of the HHDA Study
Project.
The recotnnended changes would moat probably
substantially reduce supervisor and clerical processing
tiae, giving the following revised estimates.
- Project management $ 32,000
- SMSA set-up 324,000
- Institution aet-up 14.000
Total set-up coats $ 370,000
Total project coat
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cmpblc inn. thui d»t. an not eC ■ itudirt (cnu
•eaa at th. mlablii of Utuitt. Bum, knovladgi
4a« U ■ ami tact dou not n*e««clly Uply
Aqqt«q>tBd Loin*;
3i,iii«db» Google
l catuut tiic:. Tha patt<m ttt landing In prtv
p although ■ J*po>itocy Institution could h*v»
c*d by tha four hypothetical mplii aaaan la rigor* 1.1. In the an
HRmi lout origination oarghaaaa, nail (alai by fmi institution
illustration that tha loan* and pEopactiaa ara aquinlant, and tna aa»
orlglnatad no loana In oitbtr yUi, pan
orlo lnatad 40 loana In tba tint («i at
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OxlgiBCttd 0 lout
3i,iii«db» Google
a of ear aulfsl* ahso be* lu witaaga dlnluni «i
ljiuatlon of tha net antlxaly vaald beva « caflluci tcr ivlt in
CTrTr.J>Ci.fiB AT* B*da flX lUeliad i-aqaiding retention Of the BOM H
oeilbla tlumUiii to It. Tbaaa linn
nvolved. The Unt (In etepa are u aoelyele of potential ai
raeulatlene- Tba fifth atap vae to determine the extent to -which hoaa kertgaffe
halffnl In detecting poealbla differential! In tha pattern at landing eecraj
it saapllanaa with tha
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- outline, ip.llirvj
* (pacific :itw«iii al 4*U ts ba HpKMd, Tha ■•coed ■Melon lndlcati
1«Mr. tbua Una Hctigm prowiaa * a«f mitivt bul> t<x an aailrali
• fnnllT nlatad Htqita lew u
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<w*t* on anlcl-fHily awlllmi)
no BBltWiaUw AialUitai
mat en aultl-f mily AiMlJ.inaa) .
c ef til* npHtloa naolnMBU at ti
ElUlw fat aaeh •■» in which Llhui ha» or branch atflo
lean data bw tha caiurai tract in which tha prlnglnal raaldi
togathar in tact Ian Two of to* raeort
inwpaction and copying
3i,iii«db» Google
3i,iii«db» Google
SHU aap, than a. ta pnMda a unlqua ba;la toe daplctlng tha gaognphlc
pittvn of nortgaga lanaUaaJ and baaa taj aaam loaua within tba *mha.
Although aggregation o* tha. dau by can.ua tracti pea. llnltatlooa Is Judging
landing pilluiii an m -naighborhooi- basis. Chi fact that tba data ara In thla
Tba laUmiag dlacuaalcB of -hit tba «ata to M ansa It pnawntad 1>
i "jartgaga Lou Original Una »
4 ajnrtgag* loan orlginatlona o.
3i,iii«db» Google
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3i,iii«db» Google
■•«:*-.-.-■ at pvrAaaat
UUmrb tb... fear u*npl«a at iwrttna •» kjpothrtlcal. tiny «
d purchu** COE A iw f<M paxlad, r
a quail-; !>>.i.> ln<) aUck. Tli. BEOblaa thia ciMtii for
diaotpauca data li that tawladea at rtia voliw of landing, la • puticsllr
3i,iii«db» Google
which la no* 10 iwi old. Although o»ant»a intonation la anallahla in an
only Mi of tha ruublii of l_TI.ir.it. Tbu, imtw.rfg. of tha pattarn at
■and.nq In a ckiiji tract doat not pacaaaarlly iaply knowladgu of aithar to
orarnll cancua tract laral charactarlatlca of tha raclolaata and pxoputtlai
to auggaat that canaua tract! at. not tha optimal haala fat nr-ylno loan*
oa dlacloaura atataaaata. In fact, canaua ttacta ax* tha only gaographlcal
unit for which adacniata geocodinq toola aorltt. Although nalghboihoodn. a
totally hoaoganoua unit of population, might aaaa in theory t&HI ajora
: eewad Includai dapoaStacy ixiatitutlcan -with aaaata
a offlc* in an HSU. inauranca coanahlaa, 10115™ banter:
tntag* of Boitoaga landing activity.
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t*a !■■»■— J* »» i» ~U - I 11 aw tM — M— Hi— ll«l t)
■ «^ »»— « X a wai*
* f*rt -V 04 Jin-U^-m'*
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icon iIh raqolraa that ■tpll— 1» fin cwdlt ba notiflad of tba ai
of an.appllcatlcn nithtn K i.ys iltn -j. applic.tion la ooaplatad and )
•OBoUa oBtmz en* .!■;-.- ,-.-■. ;:,-,':..; In Tiel* Till and th* 140*1 cradle
opportunity Act Both role MijuUt lor. Fart 338. fair Homing, naqulntlon
Otalr aBtBBltr and enntant. |[.qul»tlcm >, Equal Cradle opportunity. =■> to.
j Maaalng ■aaulatloaa
3i,iii«db» Google
( ttB) Itti, ta i»ll:m i>
* relieving ijjfauHtlui on Inmiliin or «
Eaquiraaaat lj. for lnatltutiona In an 6WIA with umu on-r 110 Million to
■nlntain a lev *o**t 011 has* loan (nqulclaa and anpllsmtiau . raxt 33" wj
graneod is Ti tin VIII and E«, and Its r*"H1J
i.t«! in Chat Inhalation. Thnna ptoolbltnd Um nr
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2 ram imraJjUji t«rtj lii. iii-i, n™-QUcrUtJi»tiac>«qniri»iiit»,
Tba r*±r Landing Kaqulitlcu
.h* P*d*nl Hca* Lou l*nk fyaE**. tod ■*•
" providta. In p*rt, t
n tin bull lit ttun a
omaaatB of gth*r dMLli— la t3
3i,iii«db» Google
hi* Google
Although U»» proviaLooa
nrlaspln} utur* -of -cumat nguli
t tin roic-» ngolatlen MM «i« "» torn"* toil.nmq o>t> ij> o^lUnc. «
action JW.4 "Ill b* In -coBpLluic* with tlM B*cordk*apina *pguir—iim of
•cfclon 202.13 of taquLatlon B. slaillarly, the luk Board'* Aagulation Part
y folfllimo th. k
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± ncjutUnej lt« nontrd of hnlsln] to Mot
•itr Inclndlna effort* to
tktlitb d.lln«tlai, by aaob dapoiltory Institution, of 1U local
MljaOta anno ■orroundlng •men of flu or group of off leu, including any
. u, c» of tan* bull in daUnanttno. lu
inu IMtil at countlM In trtilcfc tha inmHtution't
flu* ar« lauud. . , .
landing territory, uhlch la daflnad u that local
ally, tl« obpoflltocy lnBtltotlona an required under tbn ngulatinAa to
In tlM public of tba exlatanca ud araLUIilllEy or the cm iuuhiiI and
Mtloo mud in
Hat lualf i* readily
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t tb* diacioiiic*
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It, wt f«i th* 1iig.il oat
a nitiJn an ■•». » nady
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;•■.: ttftm Met « i jm . n>WI «■ in oui nput u Tie i. tzh] ,
IS IHl3^-.L^ ttva W^hM of d»po*lt<Ky
rlf«n )-l jcdt1««« *
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lUtnaH, lBputlali.tr. *nct ulthoul aiicrimlMllon..." Lik* Tills
pxohiuu UmWMa In nil «n«lc bhiiiMim br all fina *t
V wucurt, ritu raapiet to an* aaaast at ■ milt
ilu> BraolMtad lull Id 1'
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0 nqolna tb*t appllaaHta far cradlt ba w
ctiglnatlon Rgqulf
I IKiiulng Mgulatlsu , aubjact L
tha third of thaaa iii|alia—ila U nlamt to tola aapsrt, tad thua. only
tha proTialoaa nlatad to thla aaatlOD -tl
3i,iii«db» Google
a fid Liming UffumUcn so lxqalxan or ifplicant-i 1
n aUUMon. th. rwjalitloo (equina tlmt
• •paid to elm* UiUd in ttn linlilitlm.
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■^'.-.1.. .- - FT Sggl —
■ found Is tha ottilgiw of rnAmtld g>
ocmyantM of otar an Llimr* la tho irtolflltT of tb* amtlllngW
3i,iii«db» Google
f Uh dwllina;," la aapllcltlr pnhiblead. In wMUUm, tin iqiUUn
U4d oi tha ™», ate. , at Uw llrln, la tb* »m*Wft— 1 i» ^Miuitrt
According to this daflAlelan, * MlapfegM
t tnatltnclcH an nqnlnd t
i Baqul»tlon a, Equal CEadlt CpOBCtttfl
a ftav ( ny tin aaaa broad n
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ii that, -* nuik cellfectinq data In etvplluica Bi«
nttnti th* pnhlblcMI bum *OM by BOOft to Ihm il— %
J) RMCOgdlmplnq 0( th« ■ mil lQBEd'H
ii.titut.™ .halt KUin r.cord» ■■ nqaind b, U <X» 3U.L
• nqulitlon, tlunion dram upon — jiiHtlai 1 ia utun
■ nsplnaaata of |H| iln Inn > ineulnlm te aertvaa* u
■iwlyita "111 focus as Um li
dltH that tfi. lagulataiy ■qnciu ■BiMumji ragulaud financial ll
oftantlua of *■
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it* neord at halplov t<
*!*■ lndijig tanitecr. ahlel) u laflnad a* tint li
rlnally, tin dapeaitarr iBMltntlou •» «a>lxa4 BBa« tha nvalatlna to
inteca tlH yuiillc at u» iiliuin ul anllablllty of u* en iUf at an*
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hi* Google
mmm
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3i,iii«db» Google
rigora 4.1 On, in lll||l— I III (i
■ tin baaia of tt» aulyali
ocaatian ana analyaia raipilrad baton ■ oaf lnitlTa aaatia— nc of oaapllaaoa
id public of fielali. . .■id .officiant Intern
laglalatiia asroUBf i aianrialnaeion and radllnlna. nui sMlnltten Car
<«aruiad M H m lM*al *»** ****" «■«■"*— *M^1°«, -plnh b» tha BBBfJ
funnel— H —tit, —llalt 1* oaf laad u — -njL—fnl tart atata flajajja.
"■W" HHM »— * - «*" «»««-ala looMlo. of at «"—**■
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■noulntlon JIM aatabliak 11 prohibit** Bun iu
(1) , ml tba ipuUl o
* of tba ladltldnnl [frwidlng M/*l» bu Eh* afKlcr
■tqulr— M. rut m.t, iff t pt toller, anldmlfr- T'"Vl -
PUertai—Uan fa '""ri ad* ■«• ■*> own tin u in «xplleltly iau
QlblUd buu. In addition. Hi* roanlatloa iuui to* oxonlnlelon on
laglaldtlon. til* location of aaUln) la ■ richly alpilflnant prohlb
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*?at*d i< u>. amam tnet ItntX em t» •l.rln.d by • mo-at
< KlfU U* •hum in flfon 4.1. Ttl* Initio tt^t ..p.r.t
MM1 <Mly tbrwuh OH of lm|IH>ln inf o™ t ion Wat d.f in. th. - j»po. i t Ion
•9* o* aaallisf, .r. prohlh.it *1 hh Ui«t
aiTlat th* ptttun of tton wlnbl** ■» •
■ cctrrlda ■ — Hli»|fnl tHli B
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p«tt*ra chat are gaoflcapMivall.j' acrayaa. lhwa eo«pUanca caqulraawnta
■ilk UHElIUd d»agr aphid thac alattlr pro. Ida. 1 ■aulogful bull (or
«|illm Inclaa*! m, oolgr, milmll orljjin nad^hborhood, Incm,
ud •»• of J—lllag. max provldin] i lau saanta^tul buia (or ciapariaon
uaiattm, and 500a [UQ naicU* or rlqhU jnntad undar tha Cnuiau Cra
a fqulf Bnt* "ight
indirldul applicant, and
■ Oaf lnad by Uaa f*— *'-' Hi
ccmyiium .ich tha nqilnam. uau Men of taoaa thai eataosrlai
■ Mnetlr hhCbI tipa—i On. mill —.m" la juaji ip»li allj *
• ownu* «* <u*ta b
< availability of thll lafwtlOB. Third Mcauu ponulatioa v
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Ktw duclo«ir. fen in Mnetlr nlMit to tJ
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• applicability °» »oa*ga»a 41«clo«» data, t.
fl applicability, tt
■ tec <Jaf inlng
. Cor aaaaailng landing
lling. ■ piohlbltsl Mil sndu rOM fgalatlf
only cutiMitly
gaographlc naala (DC diaplaying pattavna c* nortgaga landing within
though dlapUylng sortgaga landing pattaltM OB tha baaia of actual
1 ba aura uaaful. this approach ia impractical ■—■— . of t
3i,iii«db» Google
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F LDDIHG BY THREE I KST ITOTI OH 3
3i,iii«db» Google
3i,iii«db» Google
aortgaga diaciotiv* data alart tb« uar u tha po— lhlllty of running a
diacrlmijiatory UnOlng practical. Thin ohuntlui i. bud upon tha Col:
nlud at t—n 1U0.000 and JBOO.OOO.
• pattama Of low landing — faMd, pnclaalv ^0 *■* racial
■» aiplaln tin ai*(ar*ntial landing pattama. Bathing In '
} My b* explained fey On list that no an* applied far .
Die diiCrlninatary landing practical nor strong aTldi
i obMrvatien la b— J opcci tha tollowlag finding* i
■ 2 and 1, which hava high ■lno
3i,iii«db» Google
hi* Google
d tin. bull at Urn teas of (and. Mextgiifa
d not ba nalpful iji unrauarljig >uch iao
id aDfllcatlona.
analyala ftifht to sBplorvd to aid 1b Elita
i raqulrad i*f or* da
Laia itringant daflnteloB and
3i,iii«db» Google
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Location of a— Ulna, CM II— t taloi (a) (ml (t) , ud th. CIA apaclll
ba arnyad and Uaaalad witj lvidlnq information OS toa Mil of
rLi*c, tba othar coapLlanca xaaolraaanta ('
c dlrttlbotloe at tin diparttory inMtrttnticn '(
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* ppliclM IDd pTQCtdana fCK U4 OB to* aortgao*
I -will u ehaii ui* In eifU Eights and compliuu:* invHtlgatlou. rolloving
right* ipiclalliti using
a tha (o)Jo«ti>B DM»ar»pli«, uihii to ttaasa fin qmiUra K
I highly ■lgalfiDant In light 0!
3i,iii«db» Google
i lallq 1M Ik SBlltpla r
i F— IM< UjcrlmlaMocr laadint pcetusa or malm.
«'■ nl elMl ri4hu mriiiiit'i rfiiiitr tu urn tb« acn«*t*
3i,iii«db» Google
3i,iii«db» Google
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4 corpentloa put 1'
t preliminary datvcalu-
q juBiAT^ra^ACad dat* en «ly fvalbl* L
.■ public. Conpequantly th«y «U fait ooap*ll*4 ti
3i,iii«db» Google
• U(9*lf hmdnit 1A tfa* Btttnd dun by dapoaito
! ipnciMlr " C*A«U tfBCtft, □£ -Aft Larga -fed in(vpi«l B«ny C
:aav*r*aLy -^* *yp* Jf i»:^i*i::ciu -which zwadar hoM Bortd;*?* .
tupocift uii ran,.] Institutions in th* u Dl*go a;
In Olio*,*, bowar. • alonlflcant nokear of iuUIgt
ir ottic* location, to ota., ratios*.
In. lun uau neb „ tMU., major
(in I. I«u —i. KM* SM-rtlty
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t BOWS ICCCia DUOMIW MTK >I Tig PULIC HIP PIJQ«IT3lg
* public ,„i 4apoaltory lnatltutlona. Vn by the public 1» enalyiid Ij
Hi at too Iiiih. Briefly, there am "hat aaaa «B the public Hkj
■ detail aid, ara Oie public In fact aaklno uee of tba data? Daa by
obtained in vlalt* to 44 depository lna
corporation, ad frca publiaW r
■ by tba public
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3i,iii«db» Google
c is not in finding pattutd of ndlinio? or diacriBiiutirvn
CM— uilty. Th* dttn ra potaatlnlly aj
a tin put of public Uurut gr°v* In ot*»lninj li
*g*lii»t tba pnttnrn of Li
■Ubytla public IB light of ■
■plinnc* in tb« following *■/■■
by my of eta pi-olLlblt..d b,
3i,iii«db» Google
3i,iii«db» Google
d Oiii:«jo ynsviibil li
/ UgOESTS ITIB f
an"
HES-a Ltlu-j krc«M* of
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ML.
■ rtpcctlna. It^lf tlm m
■ Onltad ItlUI L«q» nl trriay UHoUUdl'l nm? told tha tollcvlaa
u* that th« puljl ic do** not und*e-Bt*nd dd
1 public iVm not . ■■. ind tn« t«n*u» ti
d l«pc«cl*«lf ud u th« but* fee ■tal— Uf
3i,iii«db» Google
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paiallal thsaa ia IMa ■tody.
«atnrr pletbn
dantlfyioo fend datuinq redlining fc
cant oarcamagi at U» KEtoavi din
UB*d Jjy the regulator-/ aganclaa ■■ an lntagral part of chair
■ Although ho« »r*gago diacLoaura atarfcajit prorida cha- only
provlda a way of eeaainlAq thia data.
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• si- m-
t tabulation! , - 13 CPU J.
» >iul cmilt opporTunitt »oe," u nc
t mm ty-t— , -bob- wnw( i
*nd Equ*l ceadlt Opportun
!•* Uit.nt ot th. bom non,!,! DUcio.nr* *m.
•Board Hatrcnolltan scitliticil U*u - Utility of tb* ■OH llortnaaa
3i,iii«db» Google
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2<»
nortgng* Landtag ntuni
Hortgng* Cflmpin t« *nd 01
L— B— [*«rri*d Lb Acquiring and using Data
for tba coaplatanaii Analyii* . . . .
3i,iii«db» Google
to ti C l7 1 f * Ol" " Mta
Mo«o.o. loo W.1M.1-. in S« Dl.,0 County
E 1 COUTH IMt 11 t T fl II 1
thabar of Nortgaoa una orlgiMCoa in ElU
>w — wu~ .. .... <— «
rtrctiitug* of eh* Dollar ABOunt oC Hortgaga
COO* Co Da El t tinl i
Cod. —»*■—* ■ ftocw
Orijiiutimo flaring 1
■ Landing by Dapoaltory
Hortgag* Loan Origination* by Dapositocy I:
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■ Si* tttrt rfHlll) lai tka F*4>nl a
n* .tody b.„D » I*pt«b*c :
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Colt of Hlaaplllnj li
DtllllT Ol tb. ■«• Hor
far l^tniii iu lafealrlu' •bllltj t° ceaflr ■
3i,iii«db» Google
ttudy — Chl=*jo, »M DUgo, and Buffalo. Thin ctaplUtian
not raflact Mm coiplete volia. of lending In ttw the** SNBta.
aa analyala coaplataa tha toUl landing picture by providing
uli for uaoaratandinq and intorBratlng
reporting by eh™±i»; the Hint of leading by th. following a
a BHSA MlIlH tliay Claim •.
i nputliu In u SaB*
3i,iii«db» Google
1 landing pattern et dapsaitory lnatitutiona •
th« raaaona tor tha vuiatlou ■an to* raailn. To accnpliah tha ce«pl
naaa analvBla, data on tha aoEt^aga landing activity of thaaa cellar: typaa a
laadan had to ba fowrd. Talidatad, and analy*ad* Tha aathodology uaad to
•eoaapllaB. thia tut lnaolaad tha following atapa.
origination! lnvcl"lng a
3i,iii«db» Google
■aa darlvad for Ian Dlaoo Coonty. Oar BnalrBla,
r InclnJlnj tarn OB «Klg«I *l
IB pil*p«U Or pTOp*ni*B
J appllad to axnlnda large contraction mod httmin— ECOp*rty laua. Th«
rltaria onad In Bach of tha thraa couotioa ara daaciibad in datail to
rtoag" landing; data for 19TV In tarn, of thaaa apaclflad czltarla.
■a data coapilad frga. tha dlnclotura
a orlglnationa and puxohaaaa. Ttaa auatoar and anoant of aach
3i,iii«db» Google
loan origination
. rinally, th.
tab
fui .t.t~ent, bob mpu*4 fa the
•aU» ma, ,mi
•a. tn. coapi.t
■naly.i. 1. r«t,i;.« to th. .ingl.
Lb*bbm «Hr b<
in In tame ol popul.
ion .no loan, in th. SKSA. Bacauee
Of th**. thTH 1
■ltBtlonl tha •
.. derived froa th. eoBplrt.nu. .naly.la
can heh only..
-VI apprcx^ctio
act
he bbMb. .Kara of BorfjBq. landing
raflactad by MM
JlKtann IMa
■>u
Th. COBplt [.»*•• .ft. 1-/5 LS BO... hOHTU,
prorlfi. nli4 ■■
W« olthlH
vol™, and percent.™ o! aorta*a*
ludlae by aapsBitexy lnMltutUni
"■
«h« Ibbo... 1b cbUbbbt ya« UD.
tBBSSa
Thn* tn»
Of findln,! MI.
nl fro. CM .tuny, rint, THtlHtln
•atliBata. of th.
voluu icd pert™
Be),
of landing by varioua typea of landara
-.r. OM.1BB. Co
Lh. n.tlon, .ad
kin
ad for tha three countiaa in tha atudy.
Saoond, ion. of
he -aJOt I«H1I
tor
ha varlatione in tha landing pattern.
.nono th. thr.. t
™a.l *■ det.
m4m
d. Finally, a lusttat of liapertant
la.aona VAM laa>
ned Air In, the p
ffl«
of acquiring, validating/, and proceaalno
UTtsao. low <**« i» ■c^rdu-.c.
It]! fcagUlation C criteria. Th.... too, ■»
olacuMad Ik .hi
npttt.
orlain.tlonfli In 1977, over $17] billion
IB ralfe.-.l.l «
Ft***. :.;ans «r
ori
^.triUH-M^Sa.... All
d.po.Itory inatit
TltlOBl B* SB
■xrc
al benJla, autul ..vino, banka, and
HvUiqi •« lo»
«ncUtlga)-l>
■atta
c. aublact and not >uHjact to dlacloaur.
IHiUWHiUB
.»d «.t p«™
Of.
hi. tot.! enl— in 1.77.
Far purpeBBB of utit aulyalsr
. 1. O,.-.:-. CO CB^. th. Batlonal
PaMffJI trf BOrCo
■ tOB orlolBBtl
on. by wrioue type, of lmlin iq.lnit th*
pattern, by Choi
lenior. In th.
j™
countiaa. Tabl. S.l provide. ■ coaparlaon
of tn. piTnnm
at tn. dsim «
UOB*
originated by alrl typo, of landara
nationally and In
3i,iii«db» Google
:«itaqM Cor dapoaltory L
titutian* nd not just Elm* subject t
gi bank* slit Id only IT *t«t*i. ftbd
it 1»U by 4.poiitory institution, la
WH>
1KIWL
™OTm°
coom
CSS,
C-^ltah
H.l
9.3
l».»
U.4
»t«.i «„1=,. lu*.
!.»
~
«.s
«.ln,. , L-> U«1M1«.
13.1
M.J
10.1
68.7
tart,^. C^-l-
13. S
IS.7
)•••
S.J
JUneallufloua coapulaa
I"
7.«
l.t
Mi™t. ««1-
12.1
t.l
2.*
TOTAL
100
1«
wo
100
•tttc diKlonra uportlug
Diago county fc* • high DC "7.9 percent In ci
3i,iii«db» Google
>l*tv*a> wiftia shor that th* lubdiAg patt«ru 4
n nxlad ntMllhrahly —ow tin thxu onmtlH. T
't only data in ludan iubj*c
3i,iii«db» Google
n 4iBcl<wur« nfortlng. Td* BarcgA^a lamr. orig ijsat Lena of dapoaltevy
■ertfav* lsnu ttwt «■ grtgliwtad by all itapotltory
3i,iii«db» Google
im igmitim ■* ■■»— ■ °*" '•* «*■ c<
«■ Hn l—raag through tb* p—— ■ op MgdJJUi
.latlonahip b*tw**n aHpliclt loan MlKtlon
i Tho ntton nd iBpllaitioH of vbt«altiH le th* >nmi le
i Tbo Jiff lenity of aaCtiaf aortgaj* ll
ooonty offlcaa or tltla nf^ponloo to
ntflwltT ef eb» loan ooloctlon cril
3i,iii«db» Google
■ capiat* plctnra of all nalOaatlal landing aetlWty
jy iapualtury linti tut torn mfajact Co radaial1 o
ji tha thru Btandaxd MatTOBOlltaB statlatlcal a
md ctmpll.d. Tha naulta In thia compilation
a coajlrtiMU analgia coaelata* tha total landing pictura by providing a
antitativ* aatlaata of tha ralatlv* abaxaa of aertgava t— **<-g by dapoaltocy
atltutlona aubjaet to dlacloaoEa taportlng raquiraaanta and by otbar typaa of
3i,iii«db» Google
raoortlno; bacaaaa t.h*r
t> arcrt^HaJi thi cr^laraaaaa uuLyiLi, data on tba BOrtgaga !■
ttlvlty of tbaaa cellar typaa of landara had Co bo fouatd, valldj
nalyaad. torn following ntaaa nan Imreluadi
i HajtfUltlon of d*u fa uefc IW
a nlitln fraction of landtag by «t> typa a:
Digitzed by GOOgk
dill baton PjUtlng any acta*ji£ to «cquir« ari w it in Mm analyst
~jrtq«9« landing [iHini, *r aaaiyai* nn
La in¥»*tlfl*>tLoo of laKwapar or dlacrlalBatory l—fllm p:
this Una m udi a. iiplled la thii npon. Tha dnt*. anlM to IB wi
n(Vli<d -1th th. ondaratandinij that th*Y Hold b* naad only within tha ft
TMpa^tad by th* F*d*ral Beau [dan Bank 1W6 and tha rtdaral f>
1 Analrti* at th* County-arlda Laral
th* initJji iagrk plan for tin a atBty, d*ud aevaabu la, irn,* callal
Digitzed by GOOgle
■t*»rf ■ son ixtutlv* validation, analya lj ,
gaga landing pattaru. lacood.
2 JaaalTala of tha Ifclor QnmtT li
K>£tgcg«» Involving
a collection and analyaia to only U
3i,iii«db» Google
□ of ■pacific typaii C!
dapaaltory Jjiititucl«u. Conraraaly, I
■ dltfaraHlatloa of tha iol.lo.inq,
!. Typa of *wlUs« or prop.rty U.9., naidantlal •laala family.
Digitzed by GOOgk
.cut portion of th* option*! c
calf mllabl* for Bab Uago Cwty.
IMWdltm (UlasB loan and proi
Ban Dlaoo couoty bat aot tfi» othor tfe
* pin fM tl
* prlavy aourcu of &
Wrist til* HUTU at tl
* F«1W ts JM li
:-l nvti tranaplrad, m*Jc±iiy it rt«ct«t:
ithar than four of the ftvt originally
ecapllao by nha phaa* 1 contractor
3i,iii«db» Google
Mtwati
™ tha 111 in o
a Dapanaant
of financial Inat
itutlcaa
■uebangad
whan th. Igpw Court uf
-h. Stat, ol
ninoi. dacland
llinol.
public act
J9-S32. Ti
nancUl In.tlc
itlona Dlaclo
ura Act- unconatl
ut Ion. 1
Thla
ruling r«u
ted Is • eaaaa
ion of dlaol
aur* raportlng b]
™. of
th* organiMtiona
undar eh. jurladlctlon of
ha atata of
Ulnola suing th
* ..™<i
half of 1»T7.
Thia alUlnttad eh. tllino
a Dapartaant
of Financial Inat
tut Ion a
aa an available
■ourea of co
mplatanaaa taf
mat loo. «.
■U1.I.H. tha da pa E-tm.il t
did envid*
o-i.clo.ur.
tatwnta for
ad dapo.ltory inat
itutlon.
(or uaa In
«™1-
h. atudy.
.nth
aarly atagaa
* th. .tody.
th. Chicago Titl.
■MTn.
tConpany
(Chicago Tl
!•( raplacad ft
aal Batata Data. Inc. (redd aa
tha aourca of data
for Cook county. Xlllnola.
Prior to He
tobar 1977, MSI i
Mains'
t, data
fro. chic*.
Titl. . Bag inning in Octata
ar 1977, ksi baga
n obtain
ng lea data
from an alt*
mativ. •ourea
which did n
* provlda conn let
tofaaw
tion on all
■nrtgag. loa
HI. conaaqoan
ly, NCM-i data for tha laat t
hi., ton
ha of 1977
vara unaulta
bl. for uaa in
tha atudy.
inc. REDI could a
ipply th.
required
data for Cook County only
or tha flr.t
Ulna aontha of oa
l«>dar y
ar 1977,
an luv.atlg
Honor .cure.
Of •upplama
tary data MM undartakan.
Pol low In 5 a
lattice. .
rlaa ol fll.cn.
lona and negotiation.. Chicago
Tltl. agra*d to
proWd. j»»
with tha data
or Cook Coun
ty. Illinsia. Lap
Chicago
TLtU anna
to provlda only ccnput.r .
.porta or llatlagi
and not
lnfooaatlon
In Mchlna
-aadUla (oca.
On juna 10.
197B, Chicago Tit
0 dallva
ad a
COBputU 11
ting of ealand
>r yaar 1977
loana (or propart
a* In Co.
ik county.
Tha Hating
diaplaylng th
* owMr of 1
oana and eh* amoun
t of loana itad. in
calendar y.
I 1977 by aach
lansar mm t
a aaj or aourca o
data (si
th.
™Pl"™"
analyaia In Cook County.
Sumya. t»
« .n of d.
. (or aria C
ounty. na. york d
ring tha
■atly
•tagaa of tl
■ atudy. THH
chanua w B
acaaaar, bacauaa Taala Mar
tat Survey' a
3i,iii«db» Google
raj— tj nl« wa iccapmin! by acirtijagH and IdaMLf ring Ow 1*
•p an ■4eti Hn^l lout ud> in tin Cltr at *v
HunsdJuisuy . 1»T7 HMHiy IS, NN. '
IMKUl «™ «!■« jowl* *n U» ■»]■»: -™»
•inu (ik bis mif.
1. ". lilt—. Lsa ugalH, CillCon
Digitzed by GOOgk
• Up* of
tb.li trannactiona. «outh»ant Buair
»> Kaport. *u all-lnat
IWUH U
ir data au* only aratlabla In nict
Mi for. and not In u
shin*
■MHO*) J
nm. H. ■ syat.s. .^.nl ■ potnn
U aourca Of data, but
th*y
WT. ■low
In raapondlng Co our r«)uut> mtl>
mid* ***! Batata facia
l*l*Ct*d b
sc«i» tluiia- oat. hI all of th* **a<mtl*l critarl*. M *any
of tb.
lillHill
Optional Mltatla, «* Of hlon Duality, -•. raaaonably pile!
a. and
■ularil
Italy HlMMl in -acHin* luUbK
on., a tan* containing
th* 1977
«tW t
ranxactlona £or Ml) Di**a County, th
m, *u obtalnad Iran Hat
loo-ld*
in March i
19. and thna data -u* tb* aajar a
<u aean* tar th* eoapl
t*n*aa
analyaia in au Dl*oo county.
Hatienal Datai Til* financial EauulltcMry
,777;" "7-
IIOU-JlLJ -
i urban DawLofnant. -and gate* oroan
pmiUih n
port, tiHliaUicj . a national baa in
aatluta* of the total 1
■ount of
■«w« 1
ndlng by nation* typ*. of Wndan.
Mta on national landing
pattern.
«• obtalnad and uaad Hi thl. study aa • Mil
fro* -Won to Intatprat
th*
landing pa
tama d.riu*d fro* analyaLa of tba
he** countla* la till, at
u3y.*
nrUUoH
Klmrr th* landing pattocn. In th*
the*. .. l.et ad count!.*
and
tho.* M[l
ct.d In th* national .verges aa v*
1 a* th* eaua.a for th.
•
1.3.5 MU
validation. *roc**.liw, and Analiral
Th.
Id. variation In th. tor. and oonUi
t of th. data obtain*!
0.
ton th»*
omtlaa naeaaaltatad rfavolcpnant of
the** aapacata Brocadinr*
a (or
datamtry
validation, erocualna. and *n*lya
. , Date antry and data
coding
pnosdaTH
aan naadM fa th* cook and En* c
mnty data, and tap. con.
•talon
3i,iii«db» Google
'fLcult b*c«M of tha dif f*r*nc« in ttmlnoloqy u»*d by "J.
utlyala of th* por^-gtat t*nr3inq LnfoEHtlori por»r*y«.l en IhtIji'ii* itat*-
■•rmptit-i vlth »ortj*j» data nflK
pr*p*r».l Fry th* Itat* of California for tbaaa 1.
prorlM laalohta into to* utgn •
aanU. It iln arovMad
Digitzed by GOOgk
3i,iii«db» Google
nportla? ftgaliwt that of othu t-tf>*< 0:
j prvMBttd 1a tiki" raport c>
I, aortfaf* lAPdlnf lcti»lty. T1t*H
■ stviaga nd Loan M
Ji c»t»,ocv. craatcl by d«f iult fra» ill lourcti of fundi** n
3i,iii«db» Google
274
■st rapritlnglr. In light c
■iBcUtlou ltad CM raalta
originated ind tb> n
3i,iii«db» Google
•
*
■
!
3
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^
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£
3
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=
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1
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,db» Google
2.3.) maaaX Mttrlaam Haki
■HU.UT BiDhi ii,riiiri-3'j«l ■
3i,iii«db» Google
Ill Hnt*wh> nm.f.1*.
■e-rtgag* nvuln H
- u tmueial lntan*
Uarlaa bat-aan
asd laadan. Of th. 1,000 m
artgag. mfula. in *h
n.s. tha tut
aa jorltj art
louataa Is tha aouth and "•■
. nortgaga coapanla.
Morally do not
bold
althor dlnctly or through t
•■"^'-W'0
■autgaga coarulaa ori
H.H » hUU«. «
tbott 11.5 pare.
ot, of
.11
naldantlal aortgaga. H<»C
activity la In no.- VA
oana. ohara aor
**■••
cocp.ru.. —to 75 intent of
all auch loan.. Ml
• of th.lr unif
kb
guallty, ntt/Vk loam rapraa
nt a m™ gjoantlty u
muton aad ar
HiiraHii — »n tn uiou
■ Into packet • and aall
to looa-tara Is
through tha aaandary aaikat
1.1. S Hl.call.jKm. Undar.
MR H ad of lif,
. ,,
lb. Ital group of Ian
govarnaant HWBlM< panaion
and nclcaH.it fund.,
ndlt union., t
tat.
UnaMht truata. prt™w i»-.Tld-l» aod fir-.
Man togathai, than
tandar. origin.**. a hi
110-, or i.y. p.
ro-t
Of
■11 naioutial acmgagn in
1977. Tha group, hold.
2H billion, or
31 oa
rent.
of all »Utattal •*..
Host of tba gdglnatloi
a Id tha group art by prlvaCa partiea
an...
l«a
facilitating i.la. By aaking
into mi. labia for a
•here t.m <Jw
[hill
tha
dabt la hald by govatrawnt 1
ncl ralatad ag.nola. auch aa -ovsrnnant
MUuj
al
■ortgaga MaoclatioB Tuwt
Urn jtoniniauatlsn,
r.o.r.1 none loan wet
ag.
corporation, ud tha r.d>rai
National Hortgega u.ocl.tlon 1h...
inanci
■a and
-rpo-tlon. prortd. fund. (
tt aorta.,, lading by buying Urg. 0.=
lOKa-
■oatly nU/VK. but .ooa conventions-- from orlgin.ton and lnvaaton. tha
•nabllng thaaa lender, to contlnua to originate mortgagee. Thai, aqancla
.by
angaga ooly In tha eacondary
aa.*. t and do not fall
tha r. for., dlractly
ttlilc
3i,iii«db» Google
• aevilnd thnoati L
n f*l#MtioM .
ooiBtlm — Hn Di«oo CD-joCy. GtUfotnlai Cook County, aiagoi and III.
oa «mm lauding at • apKltla legation ud elM. im» eoapantlva u
Digitzed by GOOgk
— .,
Thl* chaptnr pmBti tha mult, of tha ^uapli
tan™ -nly^n for
Inn Dingo County, auromi. Th. prnmutla 11 In
fouf .nctlon.. Th.
flrat
naotlon dliraim tha djcj utlllind for th. ccnpl*-en
... analy
. in tan Dltne
Coanty. I" «*otlon 1.3 jjor. proc.dui-.i for int. u
lldatlon
.re pniuud. for t*» Ian M*so dntn. u in--inBth =
sap.li.an
"■"*
of tha nortqao. data darlvad from tha county tacocdai
. of f lc
atalnat tha
•ort-
onoa data d.rlvad fton disclosure tnt—nta. Tha purpola of
hi. analy.1
■ <auj t.
ptorlda tntlahta into tn. diffaraoca. bt— tha tw
iOild
f dun. Th
nnnly.U uu nnacihl. b.cnu*. tha smu Diana data includnd dam
lad in t mm
ties
on landar. borrow, proparty. uc loan ohuncHrlnCi
H Mat
nn.. Man
[Jin aac
lts> r«CJi
ta. f™. th. Stat, of California. tMMOi 3. or...
■*■"*•»
-nltn of th
— ~— *— * "" «- —~ ■
3.1 IK im anon o»Tn
npondat.
.p«««.
J" BT Mtionaln. Ml ElUt. H^Utat, Chul. Vlltt,
Calif oral* . Provld*
In tha font of n naon.tic tap*, th. data conpTla* 94
4i* near
It— en* fa
•acq rmnl attar* tranaactian recorded in th* I4B Dlw
0 County
ffleaa In
1*TT. although validation and taltction erltarln H
a npcllad
totha ant
In nn ittnvt to ldnntlry and nlKt nortqaca loans .
1th la Ida
, borrow
proparty ud loan cn.nct.il.tlci conparnbla to the*.
tpacif lad in ftnoulat
Ion
C, an auct emrtlatlon hi not poaalhla. Th. Mtlo»lna dtti
da not. fen
aanpln, contain Information on haw inprcvnntnt loar
.. rib.
cad lonna.
or otnan- loan ttnn.netion. not «ooMtd at th. county
of flea..
hi toman
■lament..
tnana «»
not
tofflclanr. to prorlda nn (met natch with th. norto«j
3i,iii«db» Google
»i|nlitlgn C- ueodlsgly. tl» crlcrl* oHd to tseluil* and axcloda brmi
bm baaa oarafully dafload In thla OufUi. ai«»n IhM ctLUrli. Cha IKa
provida a auitabla baala foe aatiaatlng tha »l*t]v* rolimt and p*xc*ntaq*
i* comtr rliBBlaa Bftfnt ar» csUicud n
. (st tha t.cotH fl.11. •;
Digitzed by GOOgk
3i,iii«db» Google
3i,iii«db» Google
» pvilof. *** Tjbi* t-
>1W uai o_ii tollo'lM «*
3i,iii«db» Google
mdU tlUi liability to
nd br ^iml Ml pn**tty ihooU b. Includsd In
■ ante i« U»t(lU tat Identifying
3i,iii«db» Google
to Identify «™ naMur at iihi)i tilth *p*slfl«d erltatla o
HlKtad (or tha Eiilyili <
Digitzed by GOOgk
3i,iii«db» Google
3i,iii«db» Google
Initially, tha- annroncn of aitafcllBhlng an arbitrary UH*r Halt
t dMdi imui than tht iqpar limit mild ba njcctad. It ma conclud.
Tar, that thla law anaatialactory baeiua It raaultad Is tha rajactlcn o
a. In addltloi, Ian Mage county clalam ■ Uanjlf leant nanu at hop—
3i,iii«db» Google
■ total aoabar of rajactad n
•an Dlaas Comtr, and u adaitional 9, Ml aaaoaDtloaa t.
3i,iii«db» Google
e»q«) | although icu
y cc-p«rlior. ma iJtluul,
only. Tool* of loans found en only o>
3i,iii«db» Google
ft SSL ntt4» only
ggj U 1mm =1
■J?! l* inn a
Digitzed by GOOgk
Tlv principal bilanew nhOkiLii In
,t H>U—tl— Ot Chl» t*M.
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aUaiaa by MtlsmUa of algtit Ualtlmt* t
i UlaHna For cha U
3i,iii«db» Google
■ appMrlflf oil th* h
■EBhlp of th* aufcjact pcopart;. ni*M
■ only. Thim pc—q—Jjly
Hullr. Eb* foUoninf
Digitzed by GOOgle
I analyala of tha thraa ac
aqoali 0.11 pueant of tha !« amctli n
■ validation aaalyala InUcatta tJi.t. tha « of all ai
f they ara raportad a
rf our analyala, a coaputaE
ta Data fBecond Ic^al i In tba aaccakd ■'
3i,iii«db» Google
t Uueltntlon* U only J
jnm.ua ro» iw tiro
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following findlnoa and
in Dl*go County, in C'
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alee of tns flaUig ■ for fat Dlvgo county «na *
hi* Google
4 OtlllMd fOC th. COBplat
dallnaatefl. sactlon 4_] pmtnti th" cuulti of tha cq|klit«HU analyala
Tha analyala cotitalnad In this ehnptar la buwl open data pre
™ bf tha publiahat of the Butf.lo pally m Joiurnl. Tha punlidi
Buffalo Dally un Journal, Inc. provide! JDS -.1th «i. dally Innp
Sundaya tad bolldayu) laauan of tha Journal covurlno tha pax-tod Jan
of ehraa daya to oaa waalr fro* tha data a tranaaction la racordi
of lta publication In tha Journal can occur. A aanpla Journal a
3i,iii«db» Google
it lad accoraing to tl
canfaUr M1m4. claw, ti-.aae criteria, en. da'
■»• Um of tb* Journal ntmtloo laodJ-na activity la tha nuisi f>
■our •. ltTl, to Jaaaaur >, llTi. mum aalactad to aapraaut calanaal yi
1 BOCtoaaa Isaaa la tit* antf. lacauaa of tha tlna lac In raportlno
in IlUHnlou M ail-day ad^iucsanc oar led uai aaployad. Thta adjuata.
ibLad tha aaduaioo a( 1.™S that w» oclalnatad aulaa tha laat ma Oi
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3i,iii«db» Google
JIB amlayta OKa «*jtj •nd nlMsclce Breoduu r.
4 MATY <** p*TfCHBAd UfllBf Tt
* wtxy wa «dart*luo. ending u
A mnMljtiM. Tb* follavlaq
•i* coax «• a^iHdi
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„„„■
Landar-Typa
A ona-dlglt ccda ldant Hying th. lasuJar u
raqulxad to raport undar tha act -
t«d.r-ID
irsersTirs rss;..Ti.«s-
S^KaS5£«sr"
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3i,iii«db» Google
cantaoa of aortoaga landing by tight
lad into en typaa of landarai HNOA (thoa> aubjact Eg dl.o:
at tM «i«ht Cfpaa of lanrtata. wctgaaa loana totaling 179,011,000 w
origlnatad tar preputial within tha city of Buffalo, and aortgaga lo
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lifting gmllH a
a J.ialtatisu pncludad thai HlactlB of BRmi loan, ii
Ac-c^ir-}!-.', -
■piUUg f« ••eh lmdai pracludad auccai.
linflir ipaUUf. tba miilUM Hieing HBUImJ apprcadMtaly l.iftG
InUTldal Undtr ipalllnga .Ion, .lUi tha) BBtal aM caul. dollar mldn
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• CAqjlattfxa* mziMly*lM f.
itwn lypaa of Lmfen. rt» final
ujt Cnpuy Hiatalm a cnelata at
i identify EbaicrjA.]** wh*n thay m I
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iMjuUidiuii (palling for «ch lander. Tha •«■»!« lilting
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ft Dapusy. TO M^U* t
itTiH SB Hi. ll*tl»1 (:
dictionary of oti
fac tha Cook county At
Tba "nrtaB?*"
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««_
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1 iMigl* dlqjt idwAlfyljif th* typ*
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bhAmh
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• Hit J tig fra Chicago iitl« ud ■
■dabia fo™t hy ch, j(* .t.tf hk
Ttiaaa •noiii and thalr *{g»roprl*t« ct
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aortoaa* loan. «™« by llmi co
pt«utl« within th. City of Buffalo
and 13,0'J6 ■ortg*j« loans aacurad
>y liana on propartial In th. rut of Kri.
"-""•
Th... data cm pattarnb of" 1*
idlng air .urprl.lng whan *i*wad along with
t]» homing data provided by eh* i
>w 1 Contractor. IT., houting data anew
Chit IM.JSa 11.*., ».] paruant)
f th. ]3*,E!39 1-4 fully homing unit, in
Eri. County —i. locata, within th
city lladta of Buffalo.1 Band on th...
diu and th. data in nbl* 4.1, 2.
loan. war. orlgln*t*d par .aoh on. hundnd
1-4 fully hoiming unit* within th.
city limit, and 9.6 loan* wan orlaimatad
par aaoh on hmlnd 1-4 fully homing nit. In tn. nit of Eri* couhty. That,
th. rat. of landing 1. 3.. ti_. V
-«t« for nit, outalda th. city limit,.
i™™-^^^,^
art— «d p.rc.nf,., of Undln, by th.
v.rlou. typa* of luHn ara inclw
lad in bppandlm B. Thaaa datallad raporta
(box th. iDUm activity by ucl.
bum, and ..Tin. ml loan ubcU
Ion within th* City of Buffalo and th.
r..t Of El. COBBty. Tb*** »pOB
• l.o ,be> th. numbar and wount, of th*
■srtgas* leu* arlginaead by Men
f th. .1*1* typai of land*!, lb th. 41
-— "-— ""
• county.
^^U^f^ta,.^.
~r~tl«. ar. drawn frc. th- -tb,
. * totu =f M.Mi «n
loa» with a total *.lna of
JUS.Jli.OOO -t. origin.
*d within aria Conty In l*TT.
. anprallHt«Ly 2a parent
f th. Origination. «d IB prant
1 nortgng* loan* in Brl* County vara
3i,iii«db» Google
I UmUttj. In una M ambit ■
■ D»*ldad t2.3 pare*
4 for approalMtaly JO parcant of th* to-
togathac originated ■ppta
orlvlnatad .llolil-ly -
■ sciglnttad (BbacaiiUallr li
3i,iii«db» Google
rzi.
fkl
a d-ptax pnaaaf th
r.ault. ol th.
o-Ut— « analyai. f«
CM* cour
ty. jTlliwl.. Thla p
aaantatlon 1* In
tour .actlcna Tha flrat
mil hi i
on tain. 1 annua. Ion
rf th. data utui
ud for <M co.plat.naa a
an.lyala
In .action M JB
a proc.dur*a for
data .ntty, validation.
andptsc.
Hlqm diacuaaad.
SKtiao 5.3 nm
•nta th. raaulta ef th.
ceaipl-.t«n.aa analyala for Cook
COBBty in taw
de tha volum. nd p.r=.nUo.
of ™>rtg.
o* IfMaM hy ***■ tVP«" •* laatera .
Th. final Motion prsYltea
'— "»
of th. t-muaa
terl»d fro. th.
*"**"*
S.l TO
a^oc-wa*.
Th.
Wl^WUMll
thla chapt« la
baMd gpoo data pRpvlted to
™ W Ol
< CMcaae NO) t TTu,
It CO., Chlcaao,
lllnol. frovld.d In tha
Inifi
i ti llatlnoj, toa data di.play th
■ortgaq.a origlnatad by .ach
l«du in
Coo* Coanty (at 1»"
JIU dmlopad
lata .ntry prooadu™ ud
coaputv
prog™ .nablln; th.
teta to M anur
»1 Into ■ autgutad data
baaa. vn
ldatad. aidfixnwl
TH. ... : :
gunt, and ptrcant*,. of sort-
.aoa i«™ ™isiMt.a V ". v
irioua typaa of 1
andar. w,r. *.t.™in.a and
"•»*"*
tn aaaaaa th. landing
***—•»■ "-*
county.
Th.
CWte^. tltl. a»d fc,
MCWMM
ina a ooaplata .utcaaatwl
da ta aw
Of th. ra.l .lUU t
tl. tranaactlona
In cook county. Th. tltl.
tranuoti
in» In thla data h...
idantlfy auto.g
. when th*y ar. ariqlnatad aa
part of t
H changa In firo,*rty
tltla Bae*u»
h* data :«d for thla study ->
tetlvad f
ro. InfCMtioO On • itlo Chug*, sol.
thoaa nortgaga loan, that
accompany
Chang., in propart,
ltlaa aca included. con»™.ntl, hw
at lean* « Kf lian
lemuirtkleb an
raporUd In dlaoloaura
tharam, tba Chicago Tltl.
3i,iii«db» Google
listing proirld*! only tJ
I ocoivplad by th* a
it uIf tntii for titivating tl
m «j«lmiua try *ul« la*
3i,iii«db» Google
3i,iii«db» Google
Deluding enly ■ortgkg* loui lu* th«n IMi valtM Is th* flul llatlng.
■ !U« t« UK CHt Cenraty fli
3i,iii«db» Google
»».
•an.
Landar-typ* Coda
A tlAgl* digit identifying ch. typa
1. jv>rtj»q. Ccvpuiiu
■..nil.i-iilrr.cif ic.t Un CSO*
^ t^B*n1^rd!LtbLi'^rtr''
■— «
£s^!r2U Su™
"•*" ■■'
:™.i'"fi1s;n.;s***""'
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is [xnuleaad In Eh* Lilting trim Oilcaao Tlttt and Rut
r ail batchflB van «ntarad, tha> batch total* hsti analyaad
«mti »11 tin tetili (gEMd. th«y "«• w^d to emu th»
3i,iii«db» Google
3i,iii«db» Google
■f Clu lew ultluttd by Eta *
■ is npiEti Bhowlnf tha toIh wd ptrcvntag* «f landing b
• follo.i«j finding! u
■ orlginat*! Hlthln cooi Co-inty li
3i,iii«db» Google
hi* Google
aclaJnWlMM Is 1*77 «d pzortMl 1
oxlyluaua hy dapalto
> ptrotr.t of th* — tf*f funfling.
( tfca finding! for CM* County u
3i,iii«db» Google
i la jathari™ , filiating, ad uiD| data to aaaaaa n
19-", 111) bin™ In n.loVitUl fcortg*,. loan. IMi orl^lnatad ii
b up tba feaainlng U parcmt of the total volwa at landing. Alao
wn la 6.1 la the dollar volume of ■ort^aaa loana srlglnatad. by tha var:
flat! In each of tha tticee counties. Tneae Manna claazlv liaiaTiala
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■ flBdljigft of tiia ecaplat
■ study nnlt* ihow tlM wtut to which u ■y^r^atlaa of th.
X* ■ tatuwttl of a*pOiltoty Institutions BuhJBCE to Fvdanl D>
3i,iii«db» Google
325
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H pattam occur at tin comer 1ml-
mlt. Tha Eiuuraa ara in taraa of t
■Drtg*7i Labia orlflinitad by dapoaj
m Brorldnd by lain othar
dqnaitoiy lnatltutlcn* ara mil] act
4 daelcta 1*H than two -third* I!
i for Cock and III* County daeleta naarly Bl
it dapealtoy tutltotlsna. but ravaal notfilni) •bouc tha iuuu ten tlu
on ha knew bafsra tto ration banlnd tha pattama can ba fully undarab
Digitzed by GOOgk
3i,iii«db» Google
• .1.3 variation In Hitaw Lending bv Daaoaltorv imtltutlon.
Mtt f™ tha MA
taoaaa aaalyala aboa that tba landing pattern* of
d.l>o.ltory iMtltOtlcn Wild
■Ignlflcantly eaong th. thr.e oountle. Th.
P«n"iK o* landing la ueB
eoaaty by ooaaarcial harm autual .aving.
banks and raving* and loan u
■oclatlon* aabjaot to diacLo.ur. reporting along
14 <l«n ID figure t . Th. national p«rc.nUg.e
ntwBtad can be aial.adj.ng 1
IT .tit... -m. percentage of
th.lt acrcgag. lading In tha*. .t.t.i
thai, tor., 1. auch high*r tha
n thair national aaapaaa of 5.* parent. Mutual
aaving. MM., for ..aapl*. h
old nearly 12 billion of aortgaga dabt in than*
1 llnM, c«p.rri to 5B5 bl
11 Ion hald by laving, and loan ai.ooUtlona.
Thiu, th. praiand*. of autual
•avlng. sank* In Ell* county but not San Diego
or cook M«H ■■ eh. Bit
ilgnKloint eitd* o( variation* in th. percentage
Of landing by dapoaitoty ;n»t
Itutione. Ii Ull -.-aur.-,, nutual aavlnga berth*
originated 41. s parent "t tr
, aoregag* *»1« in l»77--nore than »lca tha
""" °' •lth" "*"*»• "*
ou wocUtlon. or <w»ial bank..
ClwlMM^yl.
ag* bank* In (rle county originated aortgaga*
that aavlnga ml loan aaaocl*
t ion* plight otharwiae hava aada. Th.** aavlnga and
loan a**gci*ti«* originated
only 20. percent of tha aoregag* aonla. in Erie
County, a [Igur. BfjajM anting
la** thaa one-half of either th* national average
or that t> tha oth« two ooun
tl...
Tba conbinad vol!-, ot
aorta*,, landing by autual -vlng. bank. *nd
aarlnga and loan uncliUoi
provide, a aaanlngtul atatlatle froa -hich to
tutlon* caablaad to originate
SlOi billion or S9.7 percent of th. 1171 billion in
" — ■* aortgeg.a riMi
ga and loan **aoci*tion* wr. th* only thrift Inatl-
tutlon* priaant In Ban Dieoo
end Cook count i... The*. iiencLatloni orlginatad
54.7 parent of tha dollar ro
lua. in San Diego ma M 7 parent of th* dollar
valine In cook county. Hutu.
1 a.vlng. hank, and aavlng* *nd loan a**ocl*tlon*
3i,iii«db» Google
3i,iii«db» Google
J buki alio niki iLgnid-
w housing Id 3»n cL«9° County3 and Cha raaultlog
it»d Co San Dlaqo Goaty in 1977, ud 21 tha lar?*
I nanny fran ^aograph.
3i,iii«db» Google
U.«., IS. J pmtl ttau tht ulienil 4nrqi II.*., U.SpHCntl. Cn
Hull pamtaoH of India, In Erla county ud Cook county -.r. snlstu
angulation c apaclflafl that dapoaltDry laatil
* *ppai]i!ice» . the d-poiltory ina tltatiana J
q to the total dollar VOlUaat of mortgaq* li
3i,iii«db» Google
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■ffactad ai« Wchuii by On lending lutltBtlau. Erie ftrunty. for
initanc* hum 43 depository lnitltutlawj HhmUi Coc* Cowtty hu n*trly 61
n.hip btCHHB WpliClt le
■ Tin utun tnt UrlinUoa of labl^altlt* Id a
Digitzed by GOOgk
i an not aapllcltly daflnad. Dm Ilia crltarla ih] to
ma Uelndtd In a onapllntion an sac .illicitly aallaad,
wittingly aUlad by (M HUlU. H>a i rir t — an aultlfiliad
la tad with Bagnlatli
c or atata nguUUana 1* eenfnr
a by dasealtoay inatitutlon panonnal in applying o
3i,iii«db» Google
M«Blatl« c tai m ■pacify cxittrla fee u
•flCF<l*lB9lT' 1«d|°ltf 1]
« apevuCly * vloUtiu or thm infant of tabulation c
3i,iii«db» Google
■ handling of thaaa loans.
tfca Intajnt of toruLfltlan
dafinitioo of a>n«urui:tion J
gipj paying prlnl&pal
anta piapavad by tha :
laplloatlanai Ita dual p
Mm of axpildc ■
d by eboaa prapariAa d.
3i,iii«db» Google
i military iwan: Ibau aaancUt
In •xiitiivj oafinltloni . fsnuliu ■
oapoaltory in.tltutlan , Bl «faxoi
. Dapoaltory uitUiltlaii Ol*M inltltutlc
•hould conform to mjulaticm
3 Hatching Pat* from Coqnty Qfflcaa and Tltla coananlaa to Haanlatloti C
In aUitian to problem iMuXtlni from jmfeiquitiu In Manlatlon C
» or conmarelaU propartioa .
t Impnamjbll to obtain a prvc.
3i,iii«db» Google
*aly atatpl* atapa could ba l^ilana imfl to provlda an luprvrad b
ingly. no nognoot tba cogaLntary nnonniaa ecnaldac tlH tallotiny two ntapar
i.-ttmtry. Thia oauld ba Ion* through Croatian of * daaerlptlva
* itufly pnHk • vncd naalsnlaa ti
-Tina typas ci flndlnga van oarlnd fron Ua atudy. rlj
hui «r tha voluna and paccintag* of Landing by mian tyjm of London
i obulnad fol tha nation, and onrlwd'for tha thraa coiatlai In tha atudy.
jod, k_ o1 tha najot «..». for tha Tarlatloaa Is tha landing paturna
Digitzed by GOOgk
J IBBim ortglmtluu
reporting, ociqibi.t«d Bl.Q parcBT
For pvrpoM* of «alyil*f .
a utionl p*tc«r
umim
K«IC«AL
S*^J^0
c^t
<££,
CO-«=Ll»™]c.
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tutu.1 S..W unk.
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S4V1AQI £ LOU JUKCiUiODS
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100
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3i,iii«db» Google
laUlMttont,
1 by dapculuiy ti
EXPOftXTOlCr EMtTXTU-
,— „».
M Bl«qo County
«.,
.,.,
„.=_
«..
»..
— —
•"
a LMdlM >T MWlMB UHtitlltlaUi
* dlacloiur* nportlnu. I
3i,iii«db» Google
_».... s
imx or tm DOLLAR voijim or ehidehtiu.
as loam onsnmioBi r arooBiron tarn-
■ lOBJtCT n FIDEBAL WD STATE KKITDC
IZBDD.TYK
SiS*0
IUIrom
CDOCOXnTT
ASSOCXMTOWS
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th— -utta, .„, cOUntl«, lacludl*,,
• SffiTSSJT
■---*-*■-----*«-
■ r.rs?—
d-nrt for „.rci1 and raaldantia! »«,.,..
tr nlMtitl aort,*,. i™„
' X™E""""
rtgaga capnln In San Diago to eh* tight miy
XBoact of Inactions
Tim rtault* of th* itady indicate that the eveBp--
tier,* fii. dlaelaaun rape
tiag granted to depoeitory inatitutlcna In the three
HU bmiH of th.lt til
or location do not rea-jlt In a alsnif leant alolai
in OUelocun r. porting.
■ha nortgaga loan orlqlnatkona of dapoaltory inatl-
vltUn u WU ringul frta.
0.8 to 2.2 ptrc.ru of tba total dollar voliaa of
■ortgaga loana that vara 01
lginattd by all dapoaltory InaCltotlona In each of
tha thra* ommti.t. It in
Important to not., hamr, that tn... tinllnge ara
tot thna oountlaa only, ■
d thue do not eliminate tha poaalnlllty that
•jc—ptlou. Bight han • no
3i,ii,«db» Google
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b. 0.1. pUMmt IB IX*
-» DUa* SMS*.
n» FiJuiiiroiir
*r*d d*po.itorY ,n.,lt.u»
. in th.
ChiMOO »»
raporud IB thai: 1977
ll.clo.ura atacamanca $51.'
.1111 on In purohaaaa of
•oftoaoe Htm aaourad
y alnala family and multl-
aiallr ptopatti... eurche.e
l»f™tl« MB not *M
Labla In tha dlacloaura ati
til II mi
f tha atata-
chmrtaMd in.Iitutiona.
Our analyala of tn. nm
re.poni
• indicates a
•»»t =M»" «'.l.n Of daubl. cmlln, to b. S16
.Tmilll
m. Tha total
uoluna of -ortuaoe and
« lmprov,a»nt loana that
■art Mound by .mole
family 1.1 tnlu -family
propartl.. In tha chleajo
HK and
hat -air. origin. t*d
by dapoaltory inatltutl
M In tiacal yaax 1917 M>
JS.« bll
job. On thie baala.
CM -norat caa." pscc.o
aqa of doubla conitlno "a
aatlmat.
tab. 1.0 percent
th. doubl. counting InHatlMtlon,
nf™,!.n ...
B -hid. loam that —I. BUI
chMad 0
orialn.t.4 aBd
year MM Ulna properly t
portad on dlacloauxa atata-
cant avldanc. of improper
.portlno
of tha.. Irani-
ty lnatltutlona -.1 in tha
Chlcmoo
nau. improper
IctlOB* M not a major aoui
■o. of ar
■or In noma noti-
ma dollar amount of Improper report.
ng -a. 1J5.5 million.
and thia amount La ntollgtblc compared to the S3. 4
tuiut
f mortgag. lander.
H»avai. tha IIS. 5 million
that oaa
not propmrly
of th. dollar volume of al_
audi a
injection!. Upropat
r.portln, of purchaa..
f inter.. ta In parti cipetl
a ~;or louroa of
wb Room <k tot.
yp. could baoo-a eignifloa,
t. If depoaltory inatltutloni
purohmaad and failad th
report properly a large v.
lum. Of
nt.ra.ta In p»rU-
other than dapoaltory Inat
lUUOBB.
M> lhv.atlo.tlon
.
3i,iii«db» Google
utaot tfl Khlfih mztfjmq* Loui iKiutd by r»io*nt
thr.. Sludul Mtnpsllun St»ti«ic»l Ai*.. (SMS
Chieaea, aiffile, and Ma Dingo). DeobU muting
* part of tft* iiudj, i
A u (Btfiai tfat* IWM ■ MICA 1, 1977 mad rtbrumi
* dapoaltory institution* *«Ta not pEop*rly
■ coopL*!:* ualyali at Lnpropu rtpottlnq *mn
3i,iii«db» Google
* WR«At or doufcU counting li
■ d*po*i.tojy inatintiou locat*
hMEtuad in»Ututlon» ■*(■ not »qui»d to Hptntt Qiiqina
n coaplling th* itita disclaim atif int. InRMd, thei*
3i,iii«db» Google
* Mooting taJna on addtd ai^itflcane* *t
t(> nil— It !nf-:-r=«t.LCT, i'.r:,'.:fr.:,-, th. alls ud tlH dlt* ot U.
n*tioa for mhiji Lcp*n *h*y puEchBMd And iMbvaqvancl y Included it
3i,iii«db» Google
lout* tad participate
itiitlnnj w*r* ukad to pnrloa Intonation on *»
3i,iii«db» Google
a la) wasa ajwcitiwl p,r.:.
rginatad By tba
oriiuau a Joint 6± oooparatiT* fanlcifatioa |
by naidantial raal property mi* raqulrad to rap
depository ir.aUtuti.ona chat puicSaa* an latana
clationa to pattlclcaU la eha iaa) In aach of tba tin
fucchjHd daring the pL* mnthi reporting patloA. Only ■'
f partlel ;«'.:■-:. t (but I
3i,iii«db» Google
A ; '.-.■■! .■-.■■.I only an van ::rf:f,'d c
' aaalyalf vaa parEora*Hl b— < on tha -a.
validation m aumUl.
ating origination*
3i,iii«db» Google
3i,iii«db» Google
pcaltlw itlponHi ■
aul * poaitlw napsnn. n< hlghaat parcnntaga ot poaltlv*
obtained Id Chicago -h*ce 11 gf 13m 30 raapondlae; aarlnqa And
lo,a ti.a., 46 paroant) and 39 of tho MB raipandlao. banka (1.
■ Hid porchaaa of aortgnga loana aaoncf a»pd»l tory
go SOIL la analyud In datnll In th. Hit aactlon.
paRlcleatlona Indicated by tha 19 Oiieajio banka Indicating poaltlTa
napgoaaa an ■— Wad In Teblea 3 and 4. Tabla 1 ahowa tha aaonn
catad by banka that crlglnattd and laid Individual loana, or Intarea'
Indicated by tha i.llli*, li
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feQB tJi* nunv EMpooctatfT.B, J> an analyala of Etw forray infos
9 paroant (1.*., MS/»7«) *
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cant) Udintd • poiltiw [»p.
6 naponUnq taiiki or livings i
eago dtpandlnq on tha oallu ■
ago SH5A ii analyud In oatmlj, ii
a Indicting po.ltlv.
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ht HMN la ■
nvol.in, oo
• Fwlbla tail (Pt) - Hi
nlliUL7 of ■ tn
In.titUtU
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• fimfUmi
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othsr napondlno- Institution In.
Uci-tl » .tallu
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mlidatlon of nap.
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^pondnut
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tcanaaction.
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.ithar
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llctlno- U I
xam in th. UUa
m. tadiTidmi t»w-
tic- fb. I»k. »
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licloaiu* IUU»
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t™.««i™ to b.
D*U<nM
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ad In th. aa*
diiclmur. HM
f both of
IM l«ii!M.i™
m*elm4 In th.
tranactlcn.
TM rapondant* ».
N ut.i to la
lot* >hath.r or
nt hc!i tra-if action w
zmMn
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that th. EMM
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• ommnni <
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idiot. Htl.th.1
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ctLon m. t*pott*d in its di.cLc
. ■« mc«»i on - Th.
tnntltntion indluUd that th. u
.enaction
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n ariginatlota «•!■ rtpcctad. .
■ an nqalnd to »pen erlflMtad loua in If tfcan Idui mn mala
ch* -mpald principal balangai
nporta li prasantad in Tab!* '
qagad* In t
h oth.r dayoaltory lnatltutlm
g dapoaitory iaatitutiona laeatad ia Chicago
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raportad could b. ;on1ia»r^ily tiulu than alum bn. Ttaa bgn to whlcl
orlglnatlona or purchaaa* in doc r*pott*d lami to etl-Ht tba •fttet of
tounLa counting. T)m coabliicd aortcaq* activity U.a., anlaa pi™ purchaaai
1. mlnitllid -h»n l«n> «i» not raportad, *um, tnn oonblnad aortaaga
Tt» Of nW«l<» g*jg T'"'t Of Dauttlg-COaMlHq
> ffolfo of Ifjf —J >«iiTiaaaa by BtfrlaM and Loan Ju
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aaaociatlcCB that o(-lginfct»a »j
in pirttclpitioia Th« lndi»Mn«l ti
Mb la particlpatlonar nharwaJr tbav Old properly dia.
arly an aqual Mount (i.a.r 115.6 ■LUloml . Tin 516 a.
oacad vlthin tha Oilcaoo
nt aavlnga ml Loan aaaod
lncBWd In Chicanoj nhtli only ona pair
dapoaltory iaatltutiona located In Cfaleaoo.
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Sine* th* nportad t:
13.501.TJ9 (Irwdr cimud radar paxtldpttUnl •■
anting eonia oocur lnvatKH th* tsUwiag lUd i
3i,iii«db» Google
that potentially could ty
tarmLotd £*• 1) •bora) by tin t.
■ a«r.. that It uu raponad by tM mgoidanc.
: CM •Mir. SWA by aultipllw; th. outar limit ■
by aiTiainj tba •warn
smmt ol Ism aritinatad in fiical y
rhi« 'nH sua- analyala bu hi
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u Dl*9<i In Eha unllKtly «™it tut ill
.* of Doubl* counting far th* CfalMno II
Mportn, mid or purchuad putlciBUloiu
3i,iii«db» Google
umucttjumii
v. oat this li tnlikalr ud oonelwS. nit 4**1* counting .ho.
<1 Zlaal |w l«7 Hittm activity «c th» CMeiBD uu.
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tH«*« cwld b* drtmbl. ■
■ tt» l«dlag ■oti.Tlty.
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■hab.
at aanltscr Institution.
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* —• ■« «— »*« — tf
IPU.1 lmi iirliilii.ua by liul
wmemtml br »1d,1. fully ul ■
fully prDp.nl.. that
By tfcl rttpl prwlou.lT sstlliwd.
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Calculate "
±cbm la not a significant aoucca of nnor in lumm ■otioiii diacloaura data.
In utast Co -hltfi th, tlitcaso lumy rup.ijB.ti did doc Inclunt origination*
n Tablai and •■ Only two MJMI and loan aaaoclatlona old net Inclooa
old, and aavan banka did not Include lean, imj purchaeed. It* dollar
.oan aaaoclatlona (i.e. $16.5 nllllon) la inall ccaparad to t±ia dollar vnliKa
£ 1477 ■octaeoa loan orlglnatlona In tha Chicago BHSa li.a-, JS,*O0 ■llUon).
Involving dapoaitory
3i,iii«db» Google
• ttatt turn alM innrtitatad »• po*nlhility t>
cty ■■cuilnq loaJU th*T w»E« coiuldillnq f urcfiulng
3i,iii«db» Google
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DarARTMSNT or Financial INSTITUTION*
D All. riNUKUL 1
• th.t If p«p«1, mi
r nf#wil1.ttll:y en idiom uj If |KU in Mr aaklaf 1<
-j- MTm a !•? raPFi mi-j .-■■ .. .
• »MUh*d and
HdkaiT Melon
Mklle Act 79-41! r.niBlT .tit,, that j.~ -j.
"«' Uftt>?
iHlnll iti.tci
«UH
3i,iii«db» Google
A 71-631 r«|ul»> ■ ..port on jkmc •ur.|>c. cwt.ttidini portfolio. TM. x>n> 0.. »i.;
of liui on your l™k. «d th. iotut awinc I«r Hch tip ud* ml «wu eihi. II '
out — 4— t fat hihiibi fluaclaa h 1
«1T 1 to * folly <■>
M,rlNUMM«i
niaa, Aru Cod. Ml-m-KKM
*i« mi (He
t FIN* KIM. IWTITVTTOm.
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REPORT TO THE DEPARTMENT OF FIXANCIA L INSTITUTIONS, STATE OF
FOR THE PERIOD EMDING.
-.f in.iitntion. Undar tha "Financial lutettutloui Dl.clo.uri Act" (PA 79-612)
Ts bt Ulad -Ithln iO d«y> of lb* in. motion' ■ Fiial Y»i ud Eviy 6 Moot),. .
NAME OF COMPANY
A D DRESS P HONE
LICENSED BY (II ApplicibUt
LICENSE NO. (II Appllca
i Thla A Conaolldatad Raport
"I Bw i*a»r (or ■JKira) that B tin b<
sot Vnowladaa «»d ballaf to* itatamanta eontalnad la thli raport.
I) Including tha accompanying achadulaa ud itatamanti (11 any) tra trua, ud tha
ictloni ondtr Sacttss X Financial In.tllutloni
RY PUBLIC
,d by Google
Bgnamai tt m anam a m m ™ bhim ""
aatiaata r-t>« tikjabtc and volwa o{ laann -hac vara bath arlfinatad
and teld during ;h* Fined yur* «o4inf Daeaabar 31, L : " Tbla
lnfor«atlan la *n laportau lAput ta a acud? Jointly iponjorfcd
Act 'HMDA1 raporti ar* balnf comptlad and ttportlni nachcdi and
tun atud?, and -ILL oat ba iiaad In cDnnaction wlch eo^iLlanca
actlrttlaa of tht FKLsk or FDIC. lafanKLlon ausnUad bj
Individual laaclcatlsaa In -hn urvar «lll oat ba ralanand sat aid
tbn (tody, ant a copy of th* •uraaata manic* Mil ba * — r*-*r1
natnca ramlut KiQ » Q
• aarnr parcainn only ta Individual 1-4 (astir *~ "— "'*
an that anra oriflauad <kirin( tba "1»77- flaeal raar Bid
bar avid to, ar putchaaad iron nnothnr sarlnfi and Loan
It csaBarclal and aucual aavinja Itanka lscatad In cb*
n yonr "1»7J" fincnl 'iir at psxeaua tban fwm in-lnii and
tinoa sr cenBacclal bantu located in :h* ■offals smsa,
action o( cte tmiIjwiLh
of tba tur*ny pertalna ta aalaa ar purcbaaae of aartlelanclou
r lBTOlTlng ;-. family cealdantlal aortiaea loana <Do net
a part ideation* fot, at Involving bona immanent loan* ar
imw/iBic with
Print ar type jwr inndtutlon'a
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•**4 job parcou* toy l-i lasUy rulducUl mortal low from Iu | I
«tBm uaauclil ud mituml uvlnxa Wkx or u*la(> <nd Lou
■■■atUtlim iDuiid ta ch* mtfUs Mil Clf umt U "bo." to |~~|
T^Xmh « to wuatlan ft.) t~l
Lpnitr twa c*a ssclaa of omitting
ind laid La Cb* wi f UU
11} (V) Iraitlitlui *n
c«purtin( anetlua
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ItOttltUUtt Ttii ItM
Did too altbat eutchaaa « "ail mf latataata la participation! fat, at
lwelrlaf artwi laaa* for 1-4 f tally raaldaatlal preparer lauiad 1b
tha (offals ao» durtm jau "1977" flacal 7«r! (Do not laduoa
paRlelaatlaoa far, or Un-oltlaf, taeaa tin 11—11 lnana at aolcl-faallr
daalllnfa at participation cartlflcataa laauad by tha fadaral Bonn Loan
Hottfaaa Corporation, tha Cmaii—t latleoal Horti»t« isaxlatlsB at
tha tinan lama Malnlatmlaa.)
a. FvtcIwmi Taa Q a. Sail: Taa □
» a * □
{If ma am to 6* ami 6b la "no" ran bay. eomalataa CM auaatloaaalra)
If too *aU participation* fat. at Istaltlai aattaai* loam for 1-4 faallr
taattaatial atnpatj laeaud la tha Buffalo SHS* and oflalnatad la FT 1977,
plaaaa aopply tha follovlaf infatuation tot lad pattlclpatlon. (RRli
Tola ovation aaka pou eg apanlfp putcbaaaa try ■
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t. <ui ail of U» Ihh il»ead in opaaeloa 7 <■ onalnntnd by yon la fiscal
yaax "1»77" Indudad In Put a [Origination) of"iour *1»TT* flaeal Toar
■Oa raport. iiUt* (11*4 nith tna Scat* a( M» Tart, inn tsar
lneladad in tba atata raport? (Sh fooconta bactoa of paaa at)
acaaaiBB utt* »
It too parcbaaad « lntaraac
loaaa far l-» faaUy raaidanc: ...
plaaaa llat Hi. foLln-lnj information. (Do Dot include oartlclMtlooa I
or lmoliiaa boaa inprn-ri—nt loan*, aaltl-f
aot <irl«laac*d is FT 1»TJ.)
■ of laiclEntloB
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tmsnaaxiaii a LW fmCT*™ *>"> «""» "■ tmcbtcaco am
Tha radaral Ism Lou Ink board (TSUI) al Fadaxnl DtpoMt
Iuurinu Corporation (TDICI ara ccnducclnt a auxray at all
aarinfa Bd loan ■■aocincloua and all coasHrclal banks la
cba Calcaao Standard Kacrooolltan Scaclaclcal Araa (SMS*) CO
aadaaCa cba tuabar and lo'.ima it loan* chac vara TxJth orljclnacad
and jold ducint tba fiscal yaar" andlat Oaeaabar 31. 1177. Ihla
Information L» an LapocTanc Input -o a study Jointly sponaorad
97 cba FBUl and !3IC In aUch coa 197' "
ace iasB*; raport* act baiai conpllad
problaa ara balai loraacliac '
Tola information La balnaj col
id rapoctlnf aacaoda and
l«Iy for cba purpoMa of
actl»iciaa of cha F3L31 ar TOIC.
Individual iTiirlnrlqni la fcMl a
tha itudy, bat a copy of cba inr
co you if you aa alatc.
Do yea lrtah a copy of tha arjtr*aa.ta r
is c Ion (upclled by
till doe ba ralaaaao outs ids
caaulca will baj 5
TBfC. f of cba lurray parcaina only co Individual 1-* ( aslly
raaldanclal norti*|« laana chat vara drlfinncad during cba "1977"
flacal yaar and chat you alchar told co. oi purchaaad froa another
aavlnaa and loan association or coosar-cial banka loeacad In tbe
Chis*(o SWSA. If you did not alchar sail any aercsagaa chac you
orl|lnaced to your "1977" fiscal jiaat or purchase chax from tavinfa and
loan saaociationa or comuclU banks loeatsd la cba Chicago SKSA
plea** sub-ale a u|atlva Ctpor? Co --Ms aaetloa of tha quaaclosnalra
by cbaeklni cha "no" bona la questions 1 and t.
fart | of cha iur-7*y parcelna te aalaa or purchaaaa of Barclcloaclona
for , or Involving 1-4 i aaily raaldasclal nrtiaga loana (Do -c ;
ssilcl-faally dwellings dt participation certificate* Issuad by cba
aaaoelaclen « cba Tarnasra Boaa AnaLnlatraclon. if you did sac par-
ch*** or aall tbaaa in fiscal yur "1977 plaaaa aubalc a aa«acl*a
raporc Co this aacclon of cha quaitlonoairi
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(Od«laMlMa) of row 1»77" flaaal janr »n«a. taaort or,
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], riaaaa Um tha (ollonUj Ufm—rlif parealalaf onJ,» to p—<-f |aj
Mad Co whoa too Mid aarcamga loans chat you orlainatad la root
"1377" flacal yaart (If aora apace la naadad, plaaaa attach • aaparata
pa*a aad aaka aaproarlaca rafaranca to thla quaatlon.)
( Loana Total
ladlrtdaal fcnuii Loam Tou tUOtUi
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lecatad la tha flilnaan Bnl< (if auvar la -do." plaaaa So -|~|
to CO aanaclon ».)
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(ran ■■■ »on purchaaad loao* that
■ tba "1977" {local yanr af tha tarnation coat
•old chan co joa. (If aara apnea •-* aaadai, aetata a aapnraca pana
aad nana apprnarlata rafaranca to thla quaatlon.)
> iio( July 1, 197S, laatltutlana no loofar hava tha option of oadttinf
tint ihalr aW raaotta loana both originated and aold In tba aana flacal
raar. (taanlaclon C. Section 103.4, (a) (4} (11) (»)) Vararthaleaa an
lanertant enpeet of thla itndr la co aacertala tha reporting practical
currently folluaad by laaclcucloae ■object to am*. Info ma don (applied
oa tbla aaart liiunalu will aWT ba uaad la connactloa with coapllanca
a of ISIC or FbLM.
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parti sipattona tor, or Involving boaa la; aaaai loans ar ■lid-fmily
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a. •orchaaaj: T,« □ h. Sail! Taa PI
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frocidun. (or torn* It Inni audit and rnitt M™
ni^'^r'H'T?'"'"""" ''•*"•'
« tafia th. tail audit la Saptaaba:
ligation In tua .tujy <k
■ Tho.t lutttultuu dacltul
th* rollowlnf, Information had t<
raport datalllaj taTaW*1
Jim 8. Kanaaaaadad /
<T l*ocodla| analrali
3i,iii«db» Google
a. m*aca of
fa-lly, KiltllaallT. boaa la
varchaaadl indicator.
lack, lull tat Is- e.rtlc [patina Is
Iba atna> *aa aafcad
to pimWd. tba r. tulitorr
■pun Mth ■ copy o
tb.lt 117
dlacloaoT. ataUaa
at , CM a llatlaa. af
• tooattj addrnaaa. md
caaaa* aaaaj
I utl.cia.nti lot!
dad la that* H" dlaala-
• ut. .ui~Ui. In -
lanlaa, oat
ItlB.tin, loatltu
lou aaaaj aahad to coaplat.
■ad m.r. ts tha ecu
laa briar auaatU
main « thalt procaduraa
Id coat. ...OCt.I.d .
th diatlo.
ra .tataaaot prapat
otloo. TMl qaaattoaaalra
la lacladad aa Aaandl
C «f tola
taport Olbar data
taqultad for tba .end,
{■■•., Itaa *. •Inn)
•an cbtala
d by th. radiator,
• ualaan froa tba aartlel-
pat lni i.lll.tl.n.
nor to eon
duetlaa. «■• "■«'.
tha dladoaura atataaaat.
lo*a Uaclaaa, and coael.t.d a.aaa
lenalna nan (an
itd.d to JU by tha
..platar. aa.alc...
Dili obtain!* tha raaulrad lafonatloa, Jin
MUtai tba ..ocodir.
and iuni.tlDii.dlli
ulna proca
do rat dallHatad 1
Aaoaadlcaa A and 1.
Tka mlnli aaa banad
oa a rw-n
■!• <-pU»I ■'•'V
la tbla tvo-ataga laapllna
la cnllad a
Prt-.tr aawllM' »
alt asd tba loan, aad
canasa tract, it* call
d 9 Up] IT)
■ ubuciti. Ttia flra
at... of tba auBSllac
alas lmlw ..laetio
of aaap
a ol prlaur) aaapllBn unit, ih.tt tha
probability or HlKtl
a m P«po
tlnnal to tha alia
ol tba nail {l.a., tba
aaaaai af loan, d Uclo
id) Tb. aa
una- it.,, ltnolva
aalactlan. a conataat
aaakaT af aubunlta (1.
. , SO loan.
and 1 ••**,. tra<
t fro* aach aalactad
prl-ary i.-el lna nit
lalna r.Hfea
aaapllci. Thta .pp
oich imur.i that aach
laanvltblo i«!il..
.a«l«l a
ob.blllty of bait*
• aaplad. Tha KoaVar of
p Tlaair aaaallna aalti
•alKMit fo
r tha buffalo, tan
Dlaao and China. o SKSA.
•a* 14, U, and SO. f«
aactlTal*.
3 inc. Iba arlMrr
taaallBi aalta (l.a.,
aalacaaaot. -or. than sua BrtMty aaaalli.
Digitzed by GOOgk
tbla Hat. 15 r.ct. lor ..eh aoplloi unit M raodo.lT a.l«tad.
Th. ld.o.icy of Eta) tract, aalact.d vu toov.y.d to to. ropiluorr
Individual loan dati froo IM iMtltetlas'a (Hal. Tbh* data
vara than ptoTldtd to JU (or l||It|Uloi analyal..
3. lavlavlDi the eoaplatad quaatlonnalioa (or eoaplat.naa. and
rallactloa EM raault. o( tha laatltuctn'a t*oee4t°t- for it.. •UD|>U«
aoaly.ia ho-.«.( lOafititUaJ or tK.madlat. Moual IUh inn not coo-
.atTKtad lor tb. loan, .ooaftt. la iaoar.1, tha auoloara inntlid d.t.
f.™ th* looa (U» or jack.r. for loaoa that n.t.d en th. 1 rat Hut loo -a
Tha aralnar. fait confidant that hl|Bly t.llabla data van .It raced for
thaaa loan, and (ot purpdaaa of attntallon aeeurat-T, tlwn data v*r.
3i,iii«db» Google
daC for mbi«<|u«nl SHSA («ic3<ilil( iiul»l[l. Aa itiui 1» tk( I>|11
arK*4aroa, tba puryio"* o-I ttu taocsdiBi mtWili "«■ lsv««Ct|«t4 i
Ian Dlaaja, mmt CUcatD HAi.
ABTMattini "f|p«" Ualyilat tha accuracy at auraaicad mar
A aim loaa M a alalia
i naertlat Biilmiti alfltc I
■ Mil Cal«a timpwU hj tubas H. Oonnallj fi
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t wntM* Ihi dl"
During thla Aaalyal
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i 1
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i
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eiadloi* on §*aco4lBf Hang
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,) d«lD| 1477 tl|bl ol
■ luklui Bwinml'i Sup.c.liort
La CnfBtir 1 tai Appapdli i
■atllnt pnufcn n»ll*4 In ih. lo)tm >
3i,iii«db» Google
1 latitat (oh aalactad In tba Buffalo SHSA ranaad fro. a lw of ISO to
a hlxh of J,*57. Tba total dollar aawint of laana captuaaEia oa dlacloasra
atataaanta Taafad rroa a lo* at 11,7M,M0 ta a hl*>> of VS. '-06,000.
Tba atatltttcal aaapllni proeaduraa rami tad la ona aaapllaf ante
otbH tana mat nation. «• «,3, ■■! I. taa»actl*.ir.
Data raaalna to OHM! tba atturaca vltfa vhlek ln.tituti.on. la Eh*
units fot purposes of aa.aa.laa. tba MMMW "ltn uhlcb the alattt aalactad
Dalai tba ptocadutal dlacu.a.d la Cbaatat 1 aad appaadlcaa I and 1
of toll raaart, iu loana aara r.ndoal* t.latta* for itch of (ha It ••■allna
th. c.n.u- Tract Mdt... Codi™ Culda CM©.
r._ r srsay^L'sy j.'iria-
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41 a* amraar flattst* '« (■» *U>» <■"•"
i ls> at II ancaat te a U«k at 100 wM. tha atacoalia ■
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TUU 1.1: CSOCODIK ACCDUCT 1ZSULT3 Tot IDmLO
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robot-Ill
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of awn
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MM
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HJfe .—11 olio of tho SMB.,
•UelTalT
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t,v of tlUlUl a. null ind
tm
Mild <«=
din. tool., ad .aal
111 of I
i» goacodla. rHhrrldu.i oood
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mum '"■■<•'"••' *> •«"='■ °<
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lutl.i It
tho Buffalo s«». rix loititii-
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u» tit.rul I.CVll
hM
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<d fiimd Iron 8*
100 pore
1.1. 0OO ln.tltutl.nMOd
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■ ■mil.
•ddr... MMl
i>| proor
i. one lUi fiTfflir— Kt"*'
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tmim
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th oUch Eh. t.a aa.
lt.Il
atlooa mn«lM
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dlatl
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M
oalac
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a a Blah ol 10. OM.
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praaanEed on dl
a IUMHU r.nnd
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ah ol *»».•»,
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.alt
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tht tan MottE
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unit.
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alt aad ii c*aaua t
tor .«r.j.tlou aaalrala
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oth«
Ehraa laatlEutloaa
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ulaio
J and taa 01. jo -5.
*™
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1 aad Appaadlcae A
MM. Eh. proc.dur
a dl.tu.Hd la
■haotai
ol Eh
• raport, JO loan.
MM randoaj.? a
alactad
lat aaeh ol tha IS
■ aapUo,
unit.
Ih. loan. Mi •
lactta In. tha
1«J I
oao rootat prootdad
bjr aoeh
ol tba l.n .a^l.d <l.pt>.
ton laatitutio
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an Ditto. Ida prop
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a lor aach a.lacta
loan la tha lo
a to.
at tan raaaacodad E
It a
appropriate »■»■ tract
Hda (KOI
a.o.l.h.4 l« t
M San
01.,. MU.
Th. ACS u..d la th. ..(..cdia, at
,E..n. add™, lot.
«attoa
■• ol
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tad IE dot. nut
IbcIb.
a prop.rtj addtaaaa
Chat MM
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to. Tha l«7» •
of thoaa. 8rocn.ro
4. p.. a.
■M
o local, ibo CUM
Eract aa.Unaa
t could act ha loco
ed la
tha A
S. Honw, aoaa
f tha orooattT
«ni
oa that MM aalatE
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n«H
odla, WH not Inc
odad la althar
f ih.
0 gaocodln, toole.
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addta
aaa MM a 11.1 oat.
In contUHl
lDClm
lad la [ha ACG MM
rt|...ri!d and
could.
Ml 1° Eha calculat
oa at tha
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ol ,oo»dla, ac
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r-»K< In ttoH'l
i fMCOdli* itnrr; Clndlnn loi Ik* t.n let it
• itudi.d In 9u Ditto. Tfe* parental ill kcii
•rcint to ■ bl«h «t 100 flRW.
t |nwi Is II st tlH 11 larltBt BBita
■if*
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tablI o1 s«nl!n» Unit. IS
H.U Fttttntm ol *t=Ut*Y M.05 I
9t.od.rd P.rt.oiM. ol Error l.*M
95 F«„« CofU.oo. Iot.r.1
85.51 1 <
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tint
tucloaa aajtatatad
ha data ta tha it
dtaelaaura atataaaat. *
roa t h 1 •
■aap
., ch> data naarf.a
o aaaaaa tha a«
raej o
annaattaa hi.
collactad
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a at [fata antra
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a. 1.1.
Tha —bar at lau
a an tha dlacloau
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•at. of laatlM
laa*
Hl«C
tad IB tan Dlaaa ta
a*ad Ina ilari
U to
a hi.h at 10,0**.
Tha
dell
i aaeuat of loan. [
apraaaotad aa dla
ilaaan
•tataaaata nand
(MB
a la.
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ta <r *m*,m»,ooo.
lb. u^latlul ,-pU„ FWtfcB,
taa.lt
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baiaa
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Eiaaa.
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UBlt
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ana (or .aocodla*.
Mktn
a and aJ can.ua t
for
taraiatloa aaaljalo
Tha lister of
unit! diaan MM
tha
Mki
Etna inatltutloaa
■a* too tar 9a.
i.ao-1
and San Dla.o-1,
od
tan*
'"*""-**■
...
etKNtint tccinucy
IB THE Sad DIEGO
and appaadlc »
nait «» MMUto
.. dlacoaaad 1. Cbaot.t
i — *
li npert. JO loan*
MM randoal. •«
laatad
or aaeh at tha IS
aaaalle.
unit
. IH* loan* MM •
•lac tad ftoa tha
*7» laa
a collar pro.ldad
tn aaeh
of tha tan ■ —plan j.po.
tcort Inatltutlon
in Sa
Di.aa. Tha proaartT
addra
■a for aaeh aalact*
S loan ta tha loa
roata
vaa rafaocodad t
lea
aad Thoaaa Irothara Kaaa
Addteaa Codioi E
oabtlabad far tb
«"""«"*■
Iha ACC «.ad 1. ..
a ..(.octal., .ft
.1. addr... into
«atl«
u 0
SaiiMnbar 1. 1»7S,
aad It dot* not
mltifi
ptop.ctj addtaaaa
that vara
aaca
li.h.d .flit thai data. TSa 1978 ad
tlOOO
Thoa*. Stat ha ta
a p. ...
■Ml
to locata cha en.
tract aailinaoo
.* thai
could not ha loca
.d la
CC. Hcvaaot, aoa*
oi tha pcopactT »
MxaaM
that Mta MXaat
d lot
T..Bt
*odlna «n oat lac
ludad laalthar a
thaaa
.aocodln. tool..
Thaaa
tad
dad la tha ACC oata
r.n.ocodad .rj I
aataai
d la tha caleulat
an of tha
'"
ucfaa'a parcaataa*
af laacodlat «o
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udl*l Id It.
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ltutlW
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556
APPENDIX A
RECOMMENDED PROCEDURES
FOR PHASE II STATISTICAL SAMPLE DESIGN
FHLBB Contract # 677040
B Contract f 2-300- C4- 113-02
February 27. 1978
Submitted to
Federal Deposit Insurance Corporation
Federal Hone Loan Bank Board
Submitted by
JRB Associates, Inc.
8400 Westpark Drive
McLean, Virginia 22101
^■SA'f
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1. INTRODUCTION
Thta report provides information concerning cluster sampling with
probability proportional to size relative to Phase II, Accuracy. A separate
companion roport Is also Doing submitted which addresses racoMMndod audit
procedures and tha protest plan. Tho relationship of thosa aspects of
Phase II to each other, and to the remaining tasks In Phase II, Is depicted
fn Figure 1.
Tho objective of Phase II Is to estimate the accuracy with which the
depository Institutions are compiling their HHDA reports and to gather data
on the Methods, costs, and problems associated with the preparation of tha
report. This report describes the recommended procedures for selecting a
sample of the depository Institutions In the three SHSA's and, within these
Institutions, for selecting a sample of mortgage loans for geocodlng analysis
and for selecting a sample of census tracts for aggregation analysis. These
procedures will be used by JRB personnel In conjunction with FHLBB/FDIC
examiners to obtain the Information necessary to estimate the degree of
accuracy In report preparation. In addition, a survey will be conducted to
determine the methods, costs, and problems associated with preparation of the
HK)A report. This Information will be used as the basis for several of the
reports In Phase IV. JRB's original plan was to conduct only a limited
pretest of the on-site audit procedures and survey methods. This pretest
MS to be done at one or two local depository institutions, and It was to be
only a check on tha workability of the data collection procedures. During
the discussion of the detailed work plan. It was felt that this limited
approach was not sufficient to test against the possible difficulties and
problems that aright be encountered in the various banks and savings and
loans.
The new plan expands the pretest Into a complete test of all audit,
survey, and estimation procedures 1n three to six depository institutions In
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O-^ X"1
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it study SKA'S. This coeplete pretest will ecconpllsh four Important
jrpoiM. First, It will reduce th« rise, of encountering serious problems
wit tht castalttt audit Is conducted 1» the staple of SO Institutions,
■condly. It will provide ■ preview of tht results to be expected 1n the
ittaatfon of accuracy. Thirdly, ft will allot. ■ reflneamt of the esttauitad
Tfort required U conduct the full accuracy audit. Fourthly, It Mill provide
id early indication as to whether or not thaaa procaduras and data can be
tad In other araai (f .a., Coawiltjr Rjtiavettatat Act, Civil Rights Settle-
mt).
During the protest, the adequacy of tht procaduras used to gather data
id quantify the errors In the HMD* report* will b* thoroughly tested on-site.
Ijustmnts to tht procaduras will be aadt to ellalnate tht anount of trial-
i-arror tl«e that would otherwise be expended during the conduct of the
■plete accuracy audit of 60 Institutions. One critical aspect of the
xuracy analysis yet to be coaplately resolved Is tht precise role of the
iglonal exaalnars In the Identification and retrieval of pertinent data
■cat those Institutions selected for audit.
The level of effort necessary by the institution in the preparation
' the HMD* report and 1o responding to tht audit will both be estimated In
a iMaabtr of personnel required
a nuwber of parson-hours required
a Buaber of coanutar pi qui tal raqvired
a aanunt Of coiputer thee required
• expected costs to each institution.
Tht pretest of three Institutions will provide tht FHLBB and the FOIC
th insight Into the procedural and organizational problems associated with
■dltlag tht accuracy of the HMD* reports. Following the pretests, it will
i possible to refine the estimated effort required to conduct tht full
xuracy audits. If tht results of the initial throe institutions are not
ifflcltntly conclusive, up to three tare institutions will be pretested.
A.-S
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The procedures assume that the following Information would be provided to JRB
by the FHLBB, the FDIC or the regional examiners;
1. For eich SHSA, a list of all Institutions required to report
under the Act, and, for each, the number of mortgage loans
made In 1977.
2. For each Institution to be sampled, a copy fo their 1977 HHDA
4. For each Mortgage loan selected for geocodlng analysis, a listing
of the mortgage loan nuaber, the complete property address
(street, city, state, zip coda) and the census tract.
5. For each of the 15 census tracts selected for aggregation analysis,
and extract from the «ortgagt files of the following information
on all loans (single family, niultl f ami 1 y . home Improvement, and
non-occupant): census tract, dollar amount of loan, type of
loan (FHA, VA, FMHS, Conventional) home Improvement Indicator,
non-occupant ndlcator, multlfamily dwelling Indicator, and
originated or purchased Indicator.
During discussions with the FHLBB. JRB has proposed that, whenever
available, an automated listing of data necessary for the geocoding analysis
be considered as ground truth for the purpose of this study, since the
accuracy of the property address and loan nurber of selected MTrtgages on
the computerized file 1s anticipated to be acceptable.
For the aggregation analysis, however, computerized data may not be
acceptable as ground truth, and JRB has proposed that the examiners extract
the information Identified in item IS above from the individual loan Jackets,
preferably by reproducing a copy Of the loan agreement.
It has also been suggested that the visits by JRB to the Institutions
be coordinated with the Institution's scheduled audit by the regional
examiners. Whenever possible, JRB will attempt this coordination both
during the pretest and during the complete audit.
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661
2. STATISTICAL SAMPLE OESIGM
This chapter present* details Of cluster sampling with pufMHty
iportionel to site relevant to Phase II, Accuracy.
The primary objective of the proposed sampling 1s to Investigate the
uracy of loan geocodlng within each of three SHSA's. Thus, the population
be sampled Is the collection of loan reports within a SMSA.
Drawing a simple random Seattle from the population would be difficult
ause of the need to prepare a 11st of all loans fn a SMSA and the high
t of surveying geographically scattered sampling units. The sampling
vey Is Bade easier In teres of preparation, cost and admin 1 strati on If
sampling units that are to be selected were In clusters. Accordingly
h Institution is considered as a cluster and a random sample of institutions
selected. In other words. Instead of selecting loans one at a tine, we
act groups of loans, where each group is in the sane institution. Once
sample of institutions 1s selected, then randoa saaples of loans are selected
a each selected institution.
In this two-stage sampling plan, each institution or cluster 1s called
rlaery stapling unit and the loans are called sampling subunlts. The first
ge of the sampling plan Involves selection of a sample of primary sampling
ts where the probability Of selection is proportional to the size of the
t. The second stage Involves selecting a constant number of subunlts
* each selected primery unit using simple randoa sampling. This approach
ires thateach loan within a SHSA has an equal probability of being sampled.
:* there Is no evidence to suggest that geocodlng accuracy Is highly cor-
sted with size or type institution, stratification to control these para-
ars is not used.
The reduction in cost and ease of administration for cluster sampling
jus selection of a larger sample than with a one-stage simple random
sling plan. This increase in sample size should more than compensate for
loss in precision because of the use of cluster sampling rather than
gle random sampling. The sample of Institutions and loans within an 1nst1-
lon will be large enough so that loan geocodlng accuracy can be estimated
A-7
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with sufficient precision. For other characteristics of secondary importance,
we rill accept whatever precision 1* attained. Som of the charactert sties
of secondary importance Mill be estimated with sufficient precision, whereas
others will be estimated with less than the desired precision. In either case,
the various results of the sample oust be Interpreted in light of the precision
actually attained.
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2.2 notation
H - nuaber of cluster* (Institutions) or prlaary stapling units In the
population
a ■ i— cur of clusters selected for stapling
N( ■ nuaber of subunlts (loans) In the 1th clutter
n, - nuabar of subunlts stapled froa the 1 cluster
* -EH.- nuaber of subunlts fn the population
n -In,* Mater of subunlts In the staple
„ I ■ 1 - accurately coded population loan j froa psu 4
-1 | ■ 0 ■ Inaccurately coded population loan J froa psu 1
x | ■ 1 accurately coded staple loan J froa psu 1
■ ( ■ 0 Inaccurately coded saaple loan J froa psu 1
I. ■ I1 X., nuabar of subunlts accurately coded In 1th psu
1 J-l U
<i * E <« nuabar of subunlts accurately coded in saaple taken froa i psu
1 JM U
H
( -IX,* auaber of subunlts accurately coded 1n population
1-1 '
■
t • Ex, ■ nuabar of subunlts accurately coded In sa^le
1-1 '
X. th
'l " IT " *1 " Br0PBr*^o> °' loan* cod,d correctly 1n 1 psu
i, • ~ » x7 ■ proportion of loans coded correctly In saaple taken froa 1
X 1 N
' "i" T«| I N(P. - proportion of loans coded accurately 1n population
■ - 1 ■
> " T " * " T E njP< * proportion of loans coded accurately 1n sample
n n ,., i i
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664
2.3 Sampling Procedure
The sampling procedure will b« described by My of example. The following
steps art Involved:
t. Identify each Institution and Its size N. In terns of the muter of loans
geocoded during a particular time period!
2. List the Institutions as 1n the example shown below.
Institution Size N, Assigned Range
tESHl NJ !
A 350 350 1-350
1 127 477 351-477
C 4,520 4,997 47B-4,997
D 117 5,1H 4,990-6,114
E 316 5,430 5,115-5,430
F 3,010 8,440 5,431-8,440
S 1,843 10,283 0.441-10,203
3. For the example, we select a number between 1 and 10,283 at random. If
it falls between 351-477 and so Institution B
Note that the probability of selecting the 1
"i ■ htj " r
That is, the psu are selected with probability proportional to size,
where size refers to the Size Of the psu In terms of II. , the number of loans.
and not in terms of the number of accurately coded loaAs. For an un-
biased estimate of the number or proportion of accurately coded loins,
we should be selecting probability proportional to the number of correct
loans. I.e., we are substituting Nf/N as a good estimate of X,/X.
The above step Is repeated until the required number of primary sampling
units are selected. Note that since we are sampling with replacement,
1t 1s passible for any particular Institution to be selected more than
once, I.e., one institution can represent more than one sampling unit.
For each of the m primary sampling units selected (the same Institution
may be represented more than once], we draw a subsannle of size n according
to the following steps.
a. for a selected Institution, make a 11st of the geocoded loans and
give each a nunber from 1 to n, — the total number of loans 1n the
1nst1tuJion. _
b. Select n random numbers (n loans) from 1 to N, without replacement.
For example, If there were 127 loans In a selected institution and
we were to sample 6 of these, we would need to generate a series of
three-digit random numbers. Numbers greater than 127 will not cor-
respond to e loan number and to avoid wasting a large portion of the
randan numbers, we can divide each number bv 127 and use the remainder
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it the selected r
» th* 1Z7*" loa
• art uilng 7 full Intervals
_. . .... . Randca Nriwn fna 890 to
999 art discarded. Th* following example lllustritM th* procedure.
367 113 113
Hot* that the iMplIng Is without replacement end io the probability
of th* first loan selection Is 1/N.i the probability of the second
selection Is l/(«,-l), andso forth!
Repeat th* above itapi for each of th* ■ selected primary sampling
units. If an Institution was selected pore than one* In the first
sampling stage. It 1s possible for a loan to be selected nor* than
one* In th* second stag* of saaoHng. This can occur because each
tempi* of loans 1s selected from the couplet* psu. That 1s, the
second staple 1s selected after replacfng the loans that were
selected th* first time. A loan that happens to be part of wore
than one sample Is treated no different statistically than any
other loan which It selected as part of a particular random sample
from * psu. I.e., th* loan b*cn*as part of two different, statisti-
cally Independent samples.
It 1s possible that th* maaber of loans within a particular Institu-
tion H lets than the number of loans to be selected for sampling.
In this case, th* procedure outlined 1n step Z must be modified.
One method for dealing with the problem of cluster sites smaller than
n Is to combine such psu't with adjoining ones, 1n advance of the
temple selection, so that all ptu's so constructed are of site equal
to or greater then n. k small psu may be combined with one or more
other small ptu's or with a psu already of size n or greater.
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Z.* Estimation
The m1ii objective of the sampling survey 1s to estimate the proportion
of loans accurately geocc-ded. This section shows how an estimator of this
population parameter Is calculated. The estimator Is based on a sample of the
loan population end, therefore, a "sampling error" Is associated with the estimate.
To partially overcome this inadequacy associated with a point estimate, we
estimate Its variance and use this In the determination of an Interval estimate
which 1s made with a specified confidence. The point estimator determination Is
shown as Item 1 below and then three further steps lead to the Interval estimator.
P - -± Z Z x., - i E p. -X I p. - p
Ml <-l j-1 'J " 1-1 ' " 1-1 '
Z. v(P) : Variance of estimator of P
V(P) -^ I HttTrI)2 + ^r I (Ht-ff) 4 - ^ =»i(VP,a + mir L 'V^
The first term on the right-hand side shows the variation between cluster
mans. The second term on the right-hand side shows the variation of the
subunlts within the clusters.
op "Vv(P) is called the standard deviation.
Computation of V(P) Is not possible since 1t requires knowledge..ofj( .
for every loan In the SMSA. Thus, we use the sample estimator V { P)!J
3. V(P) Unbiased estimator of the variance of the estimator P.
Vv(P) is called the standard error.
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9 - it: < ? < P ♦ t m : Confidence Interval for P based on assumption
a r ar that dlitrlbutlon of P has a normal distribution.
constructing the confidence interval Htlmtor for P, we need to determine
margin of error, or precision, represented by a"*asp "he" the assumption of
mellty holds. Tha dlitrlbutlon of P It approximately normal anon tha sample
• and value of P Mt the following criteria ai ttated by H. S. Cochran
mpllnc Techniques. 3rd ad.. Him York: John Wiley 1 Sons. Inc.. 1977. p. 58).
p
Sample 51 m
.5
> 30
.4 or .6
> SO
.3 or .7
>.w
.2 or .8
> zoo
.1 or .9
> 600
.OS or .95
> 14O0
Khan the sample size It not sufficient to Justify the normality assumption
ad on the above criteria, then a confidence Interval can be found based on
1 actual distribution of tha estimate of P. The actual distribution is a hyper-
aetrlc and published tables are available for various ranges of P and sample
•. When tha sample size It saa.ll relative to the total population (nuaber of
ns), than tha blnoarial distribution (s an accurate representation of tha dls-
butlon and tha coaprahenslve sets of tables available for the blnoarial can be
d.
The sample size is generally of sufficient magnitude so
it tha assumption of normality holds. In this case, we
id to determine za and tj at noted above to construct the confidence Interval .
1 variable so Is tha tUndard error associated with tha estimator P and 1s
culatad as shown In Step 3. The variable z 1s tha abscissa of tha normal
ve that cute off an area of a at the tells where l-a 1s the reliability of
confidence Interval in anoaapastliMj P. For example, for a 9SI reliability
1.96 as determined from tables of the normal distribution. Thus, for a
tlcular reliability and standard error, U 1s possible to make a statement
ardlng tha margin of error, or precision, of the estimator of P. * common
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expression of this 1s to state that with confidence or reliability (l-o)J, tht
Interval Ptd Includes the true value for the proportion P. More precisely,
once the value of P and d have been deteralned, what we are saying 1s that In
the long run, (l-a)l of the Intervals so coeputed can be expected to Include
the true proportion P.
Note that the precision d and the reliability are related. If for a
particular standard error, the probability Is 19 In 20 (951 confidence level)
that the sample estimate will be within .10 (d-.10l of the true figure, then
99 out of 100 tines It *11T be »1th1n -125and 997 out of 1000 tlnas it will be
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SggBlJ Site - Cost Constraints
To taplaaant the described cluster stapling plan, we must determine iprtoH
i aeny Institutions (■) ire to be selected for stapling and how aany loans (n)
i to bo sampled froa MCh of the h Institutions. The values for n and n should
dtatwliwd such that the variance of the point estimator of the proportion Of
urate loans. V(P), trill be a minimum for any given level of total sampling
it.
The objective, then, Is to minimize V(P) as calculated In the above section
estimation subject to the cost constraint
c - eg + cf, * cjH
tre Cq represents total fixed costs, c, represents the cost associated with
ecting and preparing an Institution for sampling, and Cg represents the cost
toclated with selecting and Inspecting a loan record for geocoding accuracy,
a that only the costs c.n and c-neV are affected by the values of in and n and
only these variable components of the cost function will be considered
ther.
Using the Lagranglan multiplier method, we can convert the above stated
■strained minimization problem Into an unconstrained problem and use ordinary
Iculus to find the optimal value of 7i and, hence, a for any particular level
variable cost.
I staple estiaate of the variance between institutions Is shown by s£ i
i staple estiaate of the variance within an institution Is given by sj
e last expression follows since staple randoa sampling is used within
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institutions. The mean variance s, It simply ■ weighted average of si
The sb and s( are usually obtained fro*, a pilot survey. However, even
without the benefit of a pilot survey. It Is possible to establish approximate
bounds for the Inter- and Intra- Institutional variances using expert opinion
regarding probable values for p.. The Inter- institutional variance should fall
within 0.0 to 0.0225. The zero variance corresponds to all pf being alike.
The upper bound corresponds to half of the p1 being relatively low, say 0.7,
and the other half being near 1.0. In the event that m, the ntaeber of insti-
tutions sampled, 1s as small as n-2, the upper bound Is increased to 0.04S.
The variance within an institution might range from 0.0 to 0.21 which corre-
sponds to a p. from 1.0 to 0.7. The table below shows the interrelationship
between the ranges of these two variances (they are not simultaneously at a
auliaum).
0.0225 0.105
0.045 (a-Z) 0.105
This Inforvl analysis of variance ranges suggests that s. < sf and 1s supported
by another observation: the variance between Institutions is a variance of ■earn,
the pt, and, therefore, can be expected to be less than the Intra- Institutional
variance which Is a variance eaong Individual observations.
Returning to the da termination of * and n with this insight into variance
ranges, we note that the fonaula for optical n can be approximated by
"V^
A reasonable lower value for n eight be two tlees ycj/cj,. This ine
Is not very helpful In determining n when the c. and c, unit costs a
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571
sane) general magnitude. However, for the sampling problem being considered
here, the per unit Institutional cost c, Is likely to be on the order of
1000 times greater then Cj the per unit loin sampling cost and rtj/Cj than
provides a realistic lower bound on n. When c1 Is several orders of magnitude
greater then c2> the Institutional cost component c1 Is the determining factor
In establishing an appropriate value for ■ when the total resources available
are restrictive. This can be seen from the cost function.
The table below demonstrates how ■ and n vary as a function of the cost cone
nents. An Integer value of m and n Is determined such that ^n 1s as close
■ Inequality n > 2 £]7c£ and the variable c
as possible without violating
bound.
Total
Variable Cost
c1
10,000
1,000
10,000
1.000
10,000
500
10.000
2,000
20,000
1,000
20.000
1,000
20,000
500
36 55
It should be noted that the total variable cost bound is only approximate and
thus, in situations where n appears smaller than desired (i.e., 1t 1s close t
the bound 2 ^7c"2l, ft could be Increased somewhat without affecting total
cost to any great extent.
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2.6 Saapla Size - Precision Constraints
A retaining qmitlon Is whether the staple Hies associated with the budget
level* In tha table shown above, or at any other arbitrary levels, are sufficient
to provide a reasonably snail margin of error or precision (at, say, a reliability
of 951) In the estimation of P, the proportion of loans accurately gaocoded.
Strictly speaking. It Is impossible to establish the margin of error until
the saeple has been obtained. Without the results of a pilot survey
to provide at least rough estimates, we must resort to worst case analysis.
In this way, we will at least be able to establish an upper bound on the nargln
of error for a particular sample size, or alternatively, the sample size re-
quired to assure a nargln of error below a certain magnitude.
As noted above, the margin of error, d, 1s a function of the desired
reallablHty and tha standard error as determined from the expression
With the assumption that the distribution of the estimator P Is approximted
by a noma 1 distribution,! Is easy to obtain for any desired reliability 1-a-
Establlshlng upper bounds on sp Is not as straightforward. As noted In the
section on estimation.
*B-Vv(p7
«?t?>-iiiW ,v>i-*)!
The Mxlaw value for (0,-0) occurs when half of t
e other half are high. If a reasonable lower bound on
per bound Is 1.0, then the maxleun (prp)2 Is 0.0225.
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578
a reliability of 951 (i - 1.96) and a precision of, say. -OS, we find
■ the relationship between d, i and t* that tha maximum ■ required la 36.
a upper Halt on tht number of tmtltutlom to ba sampled Is, of course,
andant on our wont case estimate of the variance. If tha variance is nor*
tMBbly eatlMtad by half this figure, than tha number of institutions sanplad
Id ba cut in half while maintaining the sea* precision. This would move it
htn tha range obtained In tha coat analysis examples.
A lower estimate of the sample size required to assure a particular bound
precisian can be obtained by viewing our sample as equivalent to one drawn by a
pie random sample. In this way, we can estimate tha required sample size
ng a simple for* for tha estimation of tha nexlmua variance. For a simple
doe sample, the estimator of the variance of P for a sample size of mn 1s
2 . Plj'1-^' . IS*
n the sample size is small compared to the total population size N, and
lacing mn-l by mn the variance can be approximated by
letting p.. -0.7, we find
•if
in for a reliability of 951 and a precision of .05, we find that mn equals
ue know that this sample size Is sufficient whan It 1s drawn from
osi the entire population. In cluster sampling, we are concentrating our
pie of loans from a smaller number of Institutions than might ba expected
be represented from a simple random scheme. To the extent that n" loans
pled from a single institution will have lets variance than n~ loans
pled from the entire population, this approach underestimates the minimum
pie size.
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The preceding analyse! can bt brought together Into a single tibia for
various levels of precision and reliability (while kaaplng the stated estimates
of p, for esxlmuei variance).
Recall that ■ refers to tha number of primary sampling units to be selected
and since the first stage sampling 1s with replacement, a large Institution
■ay be selected acre than once with a corresponding multiple of n samples
taken from It [I.e., the number of sampled Institutions will be < ■).
From the cost analysis, it is apparent that It 1s not feasible
to select the required number of primary sampling units for the most stringent
levels of reliability end precision. Of course, the actual between Institution
variance alii very likely be considerably less than tha maximum variance esti-
mate used in the analysis and, therefore, the specified levels of reliability
and precision can be realized with a considerably smaller m than the one listed.
Reducing the variance to half the estimated maximum will result In a requirement
for only half the stated value for m.
One the basis of the foregoing discussion and analysis, what are reasonable
values for both m and n? Until further information can be gained from the pilot
study to Improve upon the estimates of variance, a target value for m eight be
25 with n equal to 50. Again, an institution with a large number of loans may
be selected more than once for sampling and, therefore, the total nunber of
Institutions to be sampled will probably be lass than 25. For each institution
selected, 50 loans should be sampled, 100 if It Is selected twice, etc. (If
the marginal cost of inspecting an additional loan record for accuracy is smell.
It may be desirable to Increase the n to a level such that a statistical state-
ment of reasonable precision can be made regarding each Institution sampled
rather than the focus being on Just the population of loans within the entire
SKA.)
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576
Under soae circumstances, it 1> possible to continue with further stapling
■I -I* the saaple artel Initially Is not large enough to achieve the desired pre-
cision. As stated fay Hanson, Hunritz and Hadow (S— nla Survey Methods and
THoory. Vol. I: aethods end Applications. Hew York: John Wiley 1 Sons. Inc. .
1«S3. p. 7g),
"...Not* that the Incraasa of saaple size undor such conditions any
soattlaas result In a significant bias If tha Initial saapla sin Is so
saall that It gives an unreliable estimate of tha variance and tho
estimate of the variance 1s correlated with the estimate of the Item.
But If tha initial saaple size Is large enough so that the estimate
of tha variance 1s subject to a coefficient of variation of no
greater than, say, IS percent, then one aay be able to use this approach
with reasonable assurance that If biases result, they will be saall
relative to the standard error of tho sample estlaate. Such a aethod
>1U load to an underestimate of tha variance, but this bias (s aade
saall. ■
Tha coefficient of variation of any saaple estlaate Is equal to the standard
•error of tha estimate divided by the value being estimated--* J 'P. Mote that
If P - 0.7, the standard error can be is large as 0.1 and still emt the
guideline provided by Hansen, Hurwlti and Nadow.
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Order the census tracts by number of loam.
5. Audit every loan m each of the 15 census tracts selected for institution 1.
(We need to review all loans m a census tract since we are Measuring
aggregation errors rather than sampling Individual loan errors.)
S. Reconstruct the HMOA report line Haas corresponding to the 15 census
tracts. Note classification errors by type of loan (FH*. VA, conventional,
multi-family) and by type of error (slsclasslflcatlon, transcription,
computational).
J. If statistical analysis of the Measured data aggregation error rates yields
estimates that are unacceptably high to the FHLBB and If the estimates are
of insufficient precision, additional census tracts will be audited to
estlmta the nature and magnitude of these data aggregation errors more
precisely.
i. Repeat steps 1 through 7 for each institution selected during first stage
of sampling.
* Note: This sampling plan corresponds to the one originally proposed.
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m
rox hme tt Acccmci ad
AMD PUBRST PLAN
F ■binary 27, 1978
Fadaral Mpoait inanrano* corporation
JR xaaociataa, inc.
0400 Waatpart Driva
Kcl*«n, Virginia 32101
fi!
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UBU OF coraurts
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rhia report provides inf ormation on the I
ud prataet plan for Phase II, Accuracy. A aeparata oompanion report la also
telng submitted which addreaeea recommended, procedurea for cluster smapling
"lth probability proportional to all*. The relationship of thasa aapacta
of Phase II to aacb other, and to the ■ a— lul inj taaka in Phase II, la
oapl-cted in Figure 1.
Tba objective of Phaaa II la to eatiaata tha accuracy with which the
<*>:p<3sitory institutions are compiling tbalr HKDA raporta and to gather data
"> tha methods, coata, and problama asaociated with the preparation of tha
™p«3rt. Thia report describes tha recommended procedurea for auditing a
'—tila of tha dopoaitory iaatltutiona in tha thraa SMSA'a to estimate tha
'•'Jim of arrora In geooodlng (i.e., tha incorract aaaigntant of a oanaua
tx'«et to tba addraaa of tha property) and for identifying aggregation and
**-»elaaaification arrora. Theae procedurea will ba used by JHB personnel
1(1 conjunction with FBLn/rTlIC examiners to obtain tha intonation necessary
t* estlnata tha degree of accuracy in report preparation. In addtlon,
* aurvey will be conducted to determine tba method*, coata, and problama
*n»»ociated with preparation of tha HMDA report. Thia information will be
x*"ted aa tha baaia for several of the raporta In Phaaa IV. JPJ'a original
S*lan waa to conduct only a limited pretest of tha on-site audit procedurea
**id aurvey methods. Thia pretest was to ba dona at one or two local depository
l-natitutione, and it waa to ba only a check on tba workability of tha date
■Collection procedurea. During the discussion of tha detailed work plan,
It wma fait that thia limited approach, waa not sufficient to teat egalnat
ten* possible difficulties and problama that might ba encountered in tha
Various banks and savings and loans.
Tha new plan expands the pretest into a complete teat of all audit,
aurvey, and estimation procedures in three to six depository institutions in
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bUtlooahlp of Phu.e n Tank.
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• atody Mfa'a. Tola eoaplata prataat will accoapliah four 1
rpcaaa. rlrn, it will radaoa tha rlrt of a
m Um oaanlata audit l ■ oooonctud in tha aaaaj la of eo 1
goodly, it will prorida ■ prawiaw of tha raaulta to ba arpactad in tha
Cisacion of j.-qh:-;. Thirdly it will allow a tafina— nt of tha aatiaatad
fort raquirad to conduct tba toll accuracy audit. Fourthly, it will provlda
I early Indication aa to whatbar or Dot thaaa procadurua and data can ba
ad in otbar ana* (1.*., Ccaaranlty Bainvaataant Mt, Civil Ughta Sattla-
nt).
During tba prataat, tba adaquacy of tha procedural used to gather data
d quantify tba errors in tba WDa raports will ba thoroughly tasted on-slta.
Jiil pan I a to tha procedure* will ba —da to eliminate tba aaount of trial-
-error tine that would otharwiaa ba expanded during tha conduct of tha
aplat* accuracy audit of 60 institution* . One critical aspect of tha
curacy analysis yet to ba conplataly resolved la tha pxociaa role of tba
n and ratrlaral of pertinent data
■ aalactad for audit.
Um laral of affort naeaaaary by tha Institution in tha preparation
tha MM raport and In reapondlng to tha audit will both ba estlanted in
nuabar of personnel required
nuabar of paraon-honra required
nuabar at ounputar prograna required
aaount of coacutax tlae raquirad
tha pxataat of three inatltutiona will provlda tha FHLBB and tha FWC
Eh insight into tba procedural and organisational prsblana associated with
llting tha accuracy of tha hkda raporta. Following tha prataata, it will
possible to refine tha aatlnatad affort raquirad to conduct tha full
suxacy audita. If tha raaulta of tha Initial thraa inatltutiona are not
rficlantly conclusive, up to thraa nor* Inatltutiona will ba prataatad.
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each shea, ■ liet of all Institutions required to report
v the Act, and, for snch, the ninber of aortgaga loin*
I In 1977.
aach Institution to bo ussplad, ■ copy of their 1977 mu»
art.
■saplsd, ■ listing, by losn malar,
For each ■ortgage loan salactsd for goocodlng analysis, ■ Hating
of ths aortgaga loan number, the ccnplsta property eddrass
(■traot, city, state, sip ooda) sod the census tract.
lected foe aggravation a
of ths following inf oroa
>r each of ths 15 census
an extract t cob the nortgege files
on all loans (single family,
non-occupant) i cenatii trsct
loan Cra*. va, fmHa, Ccnvsni
non-occupant indicator, ■nltlfamily dualling indicator,
originated or purchaaed Indicator.
During discussions with ths FHLtt, JRB has proposed that, whenever
available, an autoutad listing of data necessary for ths gaocodlng
bs considered as ground truth for the purpose of thia study, sines ths
accuracy of the property address and loan nuabar of selected mortgages od
the computerised file la anticipated to be acceptable.
For ths aggregation analysis, however, ooaputsriaed data «ny not be
acceptable aa ground truth, and jus has proposed that the examiners extract
ths information identified in Irani #S sbeve fresi ths individual loan jackets,
preferably by reproducing a copy of the loan agreement.
It baa also bean suggested that ths visits by jn to the institutions
bs coordinated with ths institution's scheduled audit by the regional
axaninars. whenever possible, JIB will attempt thia awiUutim both
during the pretest and during the couplets audit.
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a. MBIT MOCEDTOBS
jbb will adit selected financial institutions In Chicago, Ha Diego,
d Buffalo to obtain data on th* proms** aud oo*t* associated with th*
■paration of th* HUD* Report, mforsatlon will also to obtained to
nit Jk> to analyse th* accuracy of j—w ml Imj and data aggregation
lei-taken during tha preparation of th*** reports.
The procedures reccaaendad by JIB to audit aach institution ar* designed
tha Hquaitial *ari** of *t*rt* dasorlbed below. These «t*p*, nay faa
rfomd concurrently for several institution* within an Ml, or, for that
ttar, cunumiantly for institutions io several Sana.
lection, notification, and Survey
Stop 1. Th* PDIC and tha PHLBB will provide to JRB a list of th* nana*
all regulated institution* in Chicago, San Dlago, and Buffalo required
r*purt under th* Boa* Mortgaga Diacloaurs hot as of Decanter 31, 1977.
, tha PDIC and tha PHLSa will provld* to JIB tha total nuator
* loan* mad* by osch of these institutions In 1977.
■tap I. Using th* data provided by th* PDIC and tha PHLBa in Stsp 1,
1 will proceed to rank all institutions in aach SMS* in descending ordar
•ad on th* ngaher of aortgage loans Bad* in 19T7. in will than randoaly
Laet a noabar of institationi fron each BUM for inclusion In tha study.
Stop 3. J>B will provide tha PDIC and th* FHUn with tha list of
rcltution* to to sampled in Chicago, San Diego, and Buffalo. Tha PDIC
1 tha PEUa will contact th* appropriate regional offica to determine
in these Institutions ara *eh*dul*d for audit. To what**** ertent
islbia within tha Ciaa and raaouroa constraints of th* contract, jhb
LI strive to ooordlnat* oar visit to th* institution with that of tha
Stop*. Tha PDIC and tha FKUS will prepare and aand a latter to *ach
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t»\»rt«4 laMatakiaa, to Won taaa o* tba gupu ad aoopa of Um BMU
**M», HMiM with Oils !*«■ "ill a* a amlPi iln, |MH»< by JRJ,
*N« MtWH UtaMta •» taa ipinaiaa w< by th. institution. Is
*»* **^***«iaB ■»• *a* a"B» ^W. «■* «"• casts uaodatad vita this
W»*1»A—. mttWMMt. " *■*« at tan I Hi i ■ "HI b* •nbaittad
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•tiaa*, ;ity, iuc* and ai? ™ta, w< taat eaaaaa mki. Fur ■
MM aalaoea* tea ■aaaaaatlaa — l|rti, tka roiC wmd ta* ru
-.■ij-rjii'' Wgaa— J !■■*■■" <ar froa taat iaaUtatioia dlraetly, i
MWW> a»*aaofc ft» tka — twjaf tUa of to* foUo-iaq L
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i laingla faaily, anlt 1- fully, boaa lajiimaaaill and n
, P)tU, Comntlcul)
Original or purchaaad Indicator.
Stap ■■ Oaing tha data provide by tba rote and tba l-HUM, JM will
oeoda tha addraaa of aaoh aortgaga loan aalactad for gaocoding analyai*.
< accoapliaa tola tank, a jn analyat tralnad In gaocoding tactuiigo** will
prorldad with only tba aortgaga loan nuubar and addxa** for all aalactad
ana. naing addraaa coding guldaa, ■:■■■■.;...'■:. aap sari**, tract ootltna
pa and ceMMrclal itraat aapa, an appropriate, this analyat will ba
■tructad to antar tba daalrad Banana tract niaubar (or aaoh addzaaa
Jacant Co tha loan onabar on tba eacnodiaa workahaat (Flgura 2).
Stap 9. Khan all loana for a aanelad lnatltution hara baan gaocodad,
a JBJ accuracy taak nanagar will coapara tha eanaua tract* aaalgnad to
cb loan addraaa by tha inatitutlon to thOM darlvad in Stap 6. Whananr
a aaalgnad eanaua tract and tha darlvad eanaua traot dlaagraa. tha JKU
curacy taak nanagar will prapara a naw gaocoding vorkshcat, which will
oluda all eanaua tract dlaerapanolaa for a specific inatitutlon. Thi»
rkahaat will b* glvan a dlffarnat in analyat froa tha ona that did tba
lginal gaocoding, and thaaa dlacrapancy loana will ba ragaoondad.
Stan 10. Tha eanaua tract* darlvad for loana ragaooadad in Stap 9
11 ba ooasarad with thoaa aaalgnad by tha lnatltution. Any eonau* tract*
leb, whan ragaocoead, agraa with tha eanaua tract aaalgnad by tha Inatitu-
on will ba oonaldarad corract. Any eanaua tract* which, whan rngaooodad,
aagraa wltb tha canan* tract aaalgnad by tha inatitutlon will ba furthar
aparad with tha eanaua tract darlvad in Stap B by tba first J«* analyat.
both JK» analyat* darlvad tba aaaa eanaua tract , and this eanaua tract
Han froa tha providad by tha inatitutlon, tha Inatltution'a aaalgnad
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3i,iii«db» Google
o be In error. Any three-way discrepancies ,
the first JM analyat and tin second
im» analyst, will ba iirtwui by the jn accuracy taaJt nanagsr.
■tap 11. For each Institution, a gaocoding wuy abaat Hill ba pre-
pared (rigor* 1) which identifies Um smsa and tha institution, and indicates
tha mtv of loana gaocodad and tha maacer of census tract* Id arror. All
suyyoatlng docuaentation aaaoclatad with each particular lnatltutlon, audi
amirauatlon and tjutar rol lowing*
■tap 13. Attar coordinating schedules with tha examiner* IBtep 3),
jhb will request that tha roiC and tha FKU> schedule alta visits with esch
sampled lnatltutlon. Prior to these alta visits, Jaa will have received
and reviewed tha completed questioiinaires, received and reviewed
tha naosssary aggravation data (Step 7), and. If possible, hava completed
tba ijanotWllnij analyala (Steps 8-11) .
■tap 11. jkb will ba represented by two staff a—1 in during aach
institutional alta vislr. Tha first order of bualnaaa at aach lnatltutlon
will ba to meet with tha approprlata offlelala of tha lnatltutlon to explain
tha purpose of tha vialt and to describe tha actlvltiaa already completed
uhiich concern that lnatltutlon (step 11) . Tha primary data collection
activity to be completed during tha on-site Interview la to review and
final I la questionnaire lnfanaatlon on ssuut report preparation and coats,
and to solicit comments on tha use of the BMDA reports and tha perceived
vain* of the legislation. Ons jn parson day has bean alloted on each slta
■tep 14. The availability of data required to couplets tha aggregation
analysis I sea Ins a complex iasus. Although IS census tracts will ba analysed
by JM for aach Institution, tha amount of raw data this represents will very
greatly from institution to Institution, nacsuss of tha possibls bulk of
«*-•» 0 - 10 - 3$
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ata In largo Institutions ud tba potential difficulty la retrieving
a im auh— I— I institutions, one jn pereon-day baa bean allotted
h aita visit to raeolve any problaa encountered by tba regional
ar in retrieving tba naceaaary aggregation data for tha 15 census
r each institution , jn will have randomly aalactad up to
tha nna aaport, aod tba foic and tba m
a ox fros tha Institution directly, will h
n tba forn of reproduced source documenta or an
ixogatlon data collection worksheet (figure 4) , all data nacaaaary to
iraata aacfa of tba IS canaua tract Una Items. JHB will use a canana tract
Motion worksheet (Plgure 5) , to racord aacb loan for a given canaua tract.
it, JBS will uaa an aggregation arror worksheet (Figure 6) to document for
* aalactad census tract, tha typa, and quantity of arror identified during
) coaparlaon of JsB'e work ahaat with tha inatitutiana anauy on tha HMM
■ort. An aggregation euanary worksheet (Figure 1) , will be used to racord
i total errors aaacelatad with tha aggregation analysia for all aalactad
iaue traota foe tha lnatltutioo. These worksheet* will be attached to the
' data provided by the PD1C and the nana and maintained a* p
•tap 16. Whan tha alte vlait has been ccnplatad and both tha encoding
ilvala and aggregation analysis ace performed. JIB will prepare a brief
ort that documents tha Information on procedures, coata, and error rataa
' that institution.
step 17. when all aalactad institutions In an MSA ban bean audited,
i will consoU.da.te tha reports prepared in step IS into an Stan report.
■tap U. JsB will oaa tha reports prepared in step 16 and step IT to
ilyse the accuracy of tba HKM data required under Teak 1.1, and to prepare
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■ will ba MWM with apaajaaajUbi official. In
.tost Institution to tOmxi.tr and aapaad tha intention tnnUM
tag HMD* procaasaa and cacti, Daring tha inearviawa, JM will alao
a tha =tmt to vUoh tha must Institution Utuu In purchaaad
d participations, totalis of tha » approach to tha doobla counting
HMd loan* tos nlnTiaaaa la a nock plan MUwM to tha FDIC and
■ on January a, ifM,
• following stops anat ba taJtan to anabls tha prataat to bag in i
ip_li tha rDIC and tha FBa will contact tha rational
aianhiaia In Ban Dlago and Chicago and obtain tha
Hat of lnatltatlona achadulad for audit In tha naxt
■tap Ji Ron tha Hat of institution ■ Idnntifiad In Stan 1,
tha rDIC and tha IBLaB will aalact a (roup ot six
Institutions which anconpaaa tha following
d savings and loan
d savings and loan
a loan processing aystaa
• h Chicago radaral Bona Loan Bank Board client
- A California Institution.
Tha FDIC and tha reus, aithar through tha regional
eaaminen or froai tha institutions alractly. will
obtain a copy of tha 1977 HMD* Report lor appro-
priata atata reports) for aach inatitutlon.
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■ of tha ntudy, innil of tha wrkahaata uaad to conduct
ad. Thaaa raviaad aorkahaata aca Included In thla aactloo.
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Hie Federal Heme Loan Bank Board and the Federal Deposit Insurant*
Corporation are jointly conducting a study to detenaiiie the
procaduraa and coats associated with preparation of disclosure
raporta enquired under the Heats Mortgage Disclosure fcet. Thia
atudy ia intended to provide information to enable the FBLaB
and the FDIC to assess methods and costs and to make improvements,
where possible. The information provided in the atudy vill ba
traatad aa confidaneial. It will ba used only for statistical
purposes and not released outside of tha atudy.
iMSTrronoNi
PERSON COMPLETING QDBBVXCanttlB i
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— com jollity i ta the tarda balow, plaaaa indicate the Individual
with overall rational bility fee preparation of tba ike* report and al
thoea individuals neponeibla , as applicable, for specific: portion
■~-~-^'-
—
Title or
Department
Phone
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Orijinationa , Part A
Purcheoaa. Part ■
Boaa Iaprovaaaot
— —
aaa deacrlhe briefly the aathoda and/or
_ a prepared. Me are Intereitad In the
typea of fllaa uaed, whether the proeeae in annual, eutcaatad,
or both, and whether you only parfora aaoeodlng eontlauoualy or
tivnly whoa the report in praparad. If you have written
d wlih to furnlah than, plaeaa do ao and akip thin atop.
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608
■ M IMCgi FLaaaa ladicata tha information balow concarnino.
f tin BMC* K
y raqoaati vara uh for tha BMDA raport In tin put yaar?
b. oo you provlda copying faellitiaa (or tha BHOa report?
Do you chaxga (or copying? lei »o_
DO yon faal that tha raport ia uaafnl? Ya« _
Could it ba nd* aora uMfol? If ao, hew?
u. Mlinr. la tha BUM raport a
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S. Probl—a lid laoiavintai Flaaaa ladlcata tha araaa la »(ilc*i »
tha aoat iifotl*— la tha preparation of tha MM raport and/or a
■hieh yon faal laprawaata can ba uli.
Daflaitiooa and Tarninology la tha *cti_
Sao coding Toola aad nathoda :
Catagoriaa of Louia to ba IncloJadi
Mh« (Plaaae apaclfy) i
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Rapoct preparation Activity
Coat III
P.rc.ntag. or Coat
Data Gathering
(Jaocoding leans Co Canaua
of Fllaa
Total
100*
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lacnrut Spalllut of swm « r:
■ Tract Stent* St*»* ■
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Eaoc*dlii| »ccor«cj to tin in Dlafa !
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I 3.6: COBp*rl>oa of Typ* of Dliclaaur* HH—li GaocodlnR
1 4.1; GwLod1n| jkii:urmr.y ,,.,..,,,...,,.,,.
■« l.lt 1H(H of CascodU*
3i,iii«db» Google
rowcnta
Tnla report a-aa prapaccd ay JU aaaoclataa, Inf., HeLaaa, Vlrtiola,
Carponr-ton (FD1C1 under FHLBE atud* contract o??040. Thi ourpoM o ! tha
coapiUo. the aortieia loan dfeclseuM HHWMI Idaotifr the t.Imi™
fracUaoot mnun loane «.d. 0, I— ifilW luajMl t« thaAM win
thoa. .ode hr otbet leaden, aad to pi.p.r. . lerlae «f t.petti addrte.m,
■ Tiilatj of leeuea ai»en aa tha coat of compliance and naja to laarore
rafnlttlODe, e«f orcavanr , taocndlne., aad tha aaafbaaaae of tha dliclooure
l»7t. Tha imlTtli la baaed upon lnfoTaatlon collacted la tore. Standard
HatEooolttea Itatlatleal Aran - Saa Dlaeg. Callforala| luffalo. Ran Tort;
and Chlcaao. IlUaola. Ilia atudj fa dirfdad Into tout phaHa.
a Pbaaa 1 Dmloa Caapater fratana, and Collect
a rhaaa 1 CoapLataaaaa
Digitzed by GOOgle
.
teenier of M.elaan. St.t—M rr.p.r.tioo
'
£-&£ ««-".th" Ac™*"T " "*" *"*M'
M.1
GMM-.,t^Mb..«ltMM
CMtHt—Mi
4
Do.hU Clou Mint
*
A Caicaatial rr— Hfc [0 Analyi. DI.crlain.tloo • « .
l.dlinlnt la »»ij'obovl»od ROM Hnnxai* Landlsi F.tt.rn.
rha...
»..*-« Uaact.
Co-U.no. AMI?.!.
Th. Coot of Coaplllni Ho— Han**** Wacloawa IcmoiKi
bTtolooo co IddaMM c
€
Utility si Ibi Real MctMt* DlKlamn Act Data
I of or cone of to* Ho*. Mort ■»(• Macleane act
Kathoo. Co laacava Cmaalm teenier
*
t"e"1™ *™,■,
I*, porno., of th... mart. 1. Fa aa.lat iu ratul.iorr •,•«!«■ i«
Minn
a batcat unaor.tandloi of th. lataet af tha Act en tnaaatclaa that in
HtjKI
to lco provlBlooa, to iiiiii th. geafslaue al the dl.elo.ura lafanattaa.
to aat.
caloa aar* to laaro.e mulatto*, ana aafaccaaaot, aaa ta emueet attkaaa
f« !■■
tenet tha laaaatrlaa' ability ta owl; with tha raaaliaaanta of tha Act
"* fc*U"" C'
*ThI. i
SSBSIKB-™
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-a MMM( ■rnboiji tar laproTlna. tt
r> Chicago, tuffalo, ml In Hits. Carrie*
0 IMC id™ cbfl BCCvracy of (•ocodluB,.
* (aocu*11n| acc*T4C7 I*#ultl !
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rhl,.,^
l.»
l.H
mm •uirni* »' r
UiciUi •COH7 Inll
Digitzed by GOOgk
la—a nnlll, ahaa coae-aTad to 1U ntnij ratio sf SO pjicin for
tascadlat Mi :(inialr« AD Fan A of tha Talr loualBa. Information Hui»«j,
■cUml in [h. 1—t uxiil run. altbanib ml dtpoalcorr laatltutloaa
hava »irtu«ll7 ■•stand ihi (Mcodins prscaaa. aas* km Hoi. galas, sroessarss
Hos» Bir^i)! D<iclciori JUUHHI, Coal! institutions Mt*JMs« bsloa
ba brcujbt up to an accaptaala lnl of ■•ocodlni xoirtej.
Mfalstles C. HI dapoaltorr InHlfutiuna did Dor cup lor emu trmi far
•ay latsnal ass. For thli nagi, tha naif »f tbaaa inatllutiona aan
of £ascodlnt* The Initial tapart o-n dapoaltory lnatltutlona o-f Eh* rss.siraasut
last Laana ba £«acodad by caoaua trscts vaa jubatantial la tana of IsaTBlBf
tba coDcasts aad apprsprlara t-aftrance cuola aad la laslswntlnf. cba aacsasar*
is isocodlni procadurai and accuracy could ba acblavad In at Isaac 20 asrcant
(tsslf la ralatlialT hli>.' The v.rlfltallon ■etboda outUoad ta thia »a«t
swld a.r»a 10 raduca [Us probl.a.
Digitzed by GOOgk
of (h* fact Ibal t.v.tll Addrai
a addition, tlu acudr found tl
•cl.nlr dlffanM lanl* of fHcodlBa, a.
tUJ could be iaoro»ad :
tring ahould locluda ,
■ th. beat arallabla jaotodini tools an balu, oMd. An
a aparoarlata tcola ouch aa Addtaaa Coding Guldaa ataould ba a
3i,iii«db» Google
3i,iii«db» Google
ntrMwero*
Tba parse** ol lhl> raport la to aaaaai tha aathoda catnalt; uad
by daaaaltory laatltatleaa to aaalin caaaaa ttacta t» ruldatclal addnaajaa
1.1 •COPE MB MCraOMLOCT
tba aaariat thouaand, tha tjpa o( loan [FHA, YA . faU. Cooiant lonal) , • hoaa
ladlcttai. auICKaally Indicator, aad in orlflnatad or vurebaaad ladle ator.
raoort prapararlon. la taraa of data, tha report addraaaaa tba locttleo
of tba proaarty aad tha Idaatlflcacloa of tha canaoa tract, la tana of
Bncaaaaa, tha taport addraaaaa tha captora, aaocadlot, adltlng. aad atoraaja
<*ch standard Hatnpolltaa Statlaclcal Aria (SK5A) Vy local i mil 1 ■■ aad tha
Burtau of tba Caaaaa aad vara laBarally daalgaad to achlara aoaa naif malty
of population charactarlatlca, acoaoadc atatua, aad Kvlroj condition*- Tha
ararata tract haa about t ,000 laaMaata.* Tbaa. tba cam* itacta cacmitly
3i,iii«db» Google
•uJ «•* Mmw mt— ral, on dm fro* tin IIW u
aaUtlat I— (Taj* Ira la taa Mud Itataa, partlcalarlr I
■tatlKUal »«aaa, tba data ikilW aurlaa taa 1H0 caaat
Ml, If aar, la uhlch a )lwm U locatae. and the n ;«cnr=in, tali Elaala*
» raat tka (ran can t» calatad to tSa proporly addraaa foe puipoaaa »r
a— ljala. dfictoaur* Tapart oraparatloD. or coapllanca aualoatlon, Tha
•ajactlaa -of thla part or" -tba ■cudy vaa to Idanc Lc? ana docuaant aaocodlot
■acaprlaarllr r
■M .OI.U-I 1
• U«t«lc d.c
aad laatltaclanal atatf :
•alj dmlmoiaparuloDoi
Digitzed by GOOgk
nj accuracy flndinn Im Bnllmlo, ChlcatB, mi !■ Olajo. TMi
Infenattea tina laalikt late ih. aatnltaaa of taa fitUin mwiod Mia
■aocodlPi aceaTacT aa wall aa tha lapaet of varlova aaocoaiaf aataaoa an
Tin taaafalBi ac
utile* ultlaatalj ti
3i,iii«db» Google
..
U «, *.*«, tka a^la, p
■acaaa la ■aalTaaa' la taraa of
clM fallal* (o.
ataaaai (1} aidraaa
captura, (1) caaaaa tract aaaltsaaat.
(» UH trM
■ant. aaa tdlt lnr.
•aa W caaaaa tract atata**. 'lpta
1.1 *n<«. . ad.
"" "■"""»«*«
.( .ta.. t-r ,tm-
f, add™. c.prar.
lavalvaa racaralot praaarty aadraaa
cat. far liw mpilrlat laorsdlao A
oraaa «aotar. typically eecara at tka
tla. > tea*. ^11.
•tin la •■tattta*.
faction 2-1 4* la! Ll tta aaaraaa caftan
"" -1 ""•"
laa aataatlal praam
— — — -"" "■
hlwai
MP, „„ „«« «
*uur.. laaalaaa tka aaa «f taocoalnt
1Mb ta ■>•!■■ •
nana tract naaaar
a aj apactdc ptoc.rtv ^Itw. Tkla
ant coapln ataj. ,
th. anrall ,.,).; od in, pr«i».
Tala atiu to daflnad bT th* laoca-Hni
tool, uaaa, tta aaaiuicatiaaa at
tta HKt, CD. •*■
ttar ia acedia* 1. aa
foraad on an aniclni baali at onra
■ M- -* " ""
""■ ■-■*"*■**
■acrtaaa thta atata la ilatall.
n.,Uril
«.. cam »M «,
Kara aad aalltlBt. laaalaaa raccinUaa.
•Ml aalclni can
tract ..!«... f« .taar-. H.».«i- *- atoclanr.
nt-i-an-l.
naMtt
MM, nana tract >
«„,, 1MM ..tabll.Ma, a*, aai,
ciiuit th* 11*
karma a toaclllc aaaraaa and tta caaaaa tract ta muck it ha.
ten aMlana*. taction 1.4 aaacrlkn tka caoaaa tract atataia atata ta aacall.
Oar Hfrt.
aca .ad aaaly.la taalcataa tkat taa cracaaaraa utllltaa
d..r In.- tncb Hi It.
kHtaal pajjaa ,,,„
r. affact a. tka accuracr ef tka
a.ocodlni p.K...
ana th. ta.ultlm accuracr af tka annual Badailll
MataaanU. n,.
roblaaa a»aclataa«
th each atata tkat van ldantlflad
•*rto( tta tacaracr •**•■ af tta ataaf
an dl.ca.Md la tka ft.lla.la. aactlaaa.
3i,iii«db» Google
CA^RE ADDRESS
•ppllcitian
CENSUS TRACT ASSI3NMENT
IsSEHg
BHH TRACT CAPTURE
:3srs££
GSMS TRACT STORAGE
: »»"-—■""•
IGOII 2.1l STMXI DT SEOCODIK
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■ ■• uaafal *,tlnj j, .-.-£,. J in, 1
I aatoawt** a)— ailal l^taa, a
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■ii-ii 3p»llm at !lr«*l i
lucorract spa Hint of
•ctlj ■p.ll.d Kitu md plici
I onlj Ml mill (bin
i ■lailu, dlffinai only ti
Digitzed by GOOgk
•akaa a. difficult ■• tanlH tka rmlH iMw that tonfUi to
Iha .ubjact prcp.rt,. **>!*, «1» «**»• «■ ■» aHtol 1> tallH altk HCk
• Ituatloa. U tha MUmil ll aaaatlM aaaa alftanat *la caaaa, tha
cornet Ann caa ka telinldl hj tha il» caaa.
LLKkUUMoflUM
carawi ctMt aiim -ha. aaa at ■«■ al Iha attar Utau saaaaaata an
locorract or lataaalaca.
har.l root. .X P.O. ha. Ul...... aaaa . .ItM anala* la th.
laocoalai pracaaa. 1 rural raata aaaraaa recaraaa (or •aocodlui aaraaaal
tool!. 11, kaajant, tha aaocoala* «aff la coaarlud of ippralaari. It
aacoaaa aoaalhla to aaacoaa tha aaanaa. Th* aaaralaar caa not. tha cornet
*tr.at Mkw aid locatloa at tha tlaa el tka propartT aaaralaal. Too.,
a coaaUta aaal accural, aaajaaa aaanaa aut ka racordad la aaaltlaa ta tha
■ml rata aaanaa to anld njactlaa of tha nral rout* lalnii. Vhaa a
caaalata aad acwiata atnat illrm la not aaallaala, aaacadlaf ahaola ka
tarlana* hr aa anrauar at tka tlaa af praaaitj aaaralaal.
1.1.7 Ul.ilnl. Haadvrftlna
Illaalbla haadniiiaa aaa raalt la tka Unmet aaaiaaaam al a
caaaoa tract ...4, tbua, aa laaccarata aatcaaa of tha laocodlm arocaa. afcaa
tha iaoc«!10| naff ■:■»«[ laaatlfa all tha latt.ra art/or Bulbar, al tha
capturad aadr»>. U!,« ,1, i, ocean lha taocaolaa ataf f MM aaka aa
■aaacataa pin' u to th. l.tt.r. aal ouabar o( th. aaanaa. Ih(a caa
Digitzed by GOOgle
„
C.«. tract -.1.™
at. the.
U"
•— the u„ of gaocod
■. IMll
hlcb
ukla th.
leccodm. •
off to
•Hi*
tTllipi
iclflc
mmm
add—. Tb
a ataj.
ft— d b, tht.a atpect
1 *HCOd
D| C«
ta ■•ocodlnf ataff ,
tad tba
tlao
fr— ■ (or aaeeedlaa.
Geotodlug
tool*.
can bo <
rb.t Banal
t OttOUtad.
n.
latf Tt.pOMlM. for
•OCOdlD.
an bi
aad. up o
f a cet>ar at
officer.
officer., npiunn
•Aalalacr
ittn
•HtetOBCI
er clorfca.
GoOCOdlO(
am m p.rformad M ■ tout
UulUe. !■
ttroap.c
MLj, Our
aulMl* la
MM
II, Accuckj. ladled
■* that t
... E
taa cow
—ate aad taalr varto—
alt.
oatln* hm u lapac
.a lb. *
tut«
-lth •*
eh eo— tt
acta —a
-.1.-4 to rife^
,,
Ceo.od.ri, Toil.
—
.«..«.
...».
C.ocoaini tool. MM
■ «•
codlni •till to —.1(
i ceuuo
tract
nuaber to
a. mrnin
Heocodln,
dM of t» trpaar ■
eual and
.-.Ml
ad. Hatai
al laocodlng
toola laclada
Mn
.. Coding Guide, and
tuna m
t Si,
. Auto.il
tad aaocodlua. tea la
utll
» ■ M.I ccajpuier
mi'i i
—all
a «IM
• WW uuabar te a linn
tapaa
of [aocodlna. tool. Id relation
tVtba
la-hou..
tie— dlecue
*' ™»'
U1UT, oual
Th. Hr.au .f tb. C— h- d
••If
>INI«
manual Ml
-tt-nod
taocediua. tool., lb- ■ !„
1. lnclud
cm*i
. Tract 5
MM Ibda.e
tba
—to.
• t.d i.ocodlu. KM
UMATOT,
rJ Ceuu. Tree
Outline Has
. Th*
Oka
> Tract Strtel Iod*M
Hd ADM
CH ■
■•■tut
• oalT for t
a urbanl.ad
of each 5HSA. The Co
— H Tr-
Outl
— Napa i
r. alto as 1
■apnprlitt
Hoc
dim cool became th.j
ite net B
nun
taMChl
•tr.at date.
Co— u* Tract
Outl
- H.p. depict only —
jet toad*
MM
and county dlrt.ta—
aad ea— ua
3i,iii«db» Google
*M*lr aaaa ACC la tU lailni
ACC (hick U pr.r.rcd bj ?ubt
a Tka Cam* Itaet Cudlug Dlraetarr
C ikfliln bav can aaa plaea aaaaa ara ta aa faaa4 la taa r
X Codtni Dlnctatr ori.nJ.M aa HI alphafcatlullr
Digitzed by GOOgk
D«t of Local plaunlBi A
"«•"»■»»■"■ ">•■•
" "" p°'1 0'"" 'D'"
3i,iii«db» Google
••lanl<« [»M ti
hart CD* 1* MS *« ■
s ip*clflc pro**rEy *
■■Jflrlcr of lutoHtiul goacodlRf cooli
r.ptii.: r.«c.™« 1U
id SdSA MM, thtnfor
■ upabla el (•KBillt 1 «ieUt
faalltT of tb* c*
.mi (In, «ch «
m D*t> iTitaat, «• cataM* <
■ *r« onlv capable oi
t | tend Inn coiylatal nd cc
3i,iii«db» Google
• (.ill to M llM Ct
LncorTOCt tvaillni af (Croat or plot* :
it coot of •uraMtid jmcodlot lo diriic
0 utlllu in-h™,» .eocodlae HMi
,f goacodlaf 1ft «lao
pirtlclptta dlroctly In tho |*KOdlnf p
3i,iii«db» Google
•ttilaa, tka* aftaa Mm aia*r .raff aaaiin in nwMUi wru» «
: at Ik* ataaaitr 1««1» *prriii.ri tjoicllj a
■ 4»aM aaaialaal ram « <*e>i fraaani . "J caaaaa irate aailiaat
attaa aaa at tka raaalraa lata ilwiii, Tkalr altaet ir>™i.J,. «( ■
I* miMly nlubti 1* ■--•.«. iWn am aalrm U *K lacludad In ti
►y tnntylat at taaalaU*
atarlaa, aai caaavratlaa « of tao
a aaacaalaa. Tka ka? faatac ansclataa ai«k tka clatlcal ataff
1* tka ImI at tH.it kaalain
la nnillii r,<hr.L,,.,. Clar
I a«1til It iff lav. a hlak uamr >
i Claris .1 ataff aa» oat k* f —I i: .r ir
i Clarlcal atatf *o sec >ak> on-. Ill r
f aaUlarlf* aitk aaacaaloa taala.
it aaaaaata aaarrl.au, iralalaa aaj hUmIii, tka clatlcal ataff atll
■ • •aakaaltal aataaa, aaa tkaj will eat acklaaa raaalta
traWa* aaa- aat<*ata*. ataff.
Digitzed by GOOgk
Tin gaocodlng of
a eerma tc
ait t. a nropmtp addraaa
1. aoaatleea
pnltm' centlauognl*
•a loan, an
applied far or itaatad,
■kll* la nth.r
can It 1. preform. i
atioapacllv.
1, at »ar and aa pit n
tha preparation
x ti» nmilwMi »t.t
■act. Coot
nooue geecodla* Bota-llT
linlm ch* one
.< aanual tOOl. _i M,
'-™1™ ™
•*"•■ **"""• « ■*
dU.t»l« atatf.
« jszzzstjz
... procedure, fat aaaltnlraj ««. t™t.
of eonth or aad of ywr.
Maaaal nr antcued
(encoding iooU £16 ba
ut Ulead «h.
n geocodlng 1. partnraad
retmapectlireli.
All hough s.nagaatnt *M
atirlcd a
aft — parcleelarlj cap
rarU* — ara utilliad
fot r.rro.n.ctlvn g.oc
ding, oat «
mj toued no lMlm.1
I appraleag lnalar
""" " ""•' n[oc,duc
3 j CEHSUS jmn ,;,„
•eeerel miiinn
One, c.0an, TH
i m aiiltnad to ptop.rt. aidraaaa*
Klhodl «• iH.d W -if
oalcorj In.
itotlon. to parfora th.
bled uqi nf
■•ocodlai., C.D.U. trac
captut. and aditli*. For Ibc prtii
t putpoeee, canaua
Iiicl Mjf»| tt dafla.
d to lnclud
tbe initial recording o
Ih. addraaa and
lt> uilintd HUH irm and 0a
uba.qntnt truotar of th
laa dat In vtaat-
■m aanaJ log. <"*
fnldnra, or
*'»■«« ape tee. ara »,
loaad bt ch.
dapo.itnry In.tico.ion.
Editing 1
ivol.aa tha coeearLon of
addraa.aa ud
aaalgnad oanao* tract*
igilrnt ap.,
IMad validation crlcnrl
aucb aa ealld
ll.c. of canaua tract •
SHSA eadaa
count, eodaa, ar laaHil
al 11 alt a far
— """ """■ "
aw.
«..» «««di,, i
o.rfomad
oatlmiaualr and nanoally
-Idea.... and
unto* tract! 117 ba 1
itlallj can
rdad on loan application
lor—, aaerelaal
for-., or low applies
Ion r.glit.
. Whan teotodlug 1. p.r
oread t.troapec-
tlwlr and aanually, c
nana tractt
,,<■ initial!, racocd.d o
aork .heat a.
tfhao gaacodlng la patf
n-d Or au.
>.»d an.ni, tb» Initial
v.cordlog of
<ialg»d flUul tract.
la uda an
coaputer Hie for tboaa
*Mr**M* that
clh b* ualgnad bj autoaatad aaana
Tha* a *ddr*a*a* .hick
out b*
aaalgnad canaua tract a
h. .uto.it.
■nana auac ba faocodad
imaallT. aad
Eba Initial iHliaau
1. tanlc.ll. t«ordad o. . «rt .ba.
3i,iii«db» Google
ubaa Haul |HHAi| aatMa in hh4, tka t»t> prcklw ihk
ttorata, lanln* ih nUMln u' (Mel'lc
atfUloatlr mniui
Digitzed by GOOgk
a i«oc«linx. miiioui inch i lam Ilitiog, 1
I aUelf :.!-:».■ • COpy o
luEltucloa -Met. ».iJl, «1|> c-
toutvd M«|M*! BHEvr 111*. If, A
3i,iii«db» Google
cxocodhe iccuitcT uulti rw na
MTMM, Ml DBM. 1MB
raictco nnu
Thl. ch.pt
,b. t^odle, —r«
(BBlyBin
to t
■ Kifialo,
■on !)!*■□. .ad Chicago 3R
M. Th... MU Itio
that
■MKOdlBt Kcurtef It . problo. M ■
proilut.ly 20 mill-
of Ih.
M
lutloB. In
MM Man shSa. .« Hal
ln.ccuTicot.acD.ln. 1
■e-r. llk*lr
to Kcir in Ul
SMSU (1... Chicago), tn
■a li>atb.rn <i.... "o
■u Hl.it.). Th«
* IMln ••phulii 0PM
OdlBI
nhou.
d low up
dTh. .ppro.lB.t.1, 10 •»
COUC Of llf«ttg<7 In.
ItutlBBB
tM
™™°"
IhWM
lol.tr «* f.ll r— It. of
tho toecodlnc .eeur.cr
-at.
«.
r.i.m.d I
r.ll«o.-1
Inth.fallD.tni ••cclco.
c-ccrof Dl.do.ur. S
*""*
(Ml
N fro. Hm
tfcrooSrltUn In pi.nnotna
•ot uck of ih. thr*
• Mil
MM
■d. (Ml P
■B.ne.tlan 1. IB tht.n p.
ti ih. COBpo.Itlon o
Ihs .tudr
""
., p»»«.tl.m of mill, •■« di.o
-"«"*»*
3.1.
CEOCODIHC
ACCDIACT It TIE IDTTALO 91
«MT-nt
dt.C4lt.rr lB.tlt.Jtl0>.
MMRaati
r.n.r.I or ititl ..(i.l.r
an. In th. luff Bio >EB
oi.rd Mnto-
I»ll
■ n SC.Il.C
cnl AT.. SKSlO Airln. 1»77. tttbt of thin. In.
It.tlW
mm
T.qulnd t
pnp.rn Ih.ir dl.tlo.ur.
II lift und.1 tatal
.lion C ,
•nd
A lnntltuc
wnn i«.i.Mt«,„p
r.ili.lt dl.Uo.ur. .t
tmmu
lt«k
HMdM
Of th. Ir. lort ■(•<• B.
kin. E.p.rto.nf. Sop.
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tut ton. in th. 9«c
odlne o( prop.rty .ddr....* to can
« tract*, ex to
sadu
. it do., mt d.rin
• or diieuu th. ■KMdi AC tool*
to be IHd to
p.rfo
n th. o.ocodlno.
rn. Ulului ?covld«! b, th, Bu.
: etcuu
l.-d
JHC (1) Hit..! «• n.itlar intxidri fiat .ppiopcUt
■ for oeocodlnu
ajkajt
t. f.«tl:«i»rB, ™ ^tocaSln, ••
hod. or tool, m
provide at .11 by th. 1
•d*nl 9DVBI™=.t. Cnna.an.Mly,
th. depoeltory
in.t
tut ion. Mv, M [send to Mly =r. Mthod, .no tool
available ins
cow
rcLL .oUrM. .inn
. It xsuld ft. prohibit ivaly oo.tly
for , depoaltory
lnat
tutlon to d.nl.00 i
t* eon. Heat d.po.lt°cy inatieuti
on. either parch...
rci.llr MHin ■
Mx... coding ,uld. dlr«torl.. o
M ■ unit.
BUT.
j to a.ocod. toalr
lo*ne. Ia.ni oth« 9*ocodlne
■una mch u nap..4
Th. .
ccuracy with wnlch
encoding 1. p.f fora.d 1. . (unet
of th. amiable
"*■
ud th. .kill «d
— "",' •"«—".—.
m~.tla.tlon. and
.•^ 1. ..»__«»_ «
M^™,«,
tor .napl., th»t IS pu
mi of th. initlewlanj In th. aiicoo ntu 11...,
9 of
It In.t itation. ) ac
hl.vaj unacceptable Kturic, Unli nels. 80 f«iM.
Digitzed by GOOgk
* nlaa rallad aolal* a
»c« not adaqnat* tat g*(Kodino ThjM of tba a!
,, b, tfaaaaalru.
dlacuaa tha jaocodliig preblaai ion filly in ■ g«*putca iq»R antit i«.i
'•lii Uh O* lnlDoKlcn frc« which w KC^iUili ]ri-Mui(. (iBC* laaula-
ti-ap C aoa» not dlaeoaa aathoda of gvocodina s provldaa 04 guidanoa for
it — anlitlQB c b* rwviaad to pnrvlda yuida&ca fi
3i,iii«db» Google
Ion 101.2 Of MguUtlai C Anflnaa aiyllctbl* tai
i trjt Chi aonqtqm leu J.t. it.ii.1 ba lti^»
■rtyH including 4
3i,iii«db» Google
n by tha «nu. CD* prvralaiit
■aka as* Lona-tan (a.c.f M yaar]
typlaalLy pay* tha Lnttraat on tJia 1<
Initially, audi loaf
only p>naa lonlvlaa. taaoorary fln—plaa.
Jtandtng prlaalpal 1
it ba aaoa prlaarlly t
3i,iii«db» Google
pi ApproprlAtti loua ud lou u
loui In tba Hml of » 106. M*. 000 ud uvla luni for construction by a
in tba wait of »jo,ss7.ooo, >■■ Lena ain laclao.il la u» Mii u>
Hpsni glifuid by th* BtaU of Q
tho nfinuiclag «■ not provlrt*
fintiicad loui Mt th. nauUlU purpca* of Mgulmtlon
■olutloni To DDUntsr th* prablsB of Including
3i,iii«db» Google
■ D >• □
• □ - D
1 « >« nUdltj at IU
* gl*«h to laalajlgj
(MllT Mlll|ll i
Digitzed by GOOgle
. lionlficint prsbliB In tha iBtazpratatltm of ialouUm *
3i,iii«db» Google
>ir»iwi -°"=- in th. ■
and ***** — our analyals to tna
•ad -M-mia- u» MUrttofl ggl-ni si bf attain] * nav solo-, -ad dropolDg th*
colun for nul Ra-ldantl-1 tinoiji loam.. Iba jl-rh. of tha laport 1* nffxa-
tha Hunt ona thousand dollar- ■* addition, tha coliau toe Total n-ii.i-.iti.
aad th. I oa. .:.... .;-.-, iblllt- tt pn-td*-. Honvu, only - 1-1 s-r-aaca-a
■ i—l Iiiii 1* iBtn-o-aUr aeaUcakt*.
■a plaead upon da-oaltocy li
3i,iii«db» Google
IToalan 1 - ca»rtlntla» Irani Coapiliticn anon on ansa durlny tl
it llaillflaut cs»pl.l»ti.,
net mijiMint uian wra ttw w>« t olanlf lout btsbIoh . a caul at
,3S oannua tract! In tha ri^li. A coaclata dlncuanlan and unlyaln of
A*h typo* at anon la arnaantad In tfa* aaananlon roport, 'Mcnncr of
3i,iii«db» Google
' aidad in tha a*plcryaart ■
ccaptabla limlta
Itaa kay *1— n* In ufwcaitnc Bathed* najairaai a revlaj
•waff tba val 1 dity and acciuacy of OH leu inCaa
Una, on* aj.it Da able to Identity toe Individual 1
a particular dutlaiun atatanant. similarly, tha nda:
obtained data n aalactad emus tiaot Um foe uaa Id
lllaTaWl dlKlcultr la Unto Mill to Identic, W
Digitzed by GOOgk
an ilmflf r»t»in Ch. auk papit. una in ccMplHoj th*
3i,iii«db» Google
i umliC mma. muuibjtt.mii g
ritli public UU«, mllUilUty.
KaqnUtlDcl Ci HacjlllatJoi C noilina lifalUcy Institution, u ul.
"approprlata affozta- annually Co notify tholr dapoaKora of tha availability
o( aortgaa* loan 4ata. Ik* fali™iii7 aattyii. *» juiggccatad but not nqulnd
by In* raonlatioor 1) lnaartlnv a natlc.-* in dccjoiitor IIIMIIU, 1) potting
• ootlca In tin lobby tar at laut oaa ■snth, or Jl punllahlng • noetic*
In ■ loot 1 navapapar of gonccral circulation, ay tha m* of tb< con] unction
"ox," t.lia tabulation lajUu that una of any on* of tha cctxnca ■atboda .ill
3i,iii«db» Google
analfala of tha not I
not prCTwirta Hidaapraad &
i1 ata fanta adaqoataly and aFprc*»:l>tal.T
hi dapoaitata, but 4oaa not ca*fh ]
■auradLy inCDcwd by a jiot
3i,iii«db» Google
ipac Ify ■ -^ v. I I -r-.-.i to ba u
objactiv* of eoaylnq tl
■a niygut KaguUtlon c b* *odlf lad to apKlfy tin
.caa of aach dapoaltory institution, Tha Ddtlca ihould
kBQWladoaabla Kid raapoiwlbla for ■!■■■! Inj public inqulrlaa.
Haanlatl™ Ci taaulaCico C caqidraa tl
nrndactlaa chazga. The aaaa n
3i,iii«db» Google
•ppltcaBla BBS*, .leapt Uut, « tha option o< tha dapoaltoty ln.tJ.Cutl™
tha cumit nfilUttan potentially daprivaa tha ootlylng public of naaonaUa
accaaa. In tha San Dlago USA, for aiiaapl*, thara ara branchaa of Dapoaitorr
Jalutlnai To provida aor* caava&laiit puijllc ai
ability at • aln^l* branch o(I
3 Coprliig Prnhlaa and Solution
Raqulatlop Ci Bafulatlon C racpilraa
i Ita acrtgaga loan dlacloaura atataaaai
for InopactloD or copying." It furthar
3i,iii«db» Google
it tha 4*co«ltarr la«tl*vtlQMh pn— ihlM lBUrpnAttLona
1 coprlmj cbirgu tor till •
3i,iii«db» Google
CBWumK on cnfjuam niKMttug twiumi - prow w
ln# analyala of uaaaa is outaida th* aeap* of thia nport. ** t"
a&alyala and augqaatiad rev Laic
ten eh* pr°po»d auggaatlona, chat dartva frtai ehla gnlu, ahould not
« adaftad. ■■ tlaiild th* tan* i
« antajltal ■-..£« aaCB fiaoal y*ar.,r." Finally, [tabulation C
3i,iii«db» Google
If th> Board datim
no th. it
Lata and ngulatlou
raqulraaanta aub.ta
tlally MU
toti™«
Ucwd ur
*'"" »-*•*•»•
«-— ™
*•'
tpDlta _ Li=k
at itmdir
„
nut. .nd
contwiu,
•U<wt. ™ in>l
.d f ™ f«
liy-a.rt
T^<bp«
• Lillar in roraat B
th. ould.
ToraHHlA - 1. to
rn* cnt.nt. at rs.
•n «l«o
imil.r ta
filiation In Coin
<* typ.. o
K
auu^n
thod. oH
fauna th. fon-t
"d™t"
*
rji
*— "»
frc.th.ooid.lln..
mm
,:,
n-dln,.
• alraady following tl
3i,iii«db» Google
un: tha net and —ami ntlon c tvovid)a
that -..eh dro.i
MY Wirntlon .,
all ™F:l. .tn. najfal and uul
dollar M^t of
tortqign Imti .durir.g aach fiac»l yMt." Till! WaOl
tint • ^poaltorv
Institution -to., f
Lt*al yaa. and. on ■■,■■ 11 .,..,
»TH "" "*""
1978 Convaraaly,
«. at.t_n. fa tto parlod fa* 1.
cdociir^i^
(,r.pa» it. -(i.c.1 ,^ H* di.clo-
HI lUuwt for th. oaricd !!..«,
197B to Dacaal 11, l»J«. toon.
in. Uiclonn at
l""» «« all dapoaltor, lutitutlon. in an EISA on
osw wiy ■ tao-yanr spin far * ,i
an fi.e.1 y«*i ThL diffaranca In
tha npoitlnfu
od. ult> It ispoaa
ibl. to rt.fi.-, or to co.nl ta and Intnr-
pr.t etc ra.ultan
di.clo.ur. at.t™
t. on tha bull Of their Wlln, nattama
for * «WI tina
parted, for Hutu
X, In tha uanpU abovn Ma 1978 lineal
yean- of Ha t-o
Inatltutlona only c
aiaiae of then nontnn In can Hdb.
January. Mwn
■MM and Jiptn a
■oriod Of !l t-ontha. Conptling thaa.
tvo diaclo.ur. .t.
ta»anta mth othara
aodinc In July Saotannar, ate., nalota
littla >«•■ Sac
aggravation
Haiti aaaa two nu of landing. .«*
fluctuation and
.a.ral .!,m™r»cl:ic
dianoaa during thii nariod. Thia problan
"-M *■-«"—
by fBdnrttniiig th
»portlbg yaat.
Mrtn.l
Ti, ^pmnW-ly a,
.. fourth Of tha «U navlnn. a»d loan
• UKlitloni hid
lMl ynar =lom™
othar than Dacac-ar 31.* of th.
95? with cloaura.
othar than Dacaabar
11. aoaa J60 had cloaura. on Juna 30
vi .a. IB had
l«mi on saatant*
30. According to tha radaral Dapgalt
l>«n<R Corpori
Ion. all or naarly
11 of tha bank, undar th.lr iuxladiction
h»a fl.c.l ya.r
lO.™ - Daca*«
31.
solution, ■
auggaat that Moul
tlon C and th. Act na raviaad to HAfaliM
■unnla.lon on 4 e
Undjuc v— r buU.
Ihla rnvlaion -ill graatly tacilitae.
- ■
3i,iii«db» Google
a *nd Interpretation
n ■Bltl-laally dwllinga *r. nibdivl
3i,iii«db» Google
protalen, and luiits loaotlflad during tha thraa ph..ei of our ituS
poiitoty InBtltutiana to gain an tnalght into tha raporting probla*
c ita langthy and coaplu.) Thua, "Mia ragulatlona
alght appaar te ba dafinltlla, thay do not, by thauilm, proWd. an ada-
quata baala foe an opantlonal procadura.
TO laprova uadaratanding of and adharanoa to tha taaulatloni, na a097a.11
tha davalopnant of lupplanantary guidalioai which would clarify tha ragula-
tlona, amphaalia potantlal iihi of mliunda ratandlng . and provtda atap-by-
(tap Inatructiona for praparatlon of tha diaelooor. atataaaflt. Tha ouldallaai
;■ diraetly talatad te
locodlng toelm - typaa, availability, and ti
3i,iii«db» Google
tha ioi_i™Ij*j b. 1
h rlqura 2.1) to proriil* an owrt at
■ lagnlatlcna that an salt llfcaly ti
a of awh a chac*-of r llac mold go far la ndaeina: u» typaa of axrora
found to bt Beat praralant In tha Inatitutlona m innatl^aead fcrluv tl
3i,iii«db» Google
or pucLosuii smotatt
tan torn °i unl*
□ D
□ D
a
a
□
a
D
a
D
a
a
a
hi* Google
iKlird Hatrapolltui xutl*tlc*I AIH* -
■ inc., ■juulr*l> Of Ho— M«t9*v* 01*
"bl*lril( Of «H NOItptf* Dl.clo.ur. I
3i,iii«db» Google
HOME MORTGAGE DISCLOSURE
sects
Digitzed by GOOgk
REGULATION C
t Cull tiKii year thill be
ir ending prior to
July 1, 1916" 1st lh* putpoKi of n
U mortpfe particioaiisn o( ;bti Put.
r fiannwed by ibt Federal
n Morrtaf* Corporation, i*
maul National Monpfe Attodaiim, or tht
Funwi Home Adeiunairuion). or {Hi} I loan
rude primarily for butiocu or eocuumcr purpotc*
(other than to purehlia. repair rehaWiUin or (1) ]>„, ra M Inclndt^. (1) Each d.potiiory
remold midenrial real property) hut in a
tun with which • flnt Ilea on retidtalio
iiudtution ihi
ill atfretate, wparattly
[or etch
opotilan ualiKical im 1
SMSA) in
a hooM office or branch oAct. id
nwniie* loan
data for each Steal year
berin.iini
with in Ian (u
1976, with th
■ exception at mortpn
icribed in mbicctign (4) of ihit para;r
iih. Men.
ulaiing to Htideniial a:
il property
located within
the relevant SMSA (i.e..
ihi SMSA
where a home
or branch office ii locait
dlihallb*
Kfttjattd [to
m nortBaat Iran data
tclating lo
tniormial rani property located outside tht rrle-
Tjnt SMSA li
nd ihall be ilcmilcd by
the ctnaa
SECTION M 3 J— EXEMPTIONS erty murine the ntiduidal motipi* loan (or. in
the com of home improvemtnl Irani, the property
nprovtd) n located rrtcepi at provided in
h compilalion of data lubKCtioo 13) at thii paraeraph) leeording to the
,db» Google
REGULATION C
FHA. FtnHA, or VA
on awlii-bmir d»effiDas. «bdi<id«l at «
lean (A) oriftraual ud (B) purdmad by '
posiiory imtituooo, durini thai flsol y*ar,
(iii) mil iiiiitiii'iil moniap too*, as*
multi-fjmilj dwdlinft,
to Ud (iij). wbdividtd as to toot* loans (A)
naiad and (B) ,-■— W— I by lb* depository
b* tmorond) a located, in I iau of — — tract*. »
UK um that Kb 4am ram* ns
CliUI Bscal Tan endiac prior to July I.
IfTftar
fri> a part of a flscal yeat J thai part csds aa
Job* 30. int. pnvidad thai i sortaaaa ton
disclosure nann lot that pact of th* bud
Tear a mad* ivailibta br th* flap Miter] iaarka>
liea by September JO. 197S. and a separata osort-
t far too lamliaoi
days of tba and of (hat natal rttr. or
(iii) raada filial real property located in aa
ana of a currently denned nUnoi 5 MSA that
a am tcacied so ihi mito (= a ponioo of tbo-
ddhMd SMSA'. or other-is*} in th* Mria "WTO
mu rtt -firmly dwcQiriat, nude to aoy borrower »ho
did not, at thi i™ of iha loan transaction, iniaod
to mid* u hii principal dwaUinf in th* jraptny
■curiaf Hi* residential tnon*a*i loan (or, in tbc
be imerond).
subdivided ai to thOM
loani (A)
originated and
(B) purchased by At
depository
kbtirurion. during dui fiscal ynr.
(i| through (v) includi
text! occupant!
and non-occupanti of thi
Morijai* loon
data relating to rciidtctial real
property local*
SMSA lor
retout SMSA'
■ in ih< cas* of a depository ™ti-
nuion «iA hum* or branch ornce* in
on* SMSA) shall ilao be itemized ac
clessincationi (i
) Ihreufh (v) set forth
■on of thai data by ctnst
United Sulci
Postal Servic* ZIP eo,
C) Mortem
midantial
real property located rithin lb* reiev
ant SMSA
o be compiled ai
principal arnouno of Ioua orijiaand by th* at
tuikm to th* axttru of its interest, wbert th* k
ii mad* jointly at cooperatively, and unpaid pr
cipal balances of loans purchased by the dept
pt that, io th* taw of pur-
:Lude die unpaid Anaac*
mnr loam origicuMd or
(8) a loan originated or p
depository institution litm* as tr
other fiduciary capacity.
hi* Google
REGULATION C
d. No depmiwry
a mortjepe iota
bn or boundariaa iutU after the ZIP code for a
.„ a SUJ(0 of ton Pan. Una « bo™ paititauar lou it recorded.
intprovaaer* leant Hint lout dm k ho* d» (+) Nothiai rnnninart in ihit paraaraph h in.
oiJUd *t bora* iopra>«mw( ton for tfw pur- «™«d » "«*»* *• «*• <•' «ap. flfottwfca,
pOMi ol Stic* law, provided thai no loana wired eompuur program, or the like dial tun awn
by BM U*Bt oo retidanuai ml property thai) b* ™«ani deflnitiaiii of the applicable SMSA am
iaduded u boom tapreetauat knot la tho man- *m "« ip«ilM io tuhttcUoo (I) of tha r*n.
jift loon diiclotun trtitmtm lad re re react a *"FB. providnd '«« every monfate lo" nriuat
audi in lb* ditcionirt mem ifl rat Stain law to retidenlial ml property within the applicable
defailiea erf bom I tiinaintni loan that a being *"" of tht relavanc SMSA u jptctAed in ubuc-
i«j;_h; or ooq (I) of ibii parapaph «
(B) omit, at ita option. 107 nwmip loan thai
ni (I) both originated and tUhar >oU or pud in
full duhni wch Steal year, or R) both purcbutd
and either MM or paid in full during ttieh steal
11 SMSA u nun lestady defined ihnD
oeludad in tho data 10 ba itamitad by centtu
a or ZIP coda 11 taquirtd by paragraph (i>
bit taction. I( tueb uadud ir-iiiom an uti-
(c) Appi cable preeaeesdoa. For th* purpota of
compiling mongage loan data described In para-
graph la) of this tccttoo, a dtpoailory inttitudoa
nay pretume luolest in recordi relating to that
rapect » any mortgage kua orijioattd prior to
line IS. 1974. or purchawd at any time, that
Iha bonwar intended, at tba nam of id* lota
trantacttoa. to reside at hii principal dwelling la
|i. it men propciry i>
203JUMD of data Pan). DM II
tba rakvaol SfclSA shall ba choia u denned by ~ ^'^'iai dwe'lling't
iba Omce of Manaaantul aad Budget of tha a«« ro ta« familial.
United States Govtnuntu and ia affact on lun*
21. I97S, or iba aril day of raa Steal year to
which lit* monctfe loaa cUacbau
rttatet. whichever is tht later data.
tZ} Applicable eenma tract raimb*
dariei shall ba thou appearing or
tmt mapi in the lariat "1970 Carati . ._. . .
lion and Houaina; CENSUS TRACTS Final »J- public by tba folKwinp dataa mortfin lean do-
pons. PHC1I) Sanaa' prcpand by tht Bureau of ctoauia liutmeoti reqiuiad 10 be compiled por-
iho Cemuj, Uaktd Shtita Dtptrtanaot of Com- Bant to taction 103 4 of thii Parr.
maiea. If the rairabar loatf would ba duaakuad (Q SaptembaT W. I97S. In tho cat* of a Bat,
io the montatt Iota dteieaun Wiamant far tht down Matement relatini to a full Htcal year
.-alevaaa SMSA. tbt county, dry. or town that endine prior to Iidy I. IST4, eutpt at provided
uniqudy idaoiUUi in* etotua tnel iball ba Laaoti- „, mbtaaion R> of tbia pafttraph.
Had in thai ditclotura tiaumtnt. (jij wiihin alntty dayt of tht end of tht reto-
(3) An applicabla ZIP coda ihall be thai for vant Steal year in tba cau of a dlaelotun itata-
At ana in which Iha principal rttjuantUl real meat thai ftlatat to a full St:al year tadinj tubaa-
property KCJrini the mJdantial monpfa loan qunt to June 10, [976; tad
A-S
,d by Google
REGULATION C
ton ii
ninety dtyi of lb* date a depnai-
* of the initiil diaclown iiatanwat required met or ZIP ■
a 103.3(b) of (fab Pin. not SMSAi otner then ih*
exemption it Slid particular branch office ii I
r 30. 197*. punuaat to taction aijrtfniod Uii bum Oh
203JIWO) of tbii Put, ■ Staie-chantred depoii- with reipeet to "eh of
my iuBiiutioo ■abject 10 <b* montae* disdown SMSA'i (U, the column «
Ijwi of 1 Sou oc wMiviuon thereof bein* coo- "» appendix to tbk Pert) ar
lidcrad in [be application thail aet be required (2) Any depository iota
10 eompil* iad met* eveilabl* 10 lb* public a offices, (bom* and branch) ar
mortfBfi loan disclosure sontmoni relatine; Da a ii no jeneral public accent
full Steal year ending prior 10 July 1, 1976. »hil* mon|a*e loan diadoaun Bat
isc apolieaiioo ii pendinf More iht Board. It lb* compiled pursuant to sectioi
iiiOD a not iraniad by tb* dates specified in p
0 wall
(i)
.lilabletb
n data) ■
rd made available lor a period of Bvi yean ttiec and IhaJl d
t dose of die Am focal year during which that place within every other Si
icIosum uantmeat la required to bt maintained branch office, at which dtaii
id made available. be nude available the emin
|bl Omen at which dlacloaar* ttaierenU to be cloture statement except for
■d* available. (I) Except ai provided in
:tion (I) of this parajraph. a
ipecifled in paragraph (a] o( this sectic
home or branch office*, ai follows:
tht entire motivate loaa disclosure uatrmenl
b* made available at the home office and at
at one branch office {if there ia such a br
office) within that SMS A; and
(ii) in tb* can of depository imtituiions
have hone and branch officii is mora than
ii SMI
(U) it shall promptly fui
e requeuing We informal
ired norrjaje loan ditcloai
{ no more ihan a reajenab
1 depository inUirul
1c mortgage loan data) ihali ba made avail-
: the ham* office aad IS) the entire mortgage
isdosur* statement shall abo ba mad* avail-
r\
3i,iii«db» Google
REGULATION C
(■I A vtolaiioa of iha Act or [hit Pan ii Mb-
timinii iti t-iiHthh jaet to met™ aa |«iw««f in tasiion »J of 4a
t itMiynltil puat of a ft) As xnt in coraptUnf or dudOMBf raqukad
it il nquind pwwul » naKtfaaa k^ oau a>M not ba daamad » ba a
panriph <»> of to* tnfea » anka a roctpaa Vivian of th* Aa or Mi Pin if A* «nr M*
plan It DonsUr opaa to *■ pwMis for bwioaw.
" * H"!!2£J?** H*£ "P™*™0 SECTIOK :OJ.T-EFFECr.VE DATE
»—■■"— avaiaMa. it may impoH a i*a*maMi
cAaij* fat tha eaal of rapnxkictiaa of iht data. Thii Pan shall ba rfauivi on J una 21, 1)71
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REGULATION C SUPPLEMENT
SUPPLEMENT TO PART 103 Federal Rum Dutriet in which the, applicant
it liuiaud. A period of Ome will b. allowed from
toe due at such publication tor th* Board ■
PROCEDURES FOR AN APPLICATION recein written comment! [mm ituereited perm
EXEMPTION PURSUANT TO with npn uttm application. Should muitipla
M (aXJ) OF SECTION 203.J —--=— *■ ■ - -
in La diacretion. (1) csnialidaat the notice sf
raceipt of >a inch ippHciiwni la on Ft***
_ Rrtiiur notice. Ud (1) dnpMM with pubheauce
■ application lo the B oar J punuant *' ch* ""tice of appticatiooi received after puMica.
» the ttrmi of tail Supplement ud the Botra"> "un a( the notice al in ippiieition relaxing id Oh
Ruin of Procedure (II CFR IS!) lor i dtttraina- Iaw« of the lame Sum or municipality,
don that, uodtr th* n»i of that Sue* or rnunici- ^ Eiempttoe free* w^lwumm. If th* Board
paiity,' a Stale-chartered depoiitory inttiimion ii determine! on the bun of the information before
■ubjeci [a nquiiwnuB wbituuiiCv liaiQir to ■' **< under (he liwi of a State or municipality
thou imooied by Regulation C (II CFR :0J) and Mm* or alt Stata-charmd depoiitory imtinuiodfi)
that there ia adequate proviiioa for enforcement *'■ «*ject to nquinmenu tuacuntinlly Mauler
of loch requirement!. » [ho*e impend by thii Regulation, and thai than
. Th* application. ■> "liquate proviiioa for enforcenwat of neb
tr. ihatl he eccora- rrquiremeno. the Board will exempt UtOM Sara.
r? (I) a copy of Hie full tea o( the im of ehamred depoiitory inatiiuiiom in that Stan or
the State or municipality which are claimed by the municipality that an luhjeet CO audi requinmegn
applicant to impoe* requirement., lubiunoally [:om ** requirementa nf the Act and the Board'i
timiier (o thox impoaed by tha Regulation: Q) a regulation! In the following manner: [I) Notice
toaRient of nuoai to fupporr the da in that 0| !ht exemption will bt pgoluhed ia the F«Jml
applicable requirement! of the lav., of tha State Arjoirr and the Board will furoiih ■ copy af tuck
or municipality art lubttutially limilar to alt re- notice to the applicant, ia each State or municipal
impottd under thi> Regulation iaclud- ■uthoriry tnponiihl* for admiouiraiivi mfotce-
lanatign of reaaona aa to why any tnrnt of the laws of the Stale or nuaieipeuDv, to
are not lifntflcint; (3) i copy of tha *■ reiuluoiy autheritit* ipectttd ia aeenoa
full mi of the >wi of the State or ubdmnoi M*») of the An. and to each interested penes
diereofwhichprovidcforenforcenMOtof theStat* wh0 b" participated ia the proceeding. (3) The
liwi referred to in item (II of thii paragraph; Sj,,d "ill inlom tba appropriate official ot toy
tad (4) an undertakine. to intsrra the Board SU!* or tnunietpaliry in which Stale-chartered
within 30 dayi of the ocsurrinc* of any change in depotitory iutitutloni that have received in n-
ih« applicable law or rcjulaiioni o( the State or "fption an located of any wbMquant aaend>
municipality. nwnti of the Act (including the implementing
(e) PuhNc BMlce of fUing. in coonectioa with Froviateni of thii Pin and publiihefl interprttj-
uly application which hu Been Bled in accord- ,iJn) °' ,n* Board) which might all for aaieod-
aace with the requirements of paraenphi (a) and "'■"" ol ,ft* ltw. regulation! or ofHcial iuarpRra-
(b). notice of weh Aung will be publiihed by the dsl" ot ln* Suu or municipality.
Board in th* Ftdfat Rrjltur. and a copy of nica '*' ""vcadeei of eieiapuoe. (I) Th* Boatd
application will be made availiBte for eiaraiaation rncrtci th* right to revoke any exen-.pfion if it
by interested pmom during Nuipcu hourt at the " "f iimt drterminei that the law) of a Sat
Board and at the Federal Reserve Bank of each or munieipaUry do not in fan impot* raqiiineaaati
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STATUTORY APPENDIX
REGULATION C
U bt puMithtd by At laud in tht F«UrJ
id a copy of wch nonce dull alto bt
a At appropriate officii! of tht San
in union 305(b) of ih* A
STATUTORY AfPCiDK
JOC MainttBUo* o( Rtcordt ud Public
307. RtMueh ud Improved Methodi.
• Ml. Short Tide
Toil Lilt [dt bt clttd u tht "He™ MoKfaga
a of 1975."
reiattd montage l™" » dttermiatd by tbt Bout
(3> Ibt Itrm -Board" menu tht Board of Go*,
imon of lb* Ftdtnl Kcitrvt Syaua; ud
(*] tbt tetra -Seem»r>- mtui the Secretary of
I M4. MtlntaiKi *t Rmrth »d PuMk D*>
(tXI) E
standard metropolitan statistical irca. tl defined
by the Office of MutftnvtiiL and Budget shall
compile ind m '
it floancinj to qualillad refutation! of the Board, to tb* public for iruptc-
ttniu aad condition! don and copying at the homa aflce. and at at [oat
it title it to providt iha ont branch office within ticb ttandard rnttroBsii-
with sufficient information to eaablt Aero to lion haa an office the ni
dtttnnint weather depository institution! are fill- atrunint of mortgage <oom which wen (A) onfi-
ing [heir obligations to serve tht homing needs of nattd. or (B) purchated by ihit iniiitutioa during
tht commuoiiin ud neighborhoods in which tbty each Bk=I year (beginning with tbt laat lull bacal
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■ follaoUq la u account of tha amta uiscUtnl -Itb CHa af
■ sufl ■■rtiir to axaln tfia UUonli Fall Landing ■jrati f
tiMCaly, nporta mara obtai&ad ftcm a.
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A VpltlHd Eh* nitun of IlH
I Unding information" 'ii jiroaliMntlr
m daati. xft*r browing and bi
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in 'loan produd
-labl* for lnsp*cti£B V
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r ijihIIjki Mpon of n™a n
9^> Loan Data." Sulda it, ou tin tan* tabla, nu • (all -HI. eoapjti
lilting >t«h UK 1476 r.port. I cold bin I n.edtd the 1971 data. H* !
nUlabla In ■id-UTt. I lookad axound and found .„ unuukvl black
not ptntitttd -to copy It. I told Ma that ttan hri no regulation pre*
in? ttMlr ecp/lr.g the nport — that it 4* At tha option of ; '-,-■ landing
tiaa- I than diacloaod tha nntua of tha study and aakad hi* if ha ai
Ba uXad nlDii buainaaa cud, Hid ha'd hU 1 f» phtjna Ml
■Sat ha could da. T-anty liiwUi UtK ha Hid that 1C I cou]
.d hole aa. I aaJiad II ttiay h
i a log- Ha said that although thay pcatad tha raqoiiw
•fsita, I in* tha flnt panon **u to tan nqulnd tl
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HKTHODS OF THE FDEUL IJEj"
HETHOV OF THE FEDERAL HOC
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Cr-plctcn«»i FliuUnja
Halted, foe Iaprovln( Coafllanca . . . .
Simuti^iif Eot laprovaaanta la ftafulatii
4.3,1 5u|>pl.™aMatj CuU*llnM
Hoaa Haiti*!* Dlacloaura Ace Data
LIST OF TABLES AMD FICUM5
EHOA Examination Quail loo« aod Inatruct
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Tlit. rapon ■■. rtapand BJ m luoctttaa. Inc. , RcUaa, Tlrjlmln.
fST tba Tadaral Hum Loan Sink turd (HUM) aid cha Tadaral O.po.lt IHUIU
.[«Jj 1. to .»lr» ttw Row Morten t>i>cl~un ,c, ,., j^l.r i = r. C In
compiling ibe wiraa.e 1«> HlilH mtWM id.mUr tn« nlatl**
(tuw aada BJ octat Intel, and to pcapara a aatlas of roport addiaaaln,
Haltopolltaa Stattitical Aihi - San 0!s|o. California; luflalo. *** lock;
tad CtilcJO, Ulloola. Tha ItadT la dlaldad late foot Bhaaan.
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f fepLclot C. M.c
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tha altart naadad In aoa>llanca iiiiliitlin. to Ida ml (7 ■"■! cornet nccurae/
• Waulrln* Jipo.iior- inirllurioni to ulntiln a llatlni of
of luch a ll.clng .1 ao-.t IniriLurlnn. la a ilinlflciac Till II cent rl but lnj to
at tna egatanta n( tii. dlaclaaar* atataaaat dortoi napUaoca aulnatlooa.
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laalctaa in a.p.1
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Jta? (a). • UacuaaleB o* tha cost, aaaodatad with lariaaaiitatloa at
-Utility of tha Heaa nontaga Blseloaan Ml.** Tfcasa (Indian an ptasauad
la Earaa of aa astlaata a£ tha oinabar of paraOB yaart raqulnd id asaaaa tha
accuracy a( dladoaura •tataaaata daring coapllaoca aualBatloaa*
l.* iecuutorV riquimheIitS
laiulsclsn C nhich waa proaail|atad ky tha loard of Gsrsraara si tha
Fadacal Raaar«a MM apaclflaa tha raqalmaati appllcahla ta dayssltsry
lmiuurliiii aubjact ts (ha Act. A cap? e( lafulatlsa C la lacladad la
tin. ntett aa Ayawdli a.
<1) AST tMtHO LMttMIM "hat t... total aaaata aa si tha laat
day sf tea lataat Cull lacal yaat of 310.000,000 oc laaa
(1) Aaj daysman in.nt.iior that haa aalthar a hsaa offlsa asi
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ar eraaraaa that am aara
aa 11, ltTa on laforaaclna.
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rtfilnd to 4Hl«Ht* • cDnnnlliU plK> (oi pubilc alien 01 M '""W pBflll
■cinal b«4ii br tha CaaTtrollvr sf t»a Cirikt
«*■ liwurtd bj th« Ted*iil btpoalt Ihhiki Corf*
f tha r*d«r*l [Jepoal.t TB*a»DC« Corporation
a Mb) o( (B* low u>ki Lata Act e( nil, Sariioi
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gf .uforcin. ecaplluct Htm uv it4»l»H« si tha Act, u>7 of Eha m.Kl.t
•hill Bt b. daaaad to m ■ violative st tba Act at em* rm if tba arte*
*nd c«.p«ctl..ly, tha atthoda entrant lr '■!■■.. ■.!■-■.: by tha Fadatal Dasoilc
ilBdlafa th. tjp.i of ttoalaaa balat anesaattraa with Iba Btaauatlan
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il Deposit Imvtibm Cer*0r*tl« ti
■a iiro.i.tno. «l th* foll<j»lnt *l|)it lam as4
aft Dlaeloaur* Act (FAS Mpilatlon C3
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»ia csaalUnu amliattlan alas luddii IhtH additional aucjaela
IE li laaortant to raallia Chat tha utaaluatlan procaduraa for aaiaaalng
Froa (ha lucriMlDI lailalatlva aaathaala en cenamar ind anrldlacrialnatorr
lava rafulatlDOJ, and arocaduiaa at the ftoaalyn Training Cantar Locatad aaar
Uaahlngton. D.C. Onca tht training la CD*a>lataa, tha aualaara conduct
■acWl f« MMBtSB co^Il.oca. lha agancjr alas fcaa te)lSBal «a*laa
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(o parfon a Voapl lanca" tu.lnaclas at laaat aoca mi) II aouha far
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bom ■Diim Jl.clwut. d.ta hi. t«> cowil.j aaj diicloaaJ Cornell? to
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to wilf. (hat th. iOorti Ad tha data lscludaj ■>. tM dllllHIH t*aett
«• -pprotpri.t.. Much laaa aaahaal* HU (iv.n to ptinlBiu d..lEr.d lo
••■■■• tM Mul coat.ac and MM| d( cli* J.i. Included Id Jl.clD.u™
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,-l.<- tb. ■■*■» tlM IlHIStlOM faelM oxaalMra. th. iMlutlH MM
ba MM*) 10 pt.p.r. .0 iouiii tttNM .M tut .hh tlat ikadj w
b. .,.« ta dM. CM*. « ■«-»».
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v.r«. himnr, prortiad to aach atulant at tk. nd of tb. laaalun.
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to rasort loan ortginat iona -and loan -oanlAii «olf tM Brovialoaa of -tn*
aad aaaliaja aaal loan aaaooiatlona wra originally raquirad Co rapert appll<
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la J rocaaa of apprlalm • prooarty . In otbar loKituttsi
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co.ta and ban.f Ita of HMD. aboizld tba pro* 1. loo. at cb. Ice and/or btuliclm
*• lhD|d, Iisijort.ii-.iv f:ie di.cu.Ilim in thl> CbapCOT of Cba utility of
iUiraict form, of HMTJA pru.DC oba.rvaclwt r.th.r chm tn. raulH of « mo
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lnalatll. accuaulacd Try lb* at«dj tu. duMn. rb. tia> tun of Cb. ptuail
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foi CbU *tud». la face, tbli r.port praunta ■ Maaau;. lot a,r. clou, and
uiuaal of Indlaia from .11 thru pb.au of Iba .codj foe which JH
heid primary raipon.ir.il >ty; Thau 11, accuracy; Fbaa* 111, Caapl.lan.H;
•ud Fh*« IV, Baraga, ant haporea.
lb. IL.m. P«a- tM b.. . Cb. pMd .nd ucul u« Of Cb.
praaantad In cba eoaaaaKm t.port "CoaBllanca iulj.l..-1 TB... f ladla|.
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laa lad procedural far u
M of MM m
rtaaaa d Ik loaura data.
Tha.. dla-
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41 wall *• then ua. In cloll
riant, and
t«pllanc. iM.dlirl.
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(or talaphooa BHHat
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alUta. Talaphooa im
nrlan war a
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free th* flrat and (aur
h TULla
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let! JBd tU FDICKadla
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rk reglona Asawar. to
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1.1* Board m th* r.j.t
1 Dapo.lt
MH h™ BHB -ln.tmc.rt' II w
ha hoae «rt,.«. dlaclo
tun data
Mir CO-pI t.nc. •uHHtl
on, Th* a
•elf It aethede lor tha
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Mni, an ~>t pteeer
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r titular
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rlthte apeclelltt*.
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t Titl. VIII ■■« EI
: mif («r II tha ■R|i|i d
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tm
It Inur.ee. Coioor.tlouw
c it, "that
BMM 1. nothing .. ■
1 like It
te r
pl.c. It. Althouih ,.«1,
•r. h». d.
eon th.HlHU.tIKl
oi lean
•v.l
ebl. to the. on lo.n IO«t.
• tkii lnt
melon 1. not .ui'l
tad. Data
!•■
«||'>I«I<I -'<•" «• »•■'"
only fet t
1. ee.t SI.lI.lUiy d.
•nt n.1 loo
Of *
*tb>r lmtltetlona at. ««
rtfrr-M
•xe >i th. locetlon
f property,
or 1
tUr ■*» HI.KH th. sari
I Htll^
bell loci eeamiBltle
. rurthenen.
pi.ll.ln.iy d.tMiU gallon
uilni »i»i
rellted «M< it, ,-n !y
nlbll In
ml
.r iMiltutleeeuheie in*
■Hi «Hr
of loin 1. get ewvhelalnf On
"r ™"-- "" "*« »
l..ay:
"•wtW", thay at.
of . helpful tool. ££ Inc. the;
Hlnulni
It ANU k. eetee. b».v
t. that .U
(l.ld .<..!«!. .od c
HI rlaht.
■ o.c
•lliti lm.rvify,J .tone*
•boil Of II
net that th. Hon Ho
rteaea
Dlac
™« Act itHlf ihould be
■HtlBBld.
Although tny eekeenl
dead th.
llBMe Of b0« eort glge dl.
ee e coasll.ee. tool
they u.n
■an
tire to oth.1 1HUH nub u th. burae
d Lucuttad In pr.p.riuj the ■»»-
MM
, aed the 1ml of i» by
he public.
Com.ou.ntlj. they .1
(•it
.o-p.l.ed to — n iaeo_n.
loo .bout e
eatlnatlou of tbe Act
,,
_ .od ruic.etlon ef Daeo.ltoiy In
ate ■ablet
n. eorwy leeicte. tm
depe.ltoty
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Hit
0 U0. »f tea 4*11. Ik.
L m-on u.
. .PpB.t. to b. «.*«••
net ef a
«•*
(•« llUtlt
utloo. T.eeittd an of
th. dot.
fot
leelyeia O* th* HUM al
th.lt
flneatlv. lOMMllK
ei elan.
Oo. anelble «■ ef ho— eort ..
. dl.clo.u
. dat.l.fordaoo.lto
a imtltvUou
i*ti
to aawtlae i tw- receta
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be eredlt ne.se of .1
1 nauhbet-
=
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in oeruloo, kHi SMd tap nalaalf or u ttat t— li lot ililu£i|
■1 |Ntpu*« In r*latioaahl»
utact «t which aortftat* *'
ncly balirf prvpand hu m
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dinE Accur.c,: Dili* tha data collKt.J si
TIM r.iulu at rh. (all;.
■aoeodlflt accaru? lavala. bat
at i«Dct>dliiM «c
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ronaC™.* ace-™-1.
that
.ml.torr .«aal nation P>oo.*.r.. i— Ind. ( mlw gl it- naacadtai
aatlKH
la uaad br aaaaaitarj Imtttmlo
» aad raeoaaaaaaHaaa for HI of
pi**
njocodlot tool" <!.«., iddraan
radial (atdai) *ad raeotd n.iw.o.oc.
-,to"'
Fladlna. sb (oniiiUD Afcaiac
f,i Mad? of au»aaclaa iwraq
lata!
w th. •atanmatloa of th. «
oner "«a "Aica data aa lo.™ <a.»..
COM
tract, amac. tjp.l Hn coll
mmt, aitngatad, and raaortad on
;i.n».vr. iMWMk «*-«lti <,r .u
mmmmtmm •"• •■"!■-• '« m
■Ml
•i tax la Urn no*" — tuff.
., SaoDl.ao, and CMm.o. Attratatloo
"™
of four trana ma (teflon) and
aaalaaadi
rlSiHEiiiS'
,° or nhan . Lou la lncarractlj
Conot.tloo .rror. uac -h.n
• Khar th. aaaoat or taa dellai
»»»■" <* l°'» •>« f* *"«»*
■.lul.tlon C aStaxS for lac:
aataZTt. i°ol.o?o.o^r'.t™Unt'l.'"
I,p., ol loan ,rr.r. f.ll :,.:
oia» 10 th. boo— coomt ■ddtu
root of th. .lint aaatl.d lut
»<!... la th. luff.ln MM -da
• tlon .trot. In ■!■ tola 30 p.
rc.ot of canau. tract 11a.. ti.pl. J.
Tha ■
•t a Half least probl.. h. cat*
»■ tract aaal.naaat arrer. cauaad »
ot„ a caaava tract liaa at iacorractlr
„r__ .,..■
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ln.l«|.i*cLa lo tb
laatltBtlaB1
procdur.n tor ..Ucllo* loan.
». tb*
fll« r»o*f.rrl»»
thaaa data to
othar tUM, and aut.iatlm tb
data In*
th, dliclouH ata
•aul. Thla
cwaaa loan, to ba IHI «|l lllX
d «r naaat-
Miasm in m *
mil tract 11
a. A total of 99 loan, mi in
r-dlarJoaa*
-* " lM" "™
*N1"1»
In ton 110 caaaaa tract! IB th.
"-"■
ihr.. *f n.
t« .-»!«
MtltutlOM in tnt San Mats (Mi
A„d..r,0ra
Id aor. than 10 P*
cant of tin c
n»u, tract IIom In th* aaaala.
Tb* ttnaaat
•Ualflcant prabl.a. MM "nan.
tnct B.at(BBBU arora and th.
lnapproprlat.
dlacloaad. •Dd Bl
oana |H| .nd
t-dl.clo.id In tha 123 c.b.U 1
act* la tb*
alalia. A total <>
*3 laapptapr
at. loan. *lth a nlua In .mo..
of 120 adlllon
■an laclaaad la th... MM t(
WW- Half of thaaa or. ahnrt-t
ara csaccalslw
«-"•»«' K—
1. ™.« of
1 MUta aacb.
tUhCH. of
tb* 21 .^lod ln.tlt.ti™ 1. tb. Chlca*. SH!
A^.mt.
In ion than SO pi
OBt of th* e
bu tract Una. 1b tb. aaafla.
Cam* tract
aaaiinaaat arrora
•M tb* Boat
Unlflc.nt problaa. A total of
1, 1)0 l**e*
•an inHmiw
and 37* leaBB B*r* BBa'ai-a'lKl***4 In tk* «
c.BHat tract*
1. rh. .«.!..
tba
a *ra **1*
«MHMHM«MM
fonnd U .«b
■asllai unit of IS cuu ran
Baaninafm Mm rt
Md ralitln
0 th. M.r.ll avatar and aaount
of laana that
*ara Includad in t
a canaua trac
a. Accordingly rvo aajor indl
M. «pra...d
p.rc.nt.Ba.,
uacd In th!.
aa.ly.ll to act, ioatltu
Isn't
1H»BU« attar
iral. Hi. fl
■t tnaaa la tb* noab*r of arara
—d. p*r c.aaua
ha nuDBt of
nan. par oo.ua tract, th. ..c
ad ladaala
DM dcll.c noun
1 *mra •— 1»
n.r BaW tract r.l.tiY. to th
dollar aaonm
of loan. par »UUI
tract. Sow
t arror hull
on Ch> bull nl tk
aitai of an
rota par loan la nek can. trac
t, -1.11 a stlHT
lcatlt.tltm. lnn.tr
ad ilfolf lean
arror la.all on rb* bull of th
* Baoaat Df
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P*r-t
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m-
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Z!Z+1
H«. Mart,.,. PJJ.IIIII
port
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■a*.-' n
tit, It 1. ausea.t
d that Id.
ltution. ha raqalrad to
■amtala
1 lu
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Inforoatlo
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of leas, caaaae
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h lou In
h. dl.cln.urt .t.teaanE
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ulatta ".p.
t obKk- tba icoinqr .
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itms
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and i
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at* friHiud U * eoar
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lodicotu tM nmrftamnt d.poH.ory looiituriooo cm b> it—ted M
HHpcion by th, aoord of gov,™,, or the fetwm >■•«-» s»i« CSo.id! if th.
Bo.rd d.t.rolo.. th* BM !■>■ ■«! mulUlno "... com .In U) tfquirtxnt.
•at* cut loll r .l.il.r to tooo. Upoiod inHn th. Ml ■ ■*! CI) idoquot. prori.looi
""''■""""••
Mot of th. iUdaOM (WMH pr.p.r.d by f.d.t.llv-cH.rt.r.d
ttooo^lEocr Institution, van found Eo ,. ■lmll.r In foruc Co ttl. pilotUs*
Fom HMDA-1. nowttr, th. forwt* of nq 0
th. dU clour. ItMMM prtp.t.d
by mtfOmWN d.po.ltorr lnotltutloo. ■
r. found 10 0. •ub.C.mUltr
«ff«r.nt Horn th, rad.ll>>*. Tom MM-l.
orthtrto™. MM Ctlt.tll HIJ for
including loon. In th. •[«« dl.elo.or. nut
lento v.r. llff.r.ot ch.n th.
«**>!« loo C crlt.rl.. For »Hplt, both th
oil.ln.E.d .nd th. purtbo..d
lonnn m to.blo.d loco ■ •lnal> npoTt in
h> dl.olo.ur. • t.t.-.nt* prtn.nd
br ■t.t.-ch.rt.r.d Institution. In IlUmti
rlor to r.DMl of th. mil 1».
*■■"■! loon. v.r. not locludod In th. dUdwn KMMI pt.p.r.d bj DM
■l.ta oi Cllforol. for .t.t.-ch.rt.r.d <j.po.ltury lrujtltutlon.. Btfl.r.nc..
In colum hurling.. ..l.ll.. ooluin poaltlon.. tcn.DOl.uj lorn novel. <!-..,
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br w
IUM
lie ctliMna. nil
public imrre.t group, ca
-dllT
M
1. ami
aaanlngfullr ln«
rprat Eha
I.clo.ur. intonation lor
th.
•apoaltacy
let
melon. In an SMS*. Con
.qo.Mly,
tbn flrat .uggwtlon la that
■axul.tlo. C
b. rivlaad
d aaaa tm pt.
[..ration o
a dlaclnaur. atatnant 1
■ . tandard
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' "*
Ith th. l«n tla.
«t«tl«
*Bd crft.ri. apacif l.d in
•.gal.tl.n C.
Th..
toad aouaacloo 1
that 1.
E.uElDg anaptlona to at.
H
th.
ar. ft
nata nt contaata
■c .elf lad
In Kagulac Ion C b. nqolr
•4.
Thi. mU
sat. E
i. aalatlag problaa tn «hlch
tn. dlaalallarltlaa ban.
c.c. i*d
Ma
.1 ,)li
EnOI itatnanta
•it. coap
lit Ion onaroua and lnt.rp
at a
cln
lapoaalbla.
,,
Caml
.too. on tctutl Ua.falM**
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Th. .
ndj limlioi!. Inrfl
HN ttat
1 CO (
ulu— , and public
nop. but that tba .it.at
of
mn
bT C
■M
and pallia lot...
■1 grout.
• aol clurlr nflnH. *a«r
cbalaaa.
tbf.
""•
atrongly ulnti:
" ttat ,ta
data .» «..atUl.
Ik. .
lull 11 mil Ufa alao
.b»th«
g.t. .„ »t particularly
ua.
.ul.o
th.
ul cltli.ua , or t
b. <l>po.it
rr Imtlcullon, aod llttl
of tha
Ml
ig aid* by t h..a |
ran pa. H
ally, tha .tody flndlnga
nJ
an that
tut
highly infill to
th. r.gul
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nkf
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fulfilling
th.tr at.wt.ry ra.aon.lb
Tha.
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( a .lgDltlc.nt p
■niuin
f th* Hi.clo.ur. Illtlan
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ra too
IMC
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I 1 Mania
purnoa.. Ih... dlacloau
a a
at.aana
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nl through laol-aat.,...
of
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-
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PKOET|*|« dltCl»«nT«
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■ -« — nu: |*«crflDt «<
itaaam t^tloyad autMatad aortiai* lea* fl
CtllUfO S1ISA U*t «H IB (Kl
.«. J1.6B. ThaM flmUnaa |i
4 biriH<u :<W tat 1,000 )
■: alaiaa ■ ■ HM1«™ I
aDOluftaloSNSA.. ll.hi t
IW S2.il- Th. ottiar I
inJor all II IsatlutK
leu* In tha arudr [apart** tarn tbao 101
* San Slate lU lullalo Mil. Sli ol tl
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■aoaal aorr..,. lo.a Ilia, trt en... ln.tlto.ton. locurrad . «... par loan af
I2.M. tha ivfr.se »taf «tr lo.a far .11 11 Institutions Mt SJ.67. Tha f India*.
100 loan. .. .utooatlna tends to tacraua tha co.t o.i- l.,.m .ad that owr.ll tbe
coat par lean la nlgnar than far tintlr.ur.loiw with larga auaatltld* of loam-
The National Burd.n; A rau|n appmlaatlon ef tha total lndutrr-alda
aubjact to tba Act by tha coat par Loam Data war. -not av.ll.bl. on the ratal
Id 1977 tr> tha 1.700 dapoetlarr inatltntlona aubjact to Iba Act.
or rJ.po.ttr.ty UMMMeafJ aob).ct to NMH la tha praaer.tloa ef tbalr 1»77
dlHlMur*. ...taafnt. ta aatluMd to be approila.tclr |S.I Billion. Ttala
■MAI la rapraaaatatlaa of tha ludu.try-afd. coat par loan.
Tha PaKul.torr Bnrdan; CarlBataa of tba ratoarcaa ravalrad for
examination of the accuracy with --htrli disclosure statement* vara praparad
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wwii teqvtn -200 to MO «ln
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• apaclf ltd In I»|ulatlqo Cat
nartaaga diiclMurf
llngi also aho> that data ara not nartlcniarli u.
a balnf Bad* hy cnaaa gTDuna. Finally, tba atudy Indian* in
ta ara hlnhlr unafnl to tba ragvlatvry atanclaa. ti-*sp kk,
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4 4tgr*t*tlnt daE* Icto tba ■
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tort.... I™ rUn
mUSSS^.^— t
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of ib.
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par loan locurrad bi than lnacltutlona uilng luiouifd (aconlqua* la tb»
TM(t«P lullluli™ In [ha •tudj raporttd batnaaa 100 and 1,000 laaoa
CnicafD SKSA and on* In aich of tha Sullti|D and liffili SnSAa. El|at af thai*
dUclwoca aeataaaat. Tbaaa coaaliEad. at Una laacltutloaa la tba Chlcaaa SIS*.
•ad BUI la aach of [ba til Dlaao aid Buffalo Mil. Ul af rbaia laatltatloaa.
3i,iii«db» Google
Ihh f o
.h... ill Institution!
■aa St- 36- Tb«
othor fin fault
clou oatlend
■•■H ior<ii|i lo.n [11m, and
thai. 1 initial
ona liuitu • CH
pat loan of
*i->*. -n.e iv^»e* m n*r iu
for all 11 Ina
ltutlona PM 13-*
Tba f lnllaac
■ugg.1T
th.I, for 1 (Otic i lorn
lib aaall qu.at
tlaa of loan (l.<
. . laaa tbaa
JOO id
.1 autOO-rloo t.ndl in
IRBW tha cc
i pot lo.o and Ih
t gnnll tha
™. p.
loan i. hlajw tha. f.
l«tt«uti™ a
th i„„ .-.tit.
. of loan..
burton
isrs
"" 2 IV"
»po.,d by KHDA can b. d
■MM
and noaa l^ronaanc 1
an. xlilouJ
br d.pn.dotr tut
CutlOH
•objoct
to th. *et br th. CHt oat loon. Data
PHI not .villiH.
on tha total
■uabar
f nun loan. Dininiud
In 10JT by .oh]
ct Institution..
• u aotlaal*
... d,r
•ad froa Hiatal 1977 d
ta. Th* anal..
■ .poo which th.
ItlMtl -a.
bo»d 1
dlKUMd In Atoandla
. Tha .oalrnl.
lodlcila. that in
■daul
4.01a!
lion ttildaotlal asrt|i|> and ho» ur(
™»n. lo.ni van
orl.loataa
i, un
by th. 9,700 dopoarlorr
lo.ti.oti™ .a
>*" '° *" *"•
... a. .«»„ toac of
a.« „.r Ian,
h. lndu.tr, ,1c.
*rd.n 1„™,
br d.po
[lory Institution, subj
El ta HUT.* la t
• prapar.tloc of
Iwli It J J
dldclod
re at.t™nt. It i.tlM
•d ta t>< .pptoi
aaloly IJ.f -1111
o. Thl.
MlMt
, at coin*. *••«■• th.
t tha Mttff I
■t p.r leu foot*
In tha thtaa
MH.1
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. Ko.uL.nrT lard..!
'17Z1Z
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t. arid
too or H>J .ccur.cy -U
■» »u
MM! Id ■ ™-p.nion H
ort ontitiod "P
ocoduroi to U.«
tti. Accuracy
of Hw
Jfatt.... llKlgnu Eta
•HUH. 10 Ctva
n tha I.t.Ii of «
M0 tbii
<m found In tha di.clo.ur. •(
WW of tha
* .tudr in.tlt.ti
n. It 1>
WW)
1 that • coaplltnco >u
[nation of a dtpo.ltorj laotltotl
n lncluda
dot.n
Hutlonof tha .courier
alth ahlch tha
iicloaur. ititaaant aaa pnfind.
Ttwr* •
* tw part. » tbi. <i«
rolMtloo. Tha
lr.t H j dattraloatln of tha
<n<«
n .hlch piop.rty *rfd».
•a MM correct
y •oocoooo to th*
•ponarlata
a»
tact. Tha ..on J Had
IJBlW Of
b> «taat ta unlet
loan data
-tact It aaoroaatad lot.
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hi* Google
■ hic Hthodslstlcillr rlK.ro,,.
n tt» ln.l|h[( KlHliUd b» th.
'1
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to . rio.ncl.1 .ppllc.llon.
The Let that .ppllc.tlon d.t. do not r.vul .11 Eon. o( dl.criai n.tlon
..lu.. Con.Hiu.ntlT, th« in™. 114.1 lorn currently uod.rv.y HdKtrUH
dllf.nnn.l tn.ca.nt to ■ bonci o. . pto.pectlve tor™., on the bull
"f r.ce color te[l»lon hi or oth.r ch,r.oI.rlsU=. piohlblteH b. .I.cule.
>nch .. Iltl, vm or ECDA. 11,1. a.llnlclon Indict*, ch.. d.t. .r. n.td.d
Di,iii«db» Google
to KI DtceillHlr JutlBlr ifpltCMCiDD..
redllGlnf it Jisrriol ml ion. ippUcatlOB
tot 1) lijontlljlni ilie s.rltmi form of .
■1th a» or unii of rb. pnfcloltad l>uu
it dlKto*l>( ■opllcacteiK d.
o DDE provld* Inloraatli
AFpllHIlao. d.t. .
boonatloB conearnlaf, ■tpUeatloa* dora ntuda li
■ .ppllc.ni. n™, nbao -
Digitzed by GOOgk
JUKI -Hh-Klt
MlMll
Inn data coal
d be
dl.cloHd
•hsald data on all
nppllc.IlOM ba
iltlllU
SI calf dat.
ond
nltd ot ■
tadtwi
.pc.llc.tlo-!
Should the dl.cl
■•I ■CPlIaacioBi datn
■ho*
onlj tb*
OTM*
idaaount. ot
lain nppllcntlon.
maaeh
c.nau. UN
or .
onld tba.
AH
nclud. datnllad
mumiiini ■
I botic-
.r. prnpartr
and
loan t.can? tha.
ope Ion. •■tall
.ub.eantlal diff
kaaaa*. 1
r, th* d.»r.«
o vkl
eh thai.
■UN
date ere u**f«l
i» u.ae.im juc
rl adnata
rj »ncttc«.
U«i«
ha noa
• en.ocl.c.d
•ltd chair dim
.or.. If
only the tTS-
nacnnt
I loan
application*
In .ech iiwi t
ant aea
e an dl.cle*
Hi. Cd
•c conald
ration. dUeuaaad l.t.r
■lei. at. »>io>t
dl.clotl
ni data on .)
aonllcaclonn.
In *oc
* can*, dlaaloaur.
•cii" ■*» only
I •ltndCWll*
mil
prevlda
ba **-
•aount of
InfanacloB at <l
UIluUT reduced en.
ttM dan.
sattotr
Iratltutloun
uald comlrnt |
oro»lde
ori.lo.tlcn.
u.lr., car
ant lHi can It aat hod..
11 OeO-lled data
Sfatha I
alt
■M*
MR
, and Lou tan*
W* CO b. dl.d
■at boa
wr. than a
iimne
oh tun. fat dUelaniat
rh... data on .1
appllca
loot. pro-r
it ,
lull foe
ceapar
.on. Th* coat*
■HCUM »lth
hi. appr
inch, bmw
■rH
an to na
con. 10V
tall* hi liar than
th. C«»« Ml
"• ""
" """ "I*""1
.of th*
.port
nd.r nanul.tloa C.
MtHUl
KjMI
Th. nant of
l.c.o.ln. d.C.
r.l.r.
t* .11 tb.
application, tor
■ovtfat.
1«m wald
. coo.ldar.bl j Qlltiet
Chan th. C«*t Of
dl.clo.ln, data
o .11 sort (ig
Inn
orf,i««
hi. a
. hl,h.r coat of
dl.tlo.Ja, data
n .OPllc
.Clou dartv.
ftn.
th. lack
of M
waled loured* for
thaaa data. Hh
dapaalt
oty IMtituti
nut)
« orl8innc. a •
lolf leant euantltT
o( aortiai* loar.
.rrauall
1 U.f. act*
■taan
V.OOO Id*
..) una
aut canted aaju* to
prepare tb.lt dl
tntaannt. I
■aa
Mlltullo
■ Ml
aln an auto** ted
loan (11a and u*
thl. 11
la a. th* .on
•**«
dnca foe
tb* M
din at* fcMI— Mt.
It MM Unatlgi
h.c at 1
aat thv» ■
■at 4
vary four
loan
adl.elo.ur.
tMbMN ate naa.d upon
dat* fro. M
Ah
.utoajtad
fll*. Without .«b aut™t.d
■nana and eOuteo
or dntn
d.po.ltory
UM
utlon. tb
t curt.
■ 1) aee.ra.Ma data
la pr.parlnt lb.
I dl.nlo
•HE. .r.ceaec
hundred.
r thou
•*aa *f lotaa ueald
Incur Inr .mat*
Han the east*
taaV
curiam I,
Incur
* tb* preparation
3i,iii«db» Google
WUeatlm milt
■■plftlotd la larjm part b
i *ppll ctt laui woulil nqulra lMtl
urly coll of dM. • MIJ. '
) <10>/t.0OO ■)*■
Digitzed by GOOgk
oily Htf
U1U>4 I
or ucb of ibo four parasatara. Th. ™bor
of data ilnoii aad
— taelta
i «M rt.ruuii to 1- alatloaad
o ooo laportant paraaacar. 1
dlacloaur
o ro.ulr.Hot -Hfc. raiatlnly faa
Mta olaaooto and of In. coat nlnln
NMhi
f-.ulHi.Ml wr.u! J b. Ch> diode
to of to*
auabar aad awiiu af
■H*i
ooo (or loaoo 1. aacb caaaua tract
.■on
coaploi aod coot 1 J
dladoau
o roqulr.aaot wold bo tho dlatlo.
'" of d>
• lied data oo applicant,
presort-.
aad Ir-nluruliHulci dorlnd.
(of • «-!
It, froa tba currant ar .
■odillad
loaa application "Haior. Such d
<o could
laclodo, far >».1>,
•uch Um
■a tb. .ppllc.or'a ■.... raca a.a
locoaa,
tb. .ppralaad Talaa aad
Mo af tb. ,«»m„ ud tb. ,™ rf ,b. 1
"•
Tfc.
coot of dlooloolnc ippllciclgn d
t. could
b. cduead aub,.„t tally.
If ooly d
• ta.B danlala or ■rlr.hdranla HH
dlacloaai
. m u approach •ould ba
pnfar.bl
o, only If tha daalnd Ht of data
•ora ro*
rlctad to lha typaa aad
aaounuo
f application, la coco caaaua tr.t
. Unco
thaauuoacof d.alala
andaitbd
rotnla toa-.rb.r coutltut. onl- .
■all par
ontooa of iba o. trail
■ntorol
application iho coot! MBMiltta
d -lib .u
oa.il nt tbaa* data vould
l»HkIi
ciil^lr Lai tbaa tba coot. ...ocl
•lad Wth
■ ur.aa.clnf. all application.
til. d.I.
•trf coara, for aiaapla. mid bo
Round
ro, M mlllloe to 3U0.MM
•inlK
baro nan 100 cbaraetora par oaeb
•collet
oa aad tbat Id parcaat of
l-*WU
..to- »r. .l.b,r .!*-«. or d
mod.
A.
•and «j« cat ol.ar.tlaa 1.
bar.™
cm uaadad to danlao
«V«[
1 tut loos
in proca.alo, application
.p." .hTuzrif mpu. n i™"0n«'.«
M vould aory o.B.adli-1
not. of 0.
I for aacb application
th« ....
IO bo rrntniM. This uould, la
am, dap
ad uponvbotboc.il
appllcatl.
■o or onir daalal. and MoMraMl
> u.ra to
h. dlacloaad aad upon
t:h« 1«1
of d.t.ll tor aath application.
natltutK
oo with. •*?. ■» tbaa
1.000 .pp
It. Hon. to b* dl.cloood you 1,1 ao
t 1U.1-
banaflt froa autoaatlon.
If ■ .iinlflc.nc nuabec of iMtlt-tlooa IMr
■ roqulro
to danlop eoapnear
3i,iii«db» Google
roold nnlt la 1 ilpUf lean eiaalat In ht1i« (or thoaa In
na rstalalta usaMlltl** to neUlaa nWnt Imlaimn
■ pottml«llT utnl an nsruilr unly ti
d jmlp*DC SB tBt utility of
Digitzed by GOOgk
■n Mat -t.
kink -irh 1.000 d.poiltor. .nd 30 iitpK loua In 1 (tut. |«|[ipM[ Mai
lh> n|(»H "< ul kMHl • itu.tloni mid pr.cluj. It, ..lid M* Neat, th.
•bill .-lu.o.i, Tl.lr.ljr, Iba .ddt..... ,:,,,,:.■:! to tf.po.ftory liutltMtlou ar
aortpia Ion «ru[»..i™. Sine, tha u«nc of Ihi J«M h*M la not earr.nllT
Digitzed by GOOgk
I l^illcailona: Although (1
ill ongoing gpcxac . ;■■:. coata «qu«l et g»*»r than (boa*
under Higulatlon t iliclmurj. Om-cla» dive lopat Ota 1
epical !■■ on .Hi tins a
curad an a pa>r da.p4a.lt0r
: ■toil* (lata! )ui.
Digitzed by GOOgk
4 pi-arlda lb. public mod (ha r.
n|ili purif olio mU bin i
tncliutlDf. onlj n. arltlaai
Mat? il.jm.init* lnatii
deluding onlj ■ort|at* 10401 orljliui
» ftl* to pn*KI tb» mn|i» portfoL
3i,iii«db» Google
thar Hit tu fll. to produca ■ tap. of th. lo.n arlalaatlaaa In a «n—
Maul w ohlch the». la tats, s.nd ta I ,.r«c. tana t« |««da. Tfcaaa
1-tltuti.n. aould 1— r .M.t.r incr—nt.i „.,..
Th. .M,t,.KI .f tb. tat.rdla, «d .n«l*tl«> a™.*™ «.l^.d
by Inatltutlaua t.ir.t manual ..... Till araatl* IBfluane* th. eaata of
dlaeloalaa: th. •I(r<l.l< porttalla. If Journal, ot fllea oriaalaaa « ■
data I« th. aucatata portlolio ahould nqglri ■■■ greater chii thaa da*.
th! pr.paratlon of th. J.t! for th. arli.lB.tiou. for ■ alaala fl.cal Taar.
Innir uithout auch prutaour.e th. cost of pr.p.rlna tb* afaraiate pcii-tfolio
data cdiii- 'hi net hl|W than th. caata at areparlaa. tha data oe orialnatlooa
■-"•""■»>■■'•■<•
3.1.* Addition a! Othet TTHi of Loaaa
* fourth paealble ebaata to th. content, of th. tat —Id a. to
includ. other taaaa at la.ua la th. di.cla.ar. KitiarM. Such loan tjpw
currently not dledoead tatl.dai bg.in.aa. caaaaaKlal, or canalt Io.ua.
■halt tan coaatTOCtl.il loan., ana refiner cae Bada far eurpa.ee achat thai
ta aaaala* araaarte t. th. msA.
Although tKa benefit, aed coat. a( adding thaaa athar type, of loan.
te dleclneur* at.tteant. vara not annlTied, . (uraary Kami net la. nuaiu
that th. ben.flt-to-co.t rati, fat ulaeleaura ot thaaa loaaa -bum b. Id.
rel.tlH ta tba data auttaatlr dlaclo.ed ■«»■ loan orlgloetiooe
Und.rJably .uch loan, constitute contribution to ■ cawalty. cr.dit
need.; hMTic, it ippaiTI that th. coat Bar loan dlatloo.d vould h* ouch
hllh.r than tb. coat par wt.B„ loan orlalnatl.it. curr.ntlr di.cloaad.
Th. hlgh.r coat p.r loan oculd derive fro. nail At additional (encoding
raaulrtMnts aad fro. tba added .ffort requited ta p.ortaa and aggregate
data frr* .arloua dep.rtasnt. aad Hlai within an lnatltutlon. Tba other
Digitzed by GOOgk
raqalnaaot could b. dumpi ii
: ■boat 450 billion la quallfrlDt
lttlM nlilili JHSjU, 6.B00 u
Digitzed by GOOgk
hi* Google
ilfa of 1 mil tut Ion* nqulnd cu npsrl.
if dipoaf tocj Imitation and ttw tgla
[■porting hy ilrtin of tha oirrant aaai
| K.
IrKCnlcHtta..
U J
U 7 «7.»
*>, ta.1*. „ MM.
1.7
0.. l i.l
3i,iii«db» Google
.1 d.Ilmf ta Juatlfj id axuaaloa Mel
I la that Cba Baa* Kartaaga Dladoaura
3i,iii«db» Google
lap ran GsocoJlnfl A.
3i,iii«db» Google
vtui- i«»l3r* baAfca, «i *irlcgi mma looo lavuL I IE10W t ot*l*fi
la uliodir y*ir 1977. TM> vol*** Iim-Ibbm bain 1-4 favilj a
jod ■uJtliW.lT re*ld*ntl*l proptrtl** *b4 It rtpratita 41--8
natlcwl nlaa of U73 oIIUob orU!B>»d It i^- ItKtci. Iba
lclWi Kllli loua Qclfiucc^ S? r*4*nl Crttn '.'tiior* vklck
1*77 on b> HIlBiud bj dividing tit] billion hj S3', WO- Ihla Tltlaa n
xiIhii of l.»6 Billion aortMft lorn. ThU ll»«ro ka DDE ,-r,"'i. boar
bum Bo.;i nilm.d tint tr.Jlt Union occogutd Jot WTSilaittlt I pan
of llw »citai|e loin, bitd by o>po»ltorj Institution la 1477. Immmml.*i taw
ih. MMmp of loan bold to bo «.;■:-. nlml tn Ik* M"«V HlilHIil,
c»41t uatana mid lntlUM IIh total uiMr ofaorttaaa loaaa orliinatao'
bf 1 wio«. Ac*litat till, firtir, toa total i™t*r of BRHII loaaa oi-li!
3i,iii«db» Google
lut*. mttm Dl*t*
orlilutad by tb. 1.T0O a.v-ltotj .ubj.et
Digitzed by GOOgk
hi* Google
hi* Google
3 6105 045 180 440
DATE DUE
STANFORD UNIVERSITY LIBRARIES
STANFORD, CALIFORNIA 94305-6004
3i,iii«db» Google
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