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The Mortgage Market in 2011: Highlights from the Data Reported under the Home Mortgage Disclosure Act

Since 1976, most mortgage lending institutions with offices in metropolitan areas have been required under the Home Mortgage Disclosure Act of 1975 (HMDA) to disclose detailed information about their home-lending activity each year. The Congress intended that HMDA achieve its legislative objectives primarily through the force of public disclosure.1 These objectives include helping members of the public determine whether financial institutions are serving the housing needs of their local communities and treating borrowers and loan applicants fairly, providing information that could facilitate the efforts of public entities to distribute funds to local communities for the purpose of attracting private investment, and helping households decide where they may want to deposit their savings. The data have also proven to be valuable for research and are often used in public policy deliberations related to the mortgage market.

The 2011 HMDA data consist of information reported by more than 7,600 home lenders, including all of the nation's largest mortgage originators. Together, the home-purchase, refinance, and home-improvement loans reported represent the majority of home lending nationwide and thus are broadly representative of all such lending in the United States.2 The HMDA data include the disposition of each application for mortgage credit; the type, purpose, and characteristics of each home mortgage that lenders originate or purchase during the calendar year; the census-tract designations of the properties related to those loans; loan pricing information; personal demographic and other information about loan applicants, including their race or ethnicity and income; and information about loan sales.3

On July 21, 2011, rulemaking responsibility for HMDA was transferred from the Federal Reserve Board to the newly established Consumer Financial Protection Bureau.4 The Federal Financial Institutions Examination Council (FFIEC) continues to be responsible for collecting the HMDA data from reporting institutions and facilitating public access to the information.5 In September of each year, the FFIEC releases summary tables pertaining to lending activity from the previous calendar year for each reporting lender as well as aggregations of home-lending activity for each metropolitan statistical area (MSA) and for the nation as a whole.6 The FFIEC also makes available to the public a data file containing virtually all of the reported information for each lending institution.7

The main purpose of this article is to describe mortgage market activity in 2011 and in previous years based on the HMDA data.8 Our analysis yields several key findings:

  • The number of home loans of all types reported by covered lenders declined between 2010 and 2011 from about 7.9 million loans to slightly less than 7.1 million loans. Refinance loans fell more than home-purchase loans, although refinancings surged toward the end of 2011 as interest rates dropped. The total of 7.1 million loans reported in 2011 is the lowest number of loans reported in the HMDA data since 6.2 million in 1995.
  • Government-backed loans originated under programs such as the Federal Housing Administration (FHA) mortgage insurance program and the Department of Veterans Affairs (VA) loan guarantee program accounted for a slightly smaller share of home-purchase loans in 2011 relative to 2010 but continue to make up a historically large part of the owner-occupant home-purchase mortgage market, at nearly 50 percent.
  • Despite the surge in the government-backed share of home-purchase loans, which historically have gone to borrowers with relatively low credit scores, analysis of credit record data indicate that credit scores of home-purchase borrowers are considerably higher now than at any point in the past 12 years. The median score of such borrowers has risen about 40 points since the end of 2006, and the 10th-percentile score is up by about 50 points.
  • Our analysis of the HMDA data suggests that, at the retail level, the mortgage market has not become much more concentrated over the past five years. The 10 most active organizations accounted for about 37 percent of all first-lien mortgage originations in 2011--only slightly higher than the 35 percent share for the top 10 organizations in 2006.
  • Consistent with the overall decline in home-purchase and refinance lending, the HMDA data show that from 2010 to 2011, all income and racial or ethnic groups experienced a drop in home-purchase lending, although the extent of the decline varied some across groups. Only low-income borrowers avoided a fall in refinance lending.
  • The HMDA data suggest that lending activity has not yet rebounded in neighborhoods experiencing high levels of distress. In fact, home-purchase lending in census tracts identified by the Neighborhood Stabilization Program (NSP) as being highly distressed declined by a larger percentage since 2010 than such lending in less-distressed tracts. This decline was particularly pronounced for lower- and middle-income borrowers in these neighborhoods.
  • The incidence of higher-priced lending across all products in 2011 was about 3.7 percent, up from 3.2 percent in 2010. Similar to patterns observed in the past, black and Hispanic-white borrowers were more likely, and Asian borrowers less likely, to obtain higher-priced loans than were non-Hispanic white borrowers. These differences are significantly reduced, but not completely eliminated, after controlling for lender and borrower characteristics.
  • Overall, loan denial rates in 2011 remained virtually unchanged from 2010, at about 23 percent of all applications. Denial rates vary across loan types and purposes, and across applicants grouped by race or ethnicity, as in past years. The HMDA data do not include sufficient information to determine the extent to which these differences reflect illegal discrimination.
  • Comparing home-purchase borrower incomes reported in the HMDA data with income reported by homebuyers in household surveys suggests that incomes on mortgage applications may have been significantly overstated during the peak of the housing boom. In more recent years, there is no evidence of overstated incomes.
  • The change from using data from the 2000 decennial census (Census 2000) to using data from the 2010 census and the 2006-10 American Community Survey (ACS) as the basis for deriving median family income will affect how banking institutions fare in Community Reinvestment Act (CRA) performance evaluations. Had the new census-tract relative-income classifications been used in 2011, there would have been a net increase in mortgage lending to low- and moderate-income (LMI) neighborhoods of about 150,000 loans, about 22 percent higher than the number of LMI loans in 2011 under current census-tract relative-income classifications.

A Profile of the 2011 HMDA Data

For 2011, a total of 7,632 institutions reported on their home-lending activity under HMDA: 4,497 banking institutions; 2,017 credit unions; and 1,118 mortgage companies, 812 of which were not affiliated with a banking institution (these companies are referred to in this article as "independent mortgage companies") (table 1). The number of reporting institutions changes some from year to year. Some of the fluctuation is due to changes in reporting requirements, primarily related to increases in the minimum asset level used to determine coverage.9 Mergers, acquisitions, and failures also account for some of the year-over-year changes. Finally, periodic changes in the number and geographic footprints of metropolitan areas influence reporting over time, as HMDA's coverage is limited to institutions that have at least one office in an MSA. For 2011, the number of reporting institutions fell nearly 4 percent from 2010, continuing a downward trend since 2006, when HMDA coverage included just over 8,900 lenders.10

Table 1. Distribution of reporters covered by the Home Mortgage Disclosure Act, by type of institution, 2000-11
Number
Year Depository institution Mortgage company All institutions
Banking
institution
Credit
union
All Independent Affiliated1 All
2000 4,721 1,691 6,412 981 332 1,313 7,725
2001 4,686 1,714 6,400 962 290 1,252 7,652
2002 4,698 1,799 6,497 986 310 1,296 7,793
2003 4,675 1,903 6,578 1,171 382 1,553 8,131
2004 4,962 2,030 6,992 1,317 544 1,861 8,853
2005 4,878 2,047 6,925 1,341 582 1,923 8,848
2006 4,846 2,037 6,883 1,334 685 2,019 8,902
2007 4,847 2,019 6,866 1,132 638 1,770 8,636
2008 4,855 2,026 6,881 957 550 1,507 8,388
2009 4,810 2,017 6,827 925 399 1,324 8,151
2010 4,677 2,041 6,718 848 371 1,219 7,937
2011 4,497 2,017 6,514 812 306 1,118 7,632

Note: Here and in all subsequent tables, components may not sum to totals because of rounding.

1. Subsidiary of a depository institution or an affiliate of a bank holding company. Return to table

Source: Here and in subsequent tables and figures, except as noted, Federal Financial Institutions Examination Council, data reported under the Home Mortgage Disclosure Act (www.ffiec.gov/hmda  Leaving the Board ).

Reporting Institutions by Size and Mortgage Lending Activity

Most institutions covered by HMDA are small, and most extend relatively few loans. For 2011, 57 percent of the depository institutions (banking institutions and credit unions) covered by HMDA had assets under $250 million, and 76 percent of them reported information on fewer than 100 loans (data derived from table 2). Among all depository institutions, nearly 55 percent reported on fewer than 100 loans. Across different types of lenders, mortgage companies tend to originate larger numbers of loans on a per-reporter basis than the other institutions (38 percent of the mortgage companies reported more than 1,000 loans, a share equal to about six times that for depository institutions).

Table 2. Number and distribution of home lenders, by type of lender and by number of loans, 2011
Type of lender,
and subcategory (asset size
in millions
of dollars)
Less than 50 50-99 100-249 250-499 500-999 1,000 or more All
Num-
ber
Percent of sub-
category1
Num-
ber
Percent of sub-
category1
Num-
ber
Percent of sub-
category1
Num-
ber
Percent of sub-
category1
Num-
ber
Percent of sub-
category1
Num-
ber
Percent of sub-
category1
Num-
ber
Percent
of sub-
category1
Depository institution
Banking Institution
Less than 250 1,215 51.6 509 21.6 463 19.7 126 5.4 24 1.0 17 .7 2,354 100
250-499 231 24.9 131 14.1 317 34.2 173 18.6 56 6.0 20 2.2 928 100
500-999 106 17.7 61 10.2 120 20.0 150 25.0 119 19.9 43 7.2 599 100
1,000 or more 66 11.1 25 4.2 67 11.3 68 11.4 129 21.7 239 40.2 594 100
All 1,618 36.2 726 16.2 967 21.6 517 11.6 328 7.3 319 7.1 4,475 100
Credit Union
Less than 250 783 58.5 301 22.5 207 15.5 36 2.7 11 .8 0 .0 1,338 100
250-499 42 13.9 52 17.2 111 36.6 70 23.1 25 8.3 3 1.0 303 100
500-999 16 7.8 14 6.9 49 24.0 58 28.4 48 23.5 19 9.3 204 100
1,000 or more 0 .0 4 2.4 13 7.9 28 17.1 40 24.4 79 48.2 164 100
All 841 41.9 371 18.5 380 18.9 192 9.6 124 6.2 101 5.0 2,009 100
All depository institutions
Less than 250 1,998 54.1 810 21.9 670 18.1 162 4.4 35 .9 17 .5 3,692 100
250-499 273 22.2 183 14.9 428 34.8 243 19.7 81 6.6 23 1.9 1,231 100
500-999 122 15.2 75 9.3 169 21.0 208 25.9 167 20.8 62 7.7 803 100
1,000 or more 66 8.7 29 3.8 80 10.6 96 12.7 169 22.3 318 42.0 758 100
All 2,459 37.9 1,097 16.9 1,347 20.8 709 10.9 452 7.0 420 6.5 6,484 100
Mortgage company2
All 185 17.0 68 6.2 133 12.2 135 12.4 149 13.7 419 38.5 1,089 100
All institutions 2,644 34.9 1,165 15.4 1,480 19.5 844 11.1 601 7.9 839 11.1 7,573 100

1. Distribution sums horizontally. For example, the second column, first row shows that 51.6 percent of banking institutions with assets of less than $250 million originated less than 50 loans in 2011. Return to table

2. Independent mortgage company, subsidiary of a depository institution, or affiliate of a bank holding company. Return to table

In the aggregate, reporting institutions submitted information on 11.7 million applications for home loans of all types in 2011 (excluding requests for preapproval), down about 10 percent from the total reported for 2010 and far below the 27.5 million applications processed in 2006, just before the housing market decline (data derived from table 3.A). The majority of loan applications are approved by lenders, and most of these approvals result in extensions of credit. In some cases, an application is approved but the applicant decides not to take out the loan; for example, in 2011, about 5 percent of all applications were approved but not accepted by the applicant (data not shown in tables). Overall, about 60 percent of the applications submitted in 2011 resulted in an extension of credit (data derived from tables 3.A and 3.B), a share little changed from 2010. The total number of loans reported in 2011, 7.1 million (as shown in table 3.B), was about 10 percent lower than in 2010 and is the lowest number of mortgage loans reported under HMDA since about 6.2 million loans were reported in 1995 (data prior to 2000 not shown in tables).

The HMDA data also include information on loans purchased by reporting institutions during the reporting year, although the purchased loans may have been originated at any point in time. For 2011, lenders reported information on 2.9 million loans that they had purchased from other institutions, a decline of nearly 9 percent from 2010. Finally, lenders reported on roughly 186,000 requests for preapproval of home-purchase loans that did not result in a loan origination (table 3.A); preapprovals that resulted in loans are included in the count of loan extensions cited earlier.

Table 3. Home loan activity of lending institutions covered under the Home Mortgage Disclosure Act, 2000-11
A. Applications, requests for preapproval, and purchased loans

Number
Year Applications received for home loans, by type of property Requests for preapproval1 Purchased loans Total
1-4 family Multifamily
Home purchase Refinance Home improvement
2000 8,278,219 6,543,665 1,991,686 37,765 n.a. 2,398,292 19,249,627
2001 7,692,870 14,284,988 1,849,489 48,416 n.a. 3,767,331 27,643,094
2002 7,406,374 17,491,627 1,529,347 53,231 n.a. 4,829,706 31,310,285
2003 8,179,633 24,602,536 1,508,387 58,940 n.a. 7,229,635 41,579,131
2004 9,792,324 16,072,102 2,202,744 61,895 332,054 5,146,617 33,607,736
2005 11,672,852 15,898,346 2,539,158 57,668 396,686 5,874,447 36,439,157
2006 10,928,866 14,045,961 2,480,827 52,220 411,134 6,236,352 34,155,360
2007 7,609,143 11,566,182 2,218,224 54,230 432,883 4,821,430 26,702,092
2008 5,017,998 7,729,143 1,404,008 42,792 275,808 2,921,821 17,391,570
2009 4,216,589 9,982,768 831,504 26,141 216,865 4,301,021 19,574,888
2010 3,847,796 8,433,333 670,147 25,550 170,026 3,229,295 16,376,147
2011 3,630,284 7,390,690 686,788 35,048 185,943 2,944,662 14,873,415

Note: Here and in subsequent tables, except as noted, data include first and junior liens, one- to four-family homes (site-built and manufactured properties), and owner- and non-owner-occupant loans.

1. Consists of requests for preapproval that were denied by the lender or were accepted by the lender but not acted on by the borrower. In this article, applications are defined as being for a loan on a specific property; they are thus distinct from requests for preapproval, which are not related to a specific property. Information on preapproval requests was not required to be reported before 2004. Return to table

n.a. Not available.

Table 3. Home loan activity of lending institutions covered under the Home Mortgage Disclosure Act, 2000-11
B. Loans

Number
Year Loans, by type of property Total
1-4 family Multifamily
Home purchase Refinance Home improvement
2000 4,787,356 2,435,420 892,587 27,305 8,142,668
2001 4,938,809 7,889,186 828,820 35,557 13,692,372
2002 5,124,767 10,309,971 712,123 41,480 16,188,341
2003 5,596,292 15,124,761 678,507 48,437 21,447,997
2004 6,429,988 7,583,928 966,484 48,150 15,028,550
2005 7,382,012 7,101,649 1,093,191 45,091 15,621,943
2006 6,740,322 6,091,242 1,139,731 39,967 14,011,262
2007 4,663,267 4,817,875 957,912 41,053 10,480,107
2008 3,119,692 3,457,774 568,287 31,509 7,177,262
2009 2,792,939 5,772,078 389,981 18,974 8,973,972
2010 2,546,590 4,968,603 341,401 19,168 7,875,762
2011 2,416,854 4,311,870 339,427 27,111 7,095,262

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Home-Purchase and Refinance Lending

In June 2006, the peak month for home-purchase lending that year, nearly 712,000 home-purchase loans were extended, compared with only 254,000 such loans in June 2011, the most active month that year (figure 1).11 On an annual basis, the number of home-purchase loans (including both first and junior liens) reported in HMDA in 2011 was down about 5 percent from 2010 and was 64 percent lower than in 2006 (data derived from table 3.B).

Figure 1. Volume of home-purchase and refinance originations and average prime offer rate, by month, 2006-11
Accessible Version |  Return to text

Note: The data are monthly. Loans are first- and second-lien mortgages excluding those for multifamily housing. The average prime offer rate (APOR) is published weekly by the Federal Financial Institutions Examination Council. It is an estimate of the annual percentage rate on loans being offered to high-quality prime borrowers based on the contract interest rates and discount points reported by Freddie Mac in its Primary Mortgage Market Survey (www.ffiec.gov/ratespread/newcalc.aspxLeaving the Board ).

One factor that may help explain the drop in home-purchase lending between 2010 and 2011 is the ending of the first-time homebuyer tax credit program in April 2010.12 The first-time homebuyer tax credit program likely stimulated homebuying in the first half of 2010 as individuals sought to purchase their homes before the sunset date.13 Data from the National Association of Realtors (NAR) support this view: The NAR annual survey of home buyers and sellers indicates that first-time buyers accounted for about 47 percent of all home purchases in 2009 and half of home sales in 2010 before falling to a 37 percent share in 2011.14

To a greater extent than for home-purchase borrowing, the volume of refinance lending over time generally follows the path of interest rates (typically with a fairly short lag), expanding as mortgage rates fall and retrenching when rates rise. The interest rate environment over the past few years has generally been quite favorable for well-qualified borrowers who have sought to refinance. In some cases, the same individuals have refinanced on more than one occasion to take advantage of the declining interest rate environment. However, many other individuals with outstanding loans have not been able to refinance, either because they could not meet income-related or credit-history-related underwriting standards or because of collateral-related issues, including situations where the outstanding balance on the loan exceeds the home value.15

Compared with 2010, the number of reported refinance loans in 2011 was down about 13 percent (table 3.B). Although the total volume of refinancing in 2011 was down quite a bit from 2010, lenders experienced much higher demand in some months than others. In 2011, the peak month for refinance issuance was November, with nearly 504,000 loans, compared with only 230,000 loans in May (figure 1). The surge in refinance activity toward the end of 2011 reflects the steady drop in mortgage rates over the course of the year, which by November and December saw annual percentage offer rates on 30-year fixed-rate loans dip to about 4 percent.

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Non-Owner-Occupant Lending

Individuals buying homes either for investment purposes or as second or vacation homes are an important segment of the housing market in general, and in some areas of the country, they are particularly important. In the current period of high foreclosures and elevated levels of short sales, investor activity helps reduce the overhang of unsold and foreclosed properties. In some cases, investors or second-home buyers are able to purchase their properties for cash; in other cases, they choose to borrow and finance their purchases. Surveys sponsored by the NAR find that in 2011, about half of investors paid cash for their purchases and 42 percent of vacation-home buyers paid cash for their properties.16

The HMDA data help document the role of non-owner-occupant lending over time. The data show a sharp increase in non-owner-occupant lending used to purchase one- to four-family homes (site-built and manufactured properties) during the first half of the previous decade (table 4). The volume of non-owner-occupant lending fell sharply beginning in 2007 and has remained at comparably low levels through 2011. Although non-owner-occupant lending in 2011 remained subdued compared with levels reached in the middle of the previous decade, such lending did pick up from 2010, increasing nearly 10 percent.

As shown in table 4, the post-2007 decline in non-owner-occupant lending has been more severe than that in owner-occupant lending. Between 2000 and 2005, the share of non-owner-occupant lending used to purchase one- to four-family homes rose, increasing over this period from about 9 percent to 16 percent (data derived from table 4).17 The share fell to about 11 percent in both 2009 and 2010 but rebounded to 13 percent in 2011.

Table 4. Home loan applications and home loans for one- to four-family properties, by occupancy status of home and type of loan, 2000-11
Number
Year Applications Loans
Owner occupied Non-owner occupied Owner occupied Non-owner occupied
Conventional Non-
conventional1
Conventional Non-
conventional1
Conventional Non-
conventional1
Conventional Non-
conventional1
A. Home purchase
2000 6,350,643 1,311,101 604,919 12,524 3,411,887 963,345 404,133 8,378
2001 5,776,767 1,268,885 627,598 19,688 3,480,441 1,003,795 440,498 14,128
2002 5,511,048 1,133,770 747,758 13,923 3,967,834 870,599 547,963 8,474
2003 6,212,915 1,014,865 943,248 8,623 4,162,412 761,716 667,613 4,560
2004 7,651,113 799,131 1,335,241 6,839 4,946,423 574,841 906,014 2,710
2005 9,208,214 610,650 1,850,174 3,814 5,742,377 438,419 1,199,509 1,707
2006 8,695,877 576,043 1,653,154 3,792 5,281,485 416,744 1,040,668 1,425
2007 5,960,571 599,637 1,044,112 4,823 3,582,949 423,506 655,916 896
2008 2,940,059 1,424,483 647,340 6,116 1,727,692 972,605 415,930 3,465
2009 2,017,982 1,966,335 442,409 6,711 1,174,648 1,323,966 290,560 3,765
2010 1,822,790 1,763,826 425,345 5,853 1,090,328 1,169,729 284,700 1,833
2011 1,791,526 1,558,447 461,481 4,768 1,076,446 1,025,827 313,138 1,443
B. Refinance
2000 6,051,484 110,380 379,299 2,502 2,170,162 64,882 198,695 1,293
2001 12,737,863 705,784 823,748 17,592 6,836,106 524,228 516,616 12,181
2002 15,623,327 742,208 1,111,588 14,504 9,058,654 535,370 706,570 9,377
2003 21,779,329 1,236,467 1,563,430 23,310 13,205,472 895,735 1,007,674 15,871
2004 14,476,350 497,700 1,084,536 13,516 6,649,588 304,591 621,667 8,082
2005 14,494,441 262,438 1,135,929 5,538 6,336,004 158,474 603,914 3,257
2006 12,722,112 208,405 1,112,891 2,553 5,382,950 122,134 585,142 1,016
2007 10,173,282 375,860 1,012,827 4,213 4,123,507 196,897 496,577 894
2008 5,829,633 1,240,472 650,042 8,996 2,593,793 522,243 337,914 3,824
2009 7,290,061 2,058,210 619,286 15,211 4,414,509 1,000,911 349,147 7,511
2010 6,325,488 1,449,925 642,401 15,519 3,948,746 655,574 356,183 8,100
2011 5,550,634 1,136,045 682,769 21,242 3,401,097 512,839 384,911 13,023
C. Home improvement
2000 1,833,277 91,575 65,286 1,548 843,884 10,896 37,047 760
2001 1,771,472 16,276 60,598 1,143 788,560 6,722 32,990 548
2002 1,459,049 11,582 58,080 636 676,515 4,878 30,533 197
2003 1,430,380 13,876 63,806 325 642,065 5,226 31,113 103
2004 2,081,528 11,887 109,105 224 904,492 5,557 56,341 94
2005 2,401,030 10,053 127,857 218 1,026,340 4,483 62,298 70
2006 2,335,338 12,645 132,694 150 1,067,730 6,115 65,842 44
2007 2,072,688 16,717 128,700 119 887,123 9,409 61,321 59
2008 1,294,162 26,544 83,036 266 516,612 12,347 39,170 158
2009 743,968 28,536 58,754 246 349,993 11,256 28,568 164
2010 583,892 34,449 51,415 391 303,344 11,810 26,190 57
2011 581,023 38,194 60,763 6,808 293,735 14,392 27,768 3,532

1. Loans insured by the Federal Housing Administration or backed by guarantees from the U.S. Department of Veterans Affairs, the Farm Service Agency, or the Rural Housing Service. Return to table

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Conventional versus Government-Backed Loans

Although the total number of home-purchase loans has fallen substantially since 2005, virtually all of the decline has involved conventional lending; the volume of nonconventional home-purchase loans (sometimes referred to as "government backed" loans)--including loans backed by insurance from the FHA or by guarantees from the VA, the Farm Service Agency (FSA), or the Rural Housing Service (RHS)--has increased markedly since the mid-2000s. From 2006 to 2009, the total number of reported conventional home-purchase loans fell 77 percent, while the number of nonconventional home-purchase loans more than tripled (table 4). Although the number of nonconventional home-purchase loans has fallen since reaching its high mark in 2009, such loans still accounted for about 43 percent of home-purchase lending in 2011. The increase in nonconventional lending in recent years reflects several factors, such as increased loan-size limits allowed under the FHA and VA lending programs and reduced access (including more-stringent underwriting and higher prices) to conventional loans, particularly those that allow the borrower to finance more than 80 percent of the property value.18

Nonconventional lending has also garnered a larger share of the refinance market. In 2006, only 2 percent of refinance loans were nonconventional, compared with 12 percent in 2011. This share dropped some from 2010, as the number of nonconventional refinance loans fell about 21 percent (table 4).19

Table 5. Loans on manufactured homes, by occupancy status of home and type of loan, 2004-11
Number
Year Owner occupied Non-owner occupied
Conventional Nonconventional1 Conventional Nonconventional1
A. Home purchase
2004 107,686 23,974 16,243 125
2005 101,539 27,229 17,927 56
2006 102,458 30,530 19,105 257
2007 95,584 28,554 13,963 92
2008 68,821 27,615 11,392 93
2009 43,543 20,630 7,920 29
2010 44,856 17,086 7,655 29
2011 40,312 14,663 7,482 218
B. Refinance
2004 79,838 6,922 6,507 57
2005 73,520 7,727 6,331 26
2006 64,969 11,750 6,240 68
2007 59,591 16,174 6,332 74
2008 44,342 21,926 6,817 177
2009 37,001 21,768 6,002 73
2010 26,340 9,751 5,024 69
2011 25,299 8,919 4,765 161
C. Home improvement
2004 17,119 128 1,269 5
2005 20,239 219 1,372 3
2006 20,886 490 1,425 2
2007 19,428 889 1,494 2
2008 12,621 681 1,324 36
2009 9,781 439 1,116 1
2010 8,012 427 999 2
2011 8,244 349 972 75

1. See table 4, note 1. Return to table

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The Private Mortgage Insurance Market

In the conventional loan market, lenders typically require that a borrower seeking to purchase an owner-occupied property make a down payment of at least 20 percent of a home's value unless the borrower obtains some type of third-party backing, such as mortgage insurance. For a borrower seeking a conventional loan with a low down payment, a lender can require that the borrower purchase mortgage insurance from a private mortgage insurance (PMI) company to protect the lender against default-related losses up to a contractually established percentage of the principal amount. As a form of protection for lenders against losses from defaulting borrowers, PMI competes with FHA insurance and VA loan guarantees.

The seven companies that reported data for 2011 dominate the PMI industry.20 Thus, the reported data cover the vast majority of PMI written in the United States. For 2011, the seven PMI companies reported on nearly 409,000 applications for insurance leading to the issuance of 312,000 insurance policies, up from about 370,000 applications and 260,000 policies in 2010 (data derived from table 6). Reported volumes of PMI issuance in 2011, as in recent years, have been substantially smaller than levels prior to 2009. The large reduction in PMI issuance reflects several factors, including tighter underwriting adopted by the PMI companies in response to elevated claims and losses experienced during the recent recession and the ongoing recovery.21

Overall, 64 percent of the PMI policies issued in 2011 covered home-purchase loans, and the remainder covered refinance mortgages (home-improvement loans are classified as refinance loans by the PMI reporters). Virtually all of the applications for PMI policies issued involved loans to purchase site-built properties, and almost all of the applications for PMI related to owner-occupied units.

The data reported by the PMI industry over the years have consistently shown that most applications for insurance are approved, as lenders are very familiar with the underwriting policies of the insurers and generally are not going to submit an application that is unlikely to be approved. Overall, about 5 percent of PMI insurance applications were denied in 2011, down from about 10 percent in 2010 and 12 percent in 2009 but still notably higher than in 2006 and 2007, when only about 2 percent of the requests for insurance were turned down (data not shown in tables).22 As with the HMDA data, PMI companies report the reason for denial. The most commonly reported reason cited by lenders related to an issue with the collateral, most likely property value.

Table 6. Private mortgage insurance applications and issuance for one- to four-family properties,
by occupancy status of home and type of property, 2000-11
Number
Year Applications Issuance
Owner occupied Non-owner occupied Owner occupied Non-owner occupied
Site-built Manufactured housing1 Site-built Manufactured housing1 Site-built Manufactured housing1 Site-built Manufactured housing1
A. Home purchase
2000 1,204,520 n.a. 95,549 n.a. 955,988 n.a. 75,473 n.a.
2001 1,266,440 n.a. 122,639 n.a. 1,002,385 n.a. 90,929 n.a.
2002 1,324,958 n.a. 153,277 n.a. 1,022,754 n.a. 115,573 n.a.
2003 1,315,221 n.a. 175,958 n.a. 1,021,476 n.a. 134,677 n.a.
2004 1,078,275 10,111 192,086 1,287 807,480 7,508 143,917 984
2005 886,749 10,470 174,174 1,480 676,758 7,512 130,945 1,171
2006 838,304 9,526 134,545 1,273 659,755 6,655 98,744 993
2007 1,260,666 7,928 148,057 1,113 1,015,240 5,531 109,772 774
2008 928,978 4,082 127,773 759 591,108 2,012 66,842 367
2009 341,311 535 14,372 92 206,878 125 5,208 29
2010 214,054 172 7,644 11 154,716 55 4,750 0
2011 245,677 219 11,547 8 193,215 89 8,272 0
B. Refinance2
2000 259,245 n.a. 14,771 n.a. 185,721 n.a. 10,859 n.a.
2001 856,112 n.a. 29,870 n.a. 663,465 n.a. 17,453 n.a.
2002 1,056,788 n.a. 40,771 n.a. 775,020 n.a. 23,035 n.a.
2003 1,372,551 n.a. 46,139 n.a. 1,014,558 n.a. 27,116 n.a.
2004 597,353 6,037 31,352 233 389,563 3,956 17,243 138
2005 438,019 3,702 23,217 136 309,821 2,384 13,239 88
2006 346,978 2,554 24,201 121 234,587 1,567 14,187 78
2007 507,137 2,108 36,508 104 362,961 1,313 22,533 58
2008 454,405 1,442 33,822 123 257,189 695 11,519 34
2009 275,541 429 3,611 15 153,633 126 1,121 4
2010 145,953 135 1,437 2 99,598 56 587 0
2011 149,480 196 1,664 0 109,866 72 838 0

1. Before 2004, property type was not collected; totals for site-built and manufactured housing are shown in the "Site-built" column. Return to table

2. Includes home-improvement loans. Private mortgage insurance companies do not distinguish between refinance loans and home-improvement loans in reporting. Loan totals are the summation of refinance and home-improvement loans. Return to table

n.a. Not available.

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Junior-Lien Lending

Junior-lien loans can be taken out either in conjunction with the primary mortgage (a piggyback loan) or independently of the first-lien loan. As noted, piggyback loans can be used by borrowers to avoid having to pay for private or government mortgage insurance. Similarly, piggyback loans can also be used to reduce the size of the first-lien loan to be within the size limits required by Freddie Mac or Fannie Mae without requiring a larger down payment by the borrower. Junior-lien loans that are taken out independently of a first lien can be used for any number of purposes, including to finance home-improvement projects or, in the case of open-ended home equity lines of credit, to provide a readily available source of credit that can be drawn on at the time the borrower needs the funds. Under the regulations that govern HMDA reporting, most of these standalone junior-lien loans are not reported.23

In 2006, close to 1.3 million junior liens used for the purchase of owner-occupied properties were reported under HMDA (table 7). This number fell by more than one-half in 2007, dropped sharply again in each of the ensuing years, and decreased to less than 42,000 such loans in 2010 and 2011. More than 1 million junior-lien loans were taken out to refinance loans backed by owner-occupied properties in 2006, and this number also fell substantially starting in 2007 and continued to fall, reaching a low point of less than 74,000 in 2011.

The HMDA data also include information on junior-lien loans used for home-improvement purposes. In 2011, nearly 66,000 junior-lien loans were used for such a purpose, down some from about 80,000 reported in 2010. Both the 2010 and 2011 totals are sharply below the historic high mark of nearly 570,000 reached in 2006. Overall, junior-lien loans used for home improvement accounted for 35 percent of junior-lien loans reported under HMDA.

Table 7. Home loans for one- to four-family properties, by occupancy status of home, type of loan, and lien status, 2004-11
Number
Year Owner occupied Non-owner occupied
Conventional Nonconventional1 Conventional Nonconventional1
First lien Junior
lien
Unsecured2 First lien Junior
lien
Unsecured2 First lien Junior
lien
Unsecured2 First lien Junior
lien
Unsecured2
A. Home purchase
2004 4,209,787 736,636 . . . 573,606 1,235 . . . 853,490 52,524 . . . 2,703 7 . . .
2005 4,520,378 1,221,999 . . . 437,552 867 . . . 1,049,555 149,954 . . . 1,685 22 . . .
2006 4,013,196 1,268,289 . . . 416,143 601 . . . 878,325 162,343 . . . 1,407 18 . . .
2007 3,031,606 551,343 . . . 422,450 1,056 . . . 605,714 50,202 . . . 888 8 . . .
2008 1,636,194 91,498 . . . 971,528 1,077 . . . 410,377 5,553 . . . 3,461 4 . . .
2009 1,132,424 42,224 . . . 1,322,489 1,477 . . . 288,526 2,034 . . . 3,756 9 . . .
2010 1,049,990 40,338 . . . 1,168,343 1,386 . . . 283,017 1,683 . . . 1,821 12 . . .
2011 1,036,112 40,334 . . . 1,024,696 1,131 . . . 311,831 1,307 . . . 1,438 5 . . .
B. Refinance
2004 6,185,418 464,170 . . . 304,298 293 . . . 608,956 12,711 . . . 8,069 13 . . .
2005 5,607,642 728,362 . . . 158,198 276 . . . 578,491 25,423 . . . 3,236 21 . . .
2006 4,347,348 1,035,602 . . . 121,761 373 . . . 546,430 38,712 . . . 989 27 . . .
2007 3,462,944 660,563 . . . 196,544 353 . . . 473,336 23,241 . . . 879 15 . . .
2008 2,374,781 219,012 . . . 521,863 380 . . . 328,844 9,070 . . . 3,814 10 . . .
2009 4,300,322 114,187 . . . 1,000,422 489 . . . 342,410 6,737 . . . 7,495 16 . . .
2010 3,860,760 87,986 . . . 655,334 240 . . . 350,458 5,725 . . . 8,092 8 . . .
2011 3,327,415 73,682 . . . 512,629 210 . . . 379,519 5,392 . . . 13,004 19 . . .
C. Home improvement
2004 357,618 395,582 151,292 2,697 2,243 617 40,028 8,153 8,160 30 54 10
2005 409,947 468,375 148,018 2,197 1,873 413 42,544 10,756 8,998 17 49 4
2006 360,321 553,152 154,257 3,957 1,735 423 43,913 13,739 8,190 18 20 6
2007 301,078 435,187 150,858 7,510 1,579 320 41,670 11,508 8,143 35 18 6
2008 179,506 181,402 155,704 10,477 1,610 260 26,482 5,473 7,215 135 13 10
2009 166,865 84,414 98,714 8,197 2,541 518 19,961 3,193 5,414 99 28 37
2010 134,370 74,941 94,033 8,218 2,663 929 17,777 2,486 5,927 35 17 5
2011 129,851 60,423 103,461 7,116 2,949 4,327 18,491 2,257 7,020 64 45 3,423

1. See table 4, note 1. Return to table

2. Unsecured loans are collected only for home-improvement loans under the Home Mortgage Disclosure Act. Return to table

... Not applicable.

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Loan Sales

For each loan origination reported under HMDA in a given year, lenders report whether that loan was sold during the same year, and the type of institution to which the loan was sold.24 Broadly, these purchaser types can be broken into those that are government related--Ginnie Mae, Fannie Mae, Freddie Mac, and Farmer Mac--and those that are not. Ginnie Mae and Farmer Mac focus on loans backed directly by government guarantees or insurance, while Fannie Mae and Freddie Mac purchase conventional loans that meet certain loan-size and underwriting standards.

Overall, about 78 percent of the first-lien home-purchase and refinance loans for one- to four-family properties originated in 2011 were reported as sold during the year (data not shown in tables). The share of originations that are sold varies some from year to year and by type and purpose of loan (table 8).25 For example, 69 percent of the conventional loans extended in 2011 for the purchase of owner-occupied one- to four-family dwellings were sold that year. In contrast, nearly 94 percent of the nonconventional loans used to purchase owner-occupied homes were reported as sold in 2011. The share of conventional loans made to non-owner occupants that are reported as sold is notably smaller than that of such loans made to owner occupants. Also, the vast majority of conventional loans extended for the purchase of manufactured homes are held in portfolio; only about 10 percent of such loans were sold in 2011.

Table 8. Distribution of home loan sales for one- to four-family properties, by occupancy status of home and type of loan, 2000-11
Percent
Year Owner occupied Non-owner occupied
Conventional Nonconventional1 Conventional Nonconventional1
Share sold Memo: Share
sold to GSEs2
Share sold Memo: Share
sold to GSEs2
Share sold Memo: Share
sold to GSEs2
Share sold Memo: Share
sold to GSEs2
A. Home purchase
2000 64.8 31.3 89.1 46.0 53.7 29.3 81.4 22.9
2001 66.8 34.6 86.1 46.2 57.9 34.0 92.2 23.0
2002 71.0 36.7 88.7 43.7 62.5 36.4 87.9 29.7
2003 72.3 33.1 91.2 40.7 63.1 31.8 80.8 21.6
2004 74.2 25.5 92.2 40.5 63.5 23.6 63.7 11.5
2005 75.9 18.7 89.9 32.6 69.7 18.0 49.7 16.3
2006 74.8 19.0 88.6 31.7 69.3 19.0 61.3 15.0
2007 70.1 29.1 87.6 32.5 61.4 26.9 74.9 27.6
2008 71.6 40.1 90.0 36.5 60.3 36.3 95.1 21.6
2009 70.1 40.1 91.4 35.0 56.4 34.7 88.9 35.2
2010 69.7 37.0 92.7 29.7 30.3 34.8 91.7 24.1
2011 68.9 34.2 93.5 33.4 61.9 34.5 80.3 35.2
B. Refinance
2000 47.4 18.0 84.5 50.0 47.3 21.7 86.3 42.8
2001 61.3 37.2 85.0 51.5 61.2 38.4 92.1 33.2
2002 66.8 40.4 85.7 45.0 65.9 43.2 81.3 45.4
2003 74.2 44.8 93.8 48.0 69.8 40.4 87.4 50.7
2004 69.0 27.6 93.2 44.2 62.2 22.6 88.0 35.9
2005 69.9 19.7 89.3 33.5 64.7 16.6 85.7 40.1
2006 65.7 15.2 86.8 31.8 64.9 15.7 79.0 29.6
2007 61.7 21.9 85.1 34.5 61.1 23.9 86.9 23.9
2008 65.3 38.0 88.8 35.4 56.8 33.0 95.7 20.4
2009 79.4 52.8 89.7 37.9 61.2 40.1 93.5 36.0
2010 76.8 46.1 90.2 37.8 65.4 40.3 90.5 43.8
2011 72.7 46.4 91.3 49.8 66.4 43.5 89.5 57.6
C. Home improvement
2000 6.3 1.1 15.6 4.7 4.4 .4 52.9 .5
2001 6.4 1.5 22.3 7.6 3.9 .8 73.7 1.1
2002 5.9 1.4 28.4 7.1 4.0 .9 55.3 3.6
2003 10.5 .8 43.8 6.7 6.5 .7 35.0 3.9
2004 23.6 6.0 48.7 23.5 23.1 7.5 20.2 7.4
2005 27.2 7.0 46.2 25.3 30.2 8.8 27.1 8.6
2006 22.0 5.3 60.4 31.8 29.4 8.9 29.5 15.9
2007 19.1 6.4 70.6 30.8 26.4 12.1 39.0 11.9
2008 14.7 8.7 80.0 49.2 20.0 14.5 74.7 6.3
2009 24.9 17.8 63.4 38.9 17.7 13.4 56.1 9.8
2010 21.2 13.2 60.6 34.7 18.3 12.6 47.4 28.1
2011 19.1 11.4 45.3 26.8 19.8 13.4 .3 .1

1. See table 4, note 1. Return to table

2. Loans sold to government-sponsored enterprises (GSEs) include those with a purchaser type of Fannie Mae, Freddie Mac, Ginnie Mae, or Farmer Mac. Return to table

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Borrower Incomes and Loan Amounts

Under HMDA, lenders report the loan amount applied for and the applicant income that the lender relied on in making the credit decision, if income was considered in the underwriting decision. Lenders do not necessarily collect and report loan applicants' entire income, because in some cases borrowers have more income than is needed to qualify for the loan.

Borrower Income

The vast majority of loan applications and loans reported under HMDA include income information. For example, in 2011, income information was not reported for less than 1 percent of the borrowers purchasing a home with a nonconventional loan and for 3 percent of those using a conventional loan (data not shown in tables). Income information is reported less often for refinance loans, particularly those that are nonconventional (about one-third of the FHA loans and 63 percent of the VA loans), most likely because of streamlined refinance programs that do not require current income to be considered in underwriting.

While the available information on amounts borrowed and applicant income can be evaluated in many ways, we focus here on patterns by loan product and purpose. For home-purchase or refinance lending, borrowers using FHA and VA loans have lower mean or median incomes than borrowers using other loans, despite the fact that the FHA (and VA) loan limits were increased substantially in 2008, potentially allowing the program to be used much more widely than by the LMI households that have been the traditional focus of the program (table 9). Although the share of FHA home-purchase borrowers with incomes above $100,000 has roughly doubled since 2007 (the year before the increase in loan limits) to about 15 percent, the median income of borrowers getting FHA home-purchase loans was still about 30 percent lower than that of those getting conventional loans (data derived from table 9). The relatively low down-payment requirements on FHA-insured loans--the average loan-to-value ratio for FHA home-purchase loans was over 95 percent in 2011--may be continuing to attract lower-income borrowers.26

Table 9. Cumulative distribution of home loans, by borrower income and by purpose and type of loan, 2011
Percent
Upper bound of
borrower income (thousands of dollars)1
Home purchase Refinance
FHA VA Conventional2 Total Memo:
Higher
priced3
FHA VA Conventional2 Total Memo:
Higher
priced3
24 5.3 1.1 3.2 3.7 9.5 3.5 2.3 2.4 2.4 10.2
49 41.5 23.2 25.4 31.0 48.3 28.2 19.5 16.6 17.4 41.5
74 69.4 56.7 47.0 55.9 72.2 58.1 48.0 36.8 38.4 67.2
99 84.9 77.0 62.6 71.9 83.9 77.8 69.3 54.9 56.6 81.8
124 92.5 88.4 73.9 81.9 89.8 88.6 83.1 68.9 70.4 89.4
149 96.1 94.0 81.3 87.8 92.9 93.9 90.5 78.2 79.4 93.2
199 98.7 98.2 89.6 93.7 95.9 98.0 96.6 88.4 89.2 96.4
249 99.4 99.4 93.7 96.3 97.2 99.2 98.7 93.1 93.6 97.7
299 99.7 99.7 95.8 97.5 98.0 99.6 99.4 95.4 95.8 98.3
More than 299 100 100 100 100 100 100 100 100 100 100
Memo: Borrower income, by selected loan type (thousands of dollars)1
Mean 66.3 79.0 111.1 92.1 73.2 76.9 88.0 121.9 118.3 76.5
Median 56 69 79 68 51 67 76 92 90 56

Note: First-lien mortgages for owner-occupied, one- to four-family, site-built properties; excludes business loans. Business-related loans are those for which the lender reported that the race, ethnicity, and sex of the applicant or co-applicant are "not applicable." For loans with two or more applicants, lenders covered under the Home Mortgage Disclosure Act (HMDA) report data on only two. Income for two applicants is reported jointly.

1. Income amounts are reported under HMDA to the nearest $1,000. Return to table

2. Conventional loans plus some loans originated with a Farm Service Agency or Rural Housing Service guarantee. Return to table

3. Higher-priced loans are those with annual percentage rates 1.5 percentage points or more above the average prime offer rate for loans of a similar type published weekly by the Federal Financial Institutions Examination Council. Return to table

FHA Federal Housing Administration.

VA Department of Veterans Affairs.

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Loan Amounts

Unlike the data on borrower incomes, loan amounts are provided for all applications and loans reported in the HMDA data. Loan amounts differ across loan types, with FHA or VA loans, on average, being smaller than conventional loans (which make up most of the "other" category in table 10). However, an upward shift in the distribution of loan amounts for both FHA and VA home-purchase loans has occurred in the past couple of years, continuing into 2011 (data for only 2011 shown in tables). The shift reflects several factors, including the higher loan limits allowed under these programs.

Table 10. Cumulative distribution of home loans, by loan amount and by purpose and type of loan, 2011
Percent
Upper bound of
loan amount (thousands of
dollars)1
Home purchase Refinance
FHA VA Conventional2 Total Memo:
Higher
priced3
FHA VA Conventional2 Total Memo:
Higher
priced3
24 .1 .0 .5 .3 2.8 .1 .0 .5 .5 4.3
49 2.0 .4 3.2 2.5 13.9 1.6 .7 3.3 3.0 16.8
74 9.6 2.6 9.7 9.0 29.8 7.4 3.9 10.3 9.8 32.8
99 22.1 7.8 18.3 18.7 44.9 17.3 10.5 20.2 19.5 47.5
149 50.9 28.3 38.9 42.2 68.8 44.5 32.9 41.2 41.1 68.4
199 71.7 53.6 55.1 60.9 82.0 66.5 55.8 58.1 58.7 80.3
274 88.5 77.5 71.9 78.4 91.2 85.3 77.6 74.7 75.8 89.4
417 97.4 94.5 88.8 92.4 96.9 96.0 94.6 92.0 92.5 96.9
625 99.6 99.1 96.0 97.6 98.8 99.3 99.0 97.0 97.3 99.0
729 99.9 99.7 97.4 98.5 99.2 99.9 99.6 98.1 98.3 99.3
More than 799 100 100 100 100 100 100 100 100 100 100
Memo: Loan amount (thousands of dollars)
Mean 170.2 217.2 234.7 210.1 141.6 185.3 212.9 220.3 217.0 141.6
Median1 147 191 180 167 109 160 185 173 172 104

Note: First-lien mortgages for owner-occupied, one- to four-family, site-built properties; excludes business loans. Business-related loans are those for which the lender reported that the race, ethnicity, and sex of the applicant or co-applicant are "not applicable."

1. Loan amounts are reported under the Home Mortgage Disclosure Act to the nearest $1,000. Return to table

2. See table 9, note 2. Return to table

3. See table 9, note 3. Return to table

FHA Federal Housing Administration.

VA Department of Veterans Affairs.

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Application Disposition, Loan Pricing, and Status under the Home Ownership and Equity Protection Act

In tables 11 and 12, we categorize every loan application and request for preapproval reported in 2011 into 25 distinct product categories characterized by type of loan and property, purpose of loan, and lien and owner-occupancy status. Each product category contains information on the number of total and preapproval applications, application denials, originated loans, loans with prices above the reporting thresholds established by HMDA reporting rules for identifying higher-priced loans, loans covered by the Home Ownership and Equity Protection Act of 1994 (HOEPA), and the mean and median annual percentage rate (APR) spreads for loans reported as higher priced.

Disposition of Applications

As noted, the 2011 HMDA data include information on 11.7 million loan applications, nearly 86 percent of which were acted on by the lender (data derived from table 11). With respect to the disposition of applications, patterns of denial rates are largely consistent with what had been observed in earlier years.27 Denial rates on applications for home-purchase loans are notably lower than those observed on applications for refinance or home-improvement loans. Denial rates on applications backed by manufactured housing are much higher than those on applications backed by site-built homes. For example, the denial rate for first-lien conventional home-purchase loan applications for owner-occupied site-built properties was 14.8 percent in 2011, compared with a denial rate of 52.7 percent for such applications for owner-occupied manufactured homes.

Table 11. Disposition of applications for home loans, and origination and pricing of loans, by type of home and type of loan, 2011
Type of home and loan Applications
Number submitted Acted upon by lender
Number Number denied Percent denied
1-4 Family
Nonbusiness related3
Owner occupied
Site built
Home purchase
Conventional
First lien 1,438,327 1,260,646 186,025 14.8
Junior lien 57,851 50,569 7,915 15.7
Government backed
First lien 1,450,709 1,274,493 203,893 16.0
Junior lien 1,930 1,407 233 16.6
Refinance
Conventional
First lien 5,367,738 4,595,645 1,021,597 22.2
Junior lien 122,890 113,873 36,232 31.8
Government backed
First lien 1,115,624 829,981 264,225 31.8
Junior lien 354 262 57 21.8
Home improvement
Conventional
First lien 211,771 187,603 51,680 27.5
Junior lien 131,977 123,254 57,825 46.9
Government backed
First lien 15,879 11,175 3,407 30.5
Junior lien 8,455 6,705 3,476 51.8
Unsecured (conventional or government backed) 230,011 224,145 113,447 50.6
Manufactured
Conventional, first lien
Home purchase 196,525 189,483 99,788 52.7
Refinance 51,727 46,960 18,555 39.5
Other 70,033 62,119 22,064 35.5
Non-owner occupied4
Conventional, first lien
Home purchase 417,027 368,926 58,290 15.8
Refinance 648,094 548,887 161,447 29.4
Other 98,538 88,891 36,593 41.2
Table 11. Disposition of applications for home loans, and origination and pricing of loans, by type of home and type of loan, 2011 --continued
Type of home
and loan
Loans originated
Number Loans with APOR spread above the threshold1
Number Percent Distribution, by percentage points of APOR spread APOR spread (percentage points) Number of HOEPA-
covered loans2
1.5-1.99 2-2.49 2.5-2.99 3-3.99 4-4.99 5 or more Mean Median
1-4 Family
Nonbusiness related3
Owner occupied
Site built
Home purchase
Conventional
First lien 995,061 38,660 3.9 41.6 22.0 13.3 14.6 5.8 2.9 2.5 2.1 . . .
Junior lien 39,943 5,465 13.7 . . . . . . . . . 38.6 48.1 13.3 4.5 4.2 . . .
Government backed
First lien 1,009,654 28,592 2.8 71.3 21.5 3.2 1.1 2.1 .9 2.0 1.8 . . .
Junior lien 1,115 4 .4 . . . . . . . . . 25.0 50.0 25.0 5.2 4.8 . . .
Refinance
Conventional
First lien 3,299,037 51,664 1.6 46.8 16.6 11.0 13.6 6.0 6.1 2.6 2.1 735
Junior lien 71,341 9,550 13.4 . . . . . . . . . 30.0 38.9 31.2 4.8 4.5 201
Government backed
First lien 503,259 29,744 5.9 31.7 26.0 20.5 19.6 1.7 .4 2.5 2.3 46
Junior lien 190 6 3.2 . . . . . . . . . . . . 66.7 33.3 4.9 4.8 0
Home improvement
Conventional
First lien 126,491 10,663 8.4 29.0 16.8 13.8 17.8 7.9 14.8 3.2 2.6 366
Junior lien 59,607 6,781 11.4 . . . . . . . . . 30.8 33.5 35.7 4.9 4.5 187
Government backed
First lien 6,846 1,723 25.2 18.8 23.0 26.2 25.5 2.8 3.7 2.8 2.6 10
Junior lien 2,914 2,472 84.8 . . . . . . . . . 3.0 5.9 91.1 7.0 7.1 0
Unsecured
(conventional or government backed)
102,899 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Manufactured
Conventional, first lien
Home purchase 39,960 32,623 81.6 4.5 3.4 5.3 13.8 16.2 56.7 5.7 5.4 . . .
Refinance 24,477 7,933 32.4 17.1 9.7 10.8 21.9 16.5 24.0 3.9 3.6 577
Other 33,238 5,777 17.4 32.9 15.6 9.9 14.0 10.6 17.0 4.1 2.6 214
Non-owner occupied4
Conventional, first lien
Home purchase 285,333 13,696 4.8 46.4 16.6 11.2 13.6 5.6 6.6 2.6 2.1 . . .
Refinance 355,243 13,207 3.7 59.1 14.9 8.6 10.3 4.5 2.7 2.3 1.8 32
Other 48,084 2,760 5.7 24.6 12.7 7.5 19.8 17.5 17.9 3.5 3.4 13

1. Average prime offer rate (APOR) spread is the difference between the annual percentage rate on the loan and the APOR for loans of a similar type published weekly by the Federal Financial Institutions Examination Council. The threshold for first-lien loans is a spread of 1.5 percentage points; for junior-lien loans, it is a spread of 3.5 percentage points. Return to table

2. Loans covered by the Home Ownership and Equity Protection Act of 1994 (HOEPA), which does not apply to home-purchase loans. Return to table

3. Business-related applications and loans are those for which the lender reported that the race, ethnicity, and sex of the applicant or co-applicant are "not applicable"; all other applications and loans are nonbusiness related. Return to table

4. Includes applications and loans for which occupancy status was missing. Return to table

... Not applicable.

Table 11. Disposition of applications for home loans, and origination and pricing of loans, by type of home and type of loan, 2011 --continued
Type of home and loan Applications
Number submitted Acted upon by lender
Number Number denied Percent denied
Business related3
Conventional, first lien
Home purchase 30,458 29,464 1,066 3.6
Refinance 31,687 30,609 1,813 5.9
Other 10,157 8,904 983 11.0
Multifamily5
Conventional, first lien
Home purchase 10,146 9,367 1,106 11.8
Refinance 19,588 18,303 2,410 13.2
Other 5,314 4,904 719 14.7
Total 11,742,810 10,086,575 2,354,846 23.3

5. Includes business-related and nonbusiness-related applications and loans for owner-occupied and non-owner-occupied properties. Return to table

Table 11. Disposition of applications for home loans, and origination and pricing of loans, by type of home and type of loan, 2011 --continued
Type of home
and loan
Loans originated
Number Loans with APOR spread above the threshold1
Number Percent Distribution, by percentage points of APOR spread APOR spread (percentage points) Number of HOEPA-
covered loans2
1.5-1.99 2-2.49 2.5-2.99 3-3.99 4-4.99 5 or more Mean Median
Business related3
Conventional, first lien
Home purchase 27,589 564 2.0 24.8 24.5 22.9 24.3 2.7 .9 2.6 2.5 . . .
Refinance 28,177 549 1.9 25.7 21.0 26.6 18.9 6.4 1.5 2.6 2.5 2
Other 7,693 119 1.5 17.7 15.1 13.5 23.5 20.2 10.1 3.3 3.3 . . .
Multifamily5
Conventional, first lien
Home purchase 7,848 166 2.1 27.7 28.3 19.3 18.1 3.0 3.6 2.6 2.4 . . .
Refinance 15,238 229 1.5 27.5 26.2 18.3 15.7 6.6 5.7 2.7 2.4 1
Other 4,025 42 1.0 11.9 28.6 14.3 19.1 7.1 19.1 3.5 2.9 3
Total 7,095,262 262,989 3.7 35.5 15.6 9.9 15.0 9.6 14.4 3.2 2.5 2,387

Under the provisions of HMDA, reporting institutions may choose to report the reasons they provide consumers whose applications are turned down. Reporting institutions may cite up to three reasons for each denied application, although most of those that provide this information cite only one reason. An analysis of the reasons for denial provided to prospective borrowers whose applications for conventional credit for the purchase of owner-occupied homes were turned down finds that collateral-related issues and debt-to-income considerations were the two categories of reasons that have seen the largest increase since 2006 (data not shown in tables). Debt-to-income issues were also cited somewhat more often for applications for FHA or VA home-purchase loans, but collateral was the category that had the largest percentage increase. These relationships are not surprising, given the changes in underwriting practices and the widespread decline in home values since 2006.

In addition to the application data provided under HMDA, nearly 430,000 requests for preapproval were reported as acted on by the lender in 2011, down about 3 percent from 2010 (table 12). The majority of requests for preapprovals involved conventional loans. About 30 percent of these requests for preapproval were denied by the lender in 2011, a proportion that is higher than in 2010. Not unexpectedly, the number of requests for preapproval is down substantially from the levels recorded at the height of the housing boom, when market conditions favored home sellers and preapproval letters were a factor that enhanced the position of prospective homebuyers. In 2006, covered institutions reported that they received nearly 1.2 million requests for preapproval on which they took action (data not shown in tables).

Table 12. Home-purchase lending that began with a request for preapproval: Disposition and pricing,
by type of home, 2011
Type
of home
Requests for preapproval Applications preceded
by requests
for preapproval1
Loan originations whose applications were preceded by requests
for preapproval
Number
acted
upon
by lender
Number denied Per-
cent denied
Number sub-
mitted
Acted upon
by lender
Number Loans with APOR spread above the threshold2
Number Number denied Num-
ber
Per-
cent
Distribution, by percentage points of APOR spread APOR spread (percentage
points)
1.5-
1.99
2-
2.49
2.5-
2.99
3-
3.99
4-
4.99
5 or
more
Mean spread Median spread
1-4 Family
Nonbusiness related3
Owner occupied
Site built
Conventional
First lien 217,757 57,848 27 123,940 19,888 16,177 81,794 1,771 2.2 44.5 19.6 10.1 11.2 9.9 4.7 2.6 2.1
Junior lien 7,396 945 13 5,820 354 147 5,184 1,058 20.4 . . . . . . . . . 29.1 61.8 9.1 4.3 4.3
Government
backed
First lien 160,904 62,602 39 86,517 11,279 10,616 61,790 2,568 4.2 71.0 16.4 5.5 1.8 2.3 3.0 2.1 1.8
Junior lien 146 17 12 126 32 11 83 2 2.4 . . . . . . . . . . . . 100 . . . 4.8 4.8
Manufactured
Conventional, first lien 3,392 1,008 30 2,282 322 469 1,252 729 58.2 5.2 2.6 5.6 8.4 10.3 67.9 6.9 6.5
Other 2,625 1,092 42 1,474 227 172 1,047 36 3.4 83.3 11.1 5.6 . . . . . . . . . 1.8 1.8
Non-owner occupied4
Conventional, first lien 35,912 7,019 20 22,454 3,355 2,372 15,514 502 3.2 50.6 18.5 9.6 11.4 6.4 3.6 2.4 2.0
Other 725 322 44 361 91 135 115 11 9.6 36.4 36.4 9.1 9.1 . . . 9.1 2.6 2.1
Business related3
Conventional, first lien 499 27 5 457 39 35 361 14 3.9 21.4 21.4 21.4 35.7 . . . . . . 2.6 2.7
Other 90 12 13 77 10 22 42 1 2.4 100 . . . . . . . . . . . . . . . 1.5 1.5
Multifamily5
Conventional, first lien 70 2 3 65 6 10 48 5 10.4 . . . 40.0 20.0 40.0 . . . . . . 2.9 2.6
Other 3 0 0 3 1 0 2 1 50.0 . . . . . . . . . . . . 100 . . . 4.1 4.1
Total 429,519 130,894 30 243,576 35,604 30,166 167,232 6,698 4.0 43.9 13.3 6.2 10.1 14.9 11.5 3.1 2.2

1. These applications are included in the total reported in table 11. Return to table

2. See table 11, note 1. Return to table

3. See table 11, note 3. Return to table

4. See table 11, note 4. Return to table

5. See table 11, note 5. Return to table

... Not applicable.

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The Incidence of Higher-Priced Lending

Price-reporting rules under HMDA since late 2009 define higher-priced first-lien loans as those with an APR of at least 1.5 percentage points above the average prime offer rate (APOR) for loans of a similar type (for example, a 30-year fixed-rate mortgage).28 The spread for junior-lien loans must be at least 3.5 percentage points to be considered higher priced. The APOR, which is published weekly by the FFIEC, is an estimate of the APR on loans being offered to high-quality prime borrowers based on the contract interest rates and discount points reported by Freddie Mac in its Primary Mortgage Market Survey (PMMS).29

The data show that the incidence of higher-priced lending across all products in 2011 was about 3.7 percent, up about 50 basis points, or 0.5 percentage point, from 2010 (table 11).30 The incidence varies across loan types, products, and purposes. First, in almost all cases, nonconventional loans have a lower incidence of higher-priced lending than do comparable conventional loan products, although the differences in incidence are much smaller than in the period when many conventional loans were subprime or near prime. In 2011, among first-lien home-purchase loans for site-built homes, 3.9 percent of conventional loans had APRs above the price-reporting threshold, versus 2.8 percent of nonconventional loans. (Among nonconventional loans, those backed by VA guarantees have a particularly low incidence of being higher priced: In 2011, less than 0.04 percent of the VA-guaranteed first-lien home-purchase loans were higher priced.)

Second, with few exceptions, first-lien loans have a lower incidence of higher-priced lending than do junior-lien loans for the same purposes. For example, in 2011, the incidence of higher-priced lending for conventional first-lien refinance loans was 1.6 percent, whereas for comparable junior-lien loans it was 13.4 percent. This relationship is found despite the fact that the threshold for reporting a junior-lien loan as higher priced is 2 percentage points higher than it is for so reporting a first-lien loan. Third, manufactured-home loans exhibit the greatest incidence of higher-priced lending across all loan categories. For 2011, nearly 82 percent of the conventional first-lien loans used to purchase manufactured homes were higher priced.

The HMDA data also show that the incidence of higher-priced lending is related to borrower incomes and the amounts borrowed, with borrowers with lower incomes and those receiving smaller loans more likely to obtain a higher-priced loan. For example, 56 percent of home-purchase loans were extended to borrowers with incomes under $75,000, while such borrowers account for 72 percent of all higher-priced home-purchase loans (table 9). Across loan amounts, 19 percent of home-purchase loans were under $100,000, whereas 45 percent of higher-priced home-purchase loans were under $100,000 (table 10).

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Rate Spreads for Higher-Priced Loans

In 2011, the mean APOR spread reported for higher-priced first-lien conventional loans for the purchase of an owner-occupied site-built home was about 2.5 percentage points, compared with about 2.0 percentage points for higher-priced first-lien nonconventional loans used for the same purpose (table 11). Average spreads for first-lien conventional and government-backed refinance loans were 2.5 percentage points and 2.6 percentage points, respectively.

It is worth noting that the vast majority of nonconventional loans reported as higher priced in 2011 exceeded the HMDA price-reporting thresholds by only a small amount: Specifically, 71 percent of the higher-priced nonconventional first-lien home-purchase loans had reported spreads within 50 basis points of the threshold. By comparison, only about 42 percent of the comparable conventional loans reported as higher priced had prices this close to the margin of reporting. In contrast, the share of higher-priced nonconventional refinancing loans with APORs close to the margin of reporting (32 percent) is a little less than the share of higher-priced conventional refinancing loans with such APORs (about 47 percent).

As expected, consistent with the higher reporting threshold of junior-lien lending, higher-priced junior-lien loan products have higher mean and median APOR spreads than do higher-priced first-lien loans. Higher-priced loans for manufactured homes differ from other loan products in that they generally have the highest mean spreads. In 2011, the typical higher-priced conventional first-lien loan to purchase a manufactured home had a reported spread of about 5.7 percentage points, compared with an average spread of roughly 2.5 percentage points for comparable higher-priced loans for site-built properties.

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HOEPA Loans

The HMDA data indicate which loans are covered by the protections afforded by HOEPA. Under HOEPA, certain types of mortgage loans that have interest rates or fees above specified levels require additional disclosures to consumers and are subject to various restrictions on loan terms.31 For 2011, 574 lenders reported extending 2,387 loans covered by HOEPA (table 11; data regarding lenders not shown in tables). In comparison, 655 lenders reported on about 3,400 loans covered by HOEPA in 2010. In the aggregate, HOEPA-related lending made up less than 0.05 percent of all the originations of home-secured refinancings and home-improvement loans reported for 2011 (data derived from tables).32

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Lender Concentration in the Mortgage Market

Recent press accounts have highlighted the outsized role of a few larger lending organizations in the mortgage market.33 Table 13 lists the top 10 mortgage originating organizations (inclusive of their reporting mortgage lending affiliates and subsidiaries) according to the HMDA data. Wells Fargo tops the list, having originated over 900,000 loans in 2011, which translates into a market share of about 13 percent.34 JPMorgan Chase and Bank of America each had a market share of over 5 percent, followed by U.S. Bank and Quicken Loans with over 2 percent. Wells Fargo, JPMorgan Chase, and Bank of America had considerably larger market shares in 2011 than in 2006, in part because of their acquisitions of Wachovia, Washington Mutual, and Countrywide, respectively. The remainder of the top 10 organizations had market shares under 2 percent, and the top 10 collectively issued about 37 percent of all mortgage originations reported in the HMDA data in 2011, roughly the same as in 2006.

Table 13. Home loan originations and purchases by top 10 originators, 2011 and 2006
Percent except as noted
Organization Loans originated1 Loans purchased2
Number Market
share
Home
purchase
Refi-
nance
Conventional only Number Conven-
tional
Conventional only
Home
purchase (as a share of all home purchase)
Refinance
(as a share
of all
refinance)
Held in
portfolio3
Held in
portfolio
or sold to
affiliate3
Held in
portfolio3
Held in
portfolio
or sold to
affiliate3
2011
1. Wells Fargo & Co. 908,962 13.4 31.2 67.1 53.8 87.2 7.4 7.8 845,871 47.4 5.3 5.3
2. JPMorgan Chase & Co. 470,760 6.9 8.1 91.6 57.0 97.2 3.5 42.6 300,092 46.0 4.1 40.2
3. Bank of America Corp. 343,471 5.1 28.7 69.9 57.6 88.6 13.7 13.9 442,416 36.4 23.5 23.5
4. U.S. Bancorp 164,937 2.4 24.6 72.4 65.6 92.3 37.9 37.9 114,128 61.0 1.5 1.5
5. Quicken Loans, Inc. 143,870 2.1 8.4 91.6 42.6 64.2 .2 .2 0 n.a. n.a. n.a.
6. Citigroup 113,468 1.7 13.0 84.3 93.6 96.1 46.2 61.9 252,128 91.2 13.3 53.0
7. Fifth Third Bancorp 101,956 1.5 26.8 72.4 54.5 92.2 29.6 40.0 15,014 68.7 5.5 5.5
8. Flagstar Bank, FSB 92,875 1.4 39.2 58.8 49.8 82.0 .7 .7 32,249 43.2 6.4 6.4
9. Ally Financial 83,123 1.2 16.6 80.7 83.1 94.0 2.1 99.4 431,925 81.6 .5 38.3
10. SunTrust Bank 80,375 1.2 36.1 63.9 69.1 92.8 5.9 12.5 31,433 74.1 55.7 55.7
Total 2,503,797 36.9 23.7 74.9 57.4 89.3 11.7 25.5 2,465,256 56.8 8.3 27.4
Memo: All other organizations 4,284,175 63.1 41.7 55.4 56.7 86.3 34.9 36.8 479,406 61.4 21.2 21.6
2006
1. Countrywide 872,732 8.1 50.4 45.9 92.1 98.6 3.5 13.5 1,409,623 95.6 8.0 29.5
2. Wells Fargo & Co. 697,593 6.5 58.8 37.0 89.7 96.2 24.4 24.8 411,346 72.4 17.0 17.0
3. Bank of America Corp. 356,300 3.3 57.5 34.9 97.7 99.1 41.6 41.8 193,761 99.9 58.6 58.6
4. Wachovia Corp. 341,218 3.2 29.7 64.4 95.6 99.5 48.4 64.0 61,525 99.8 55.0 83.3
5. JPMorgan Chase & Co. 317,755 3.0 44.6 52.1 91.1 98.0 6.0 100.0 204,632 89.0 37.8 99.4
6. National City Corp. 278,426 2.6 60.9 36.5 92.1 94.2 4.2 52.1 6,206 95.8 .0 95.2
7. Washington Mutual Bank, FSB 270,278 2.5 29.8 66.0 98.7 98.9 40.7 42.8 415,199 96.7 12.1 12.7
8. GMAC Bank 248,050 2.3 41.6 58.3 92.1 97.7 2.3 73.6 862,978 96.7 10.0 20.2
9. Citigroup 215,454 2.0 30.2 62.3 97.0 98.5 48.0 60.6 616,319 91.4 54.1 70.8
10. HSBC Holdings, PLC 194,308 1.8 27.7 58.0 95.5 99.4 40.7 48.8 306,585 100.0 64.4 66.8
Total 3,792,114 35.2 46.7 48.5 92.9 98.1 22.6 43.5 4,488,174 93.4 24.8 38.8
Memo: All other organizations 6,979,080 64.8 50.9 45.8 91.8 97.2 26.7 31.5 1,748,178 94.4 38.4 54.9

1. First-lien mortgages for owner-occupied one- to four-family homes. Return to table

2. All liens are included because lien status is not always available. Return to table

3. "Held in portfolio" refers to loans held beyond the year of origination or purchase; excludes loans originated or purchased during the last quarter of the year. Return to table

n.a. Not available.

Notably, market shares derived from the HMDA data differ markedly from market shares recently reported in the press based on information compiled by Inside Mortgage Finance. It is important to note that for HMDA reporting purposes, institutions report only mortgage applications in which they make the credit decision. Under HMDA, if an application is approved by a third party (such as a correspondent) rather than the lending institution, then that party reports the loan as its own origination and the lending institution reports the loan as a purchased loan. Alternatively, if a third party forwards an application to the lending institution for approval, then the lending institution reports the application under HMDA (and the third party does not report anything). In contrast, Inside Mortgage Finance considers loans to have been originated by the acquiring institution even if a third party makes the credit decision. Thus, many of the larger lending organizations that work with sizable networks of correspondents report considerable volumes of purchased loans in the HMDA data, while Inside Mortgage Finance considers many of these purchased loans to be originations.

To be sure, both market share numbers are important for understanding the supply side of the mortgage market. The HMDA data, by focusing on the entity that makes the approval decision, highlight that the mortgage market continues to be highly decentralized along certain dimensions, with a large number of relatively small entities operating at the retail level, working with mortgage applicants, evaluating their applications, and making lending decisions. That said, overall credit availability and pricing depend on a multitude of additional factors, such as government-sponsored enterprise and FHA practices, lenders' willingness and ability to take risk, competition between wholesale lenders, and general credit conditions and investor appetite for risk.

Table 13 shows that among the top 10 organizations, many of them reported a large number of purchased loans in 2011, particularly Wells Fargo, Bank of America, and Ally Financial. As discussed earlier, many of these purchases are likely to be from correspondents, though it is not possible from the HMDA data to determine how many. It is also worth noting that organizations often turn around and resell loans that they purchased (see last two columns of table 13).

Finally, the HMDA data indicate that the business strategies among the top 10 organizations appear to vary considerably. For example, around 30 percent of Wells Fargo's and Bank of America's originations were for home-purchase loans, compared with less than 10 percent for JPMorgan Chase and Quicken Loans. Citigroup and Ally Financial concentrated relatively more heavily on refinance loans than on home-purchase loans. These institutions also differ considerably in terms of the fraction of loans held in portfolio beyond the year of origination.35 For example, U.S. Bancorp and Citigroup each held in portfolio 40 percent or more of the conventional loans they originated, compared with less than 10 percent for Wells Fargo and JPMorgan Chase. The HMDA data also reveal considerable variation across these larger lenders in the types of loans (conventional compared with FHA, VA, or FSA) they tend to extend. For example, about half of the home-purchase loans reported by Wells Fargo were conventional, whereas about 90 percent of those originated by Citigroup were of this type.

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The Credit Scores of Home-Purchase Mortgage Borrowers

Additional information about individuals obtaining mortgages to purchase homes can be gained by a review of credit record data collected by credit-reporting agencies. These data can be used to identify individuals taking out mortgages to finance a home purchase and, among these, individuals who are first-time homebuyers. Because the credit record data used here include the credit scores of individuals, we can use this metric to gauge the credit risk profile of home-purchase borrowers.

The data are from the FRBNY/Equifax Consumer Credit Panel. The panel is a nationally representative longitudinal database of individuals with detailed information, at a quarterly frequency beginning in 1999, on consumer and mortgage debt and loan performance drawn from the credit records collected and maintained by Equifax, one of the three national credit bureaus.36 The data include three key pieces of information with respect to this analysis: (1) details on each mortgage outstanding for a given consumer, including the year of origination; (2) each consumer's credit score as of the end of each quarter; and (3) each consumer's residential location at the level of the census block (a subunit of a census tract).37 The data used here are through the end of 2011.

Home-purchase loans are not explicitly identified in credit record data, but the panel nature of the data used here allows us to follow a given individual over time and infer whether that borrower purchased a home during any particular period. Specifically, we classify an individual as a homebuyer if the credit record indicates that he or she took out a new mortgage and moved to a different location (the credit record shows that the individual moved from one census block to another). First-time home-purchase borrowers are identified in a similar manner, but their credit records must show no evidence of a previous mortgage. The credit record data show that for home-purchase borrowers in general, as well as for first-time homebuyers financing their purchase, the median credit score has increased about 40 points since 2006. Furthermore, median scores now exceed by a considerable margin the median scores for home-purchase borrowers at any time in the past 12 years (figure 2).

From the perspective of changes in access to credit, a particular group to focus on is that consisting of individuals with scores in the bottom decile of all home-purchase borrowers. Here the data show that the score that delineates the bottom decile has increased nearly 50 points since the end of 2006. Individuals with scores below this increased threshold are likely to have a very difficult time qualifying for credit and, if they manage to qualify for a loan, are likely to pay higher prices. Consistent with this observation, overall, the share of home-purchase borrowers with scores below 620, a traditional demarcation line for individuals who are typically characterized as having a credit history that would be considered subprime, fell from about 19 percent of borrowers at the end of 2006 to about 7 percent at the end of the third quarter of 2011 (data not shown in tables).

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Lending across Population Groups and Neighborhoods

Figure 2. Credit scores of home-purchase borrowers, by selected credit score percentile, 1999-2011
Accessible Version |  Return to text

Note: The median is the 50th percentile. Credit score is the Equifax Risk Score 3.0. For more information, see text note 37.

Source: FRBNY/Equifax Consumer Credit Panel.

One of the strengths of the HMDA data is that the annual data can be merged to track changes in lending activity across population groups and areas. In this section, we show changes in lending, from 2010 to 2011, to borrowers sorted by income, race, or ethnicity and by the income or minority population characteristics of the areas where they reside. We also present an analysis of lending in areas characterized by their degree of economic distress.

Changes in Lending, 2010 to 2011

As noted earlier, both home-purchase and refinance lending fell from 2010 to 2011. Virtually all population segments experienced these declines, although the falloff in activity was more severe for some groups than for others (table 14, memo items). 38 Across racial or ethnic groups, all minority populations except Hispanic whites experienced relatively large declines in activity; Hispanic whites and non-Hispanic whites both experienced relatively smaller declines in activity. Lower-income borrowers, those purchasing homes in lower-income census tracts, and those residing in areas with larger minority populations also experienced relatively large reductions in home-purchase lending.

Patterns for refinancing differed from those for home-purchase lending, as the largest declines were among non-Hispanic whites, middle- and higher-income borrowers, and those residing in areas with smaller shares of minorities and populations with relatively higher incomes. The only group to experience an increase in refinance lending was low-income borrowers; refinance lending to this population segment increased about 3 percent from 2010 to 2011.

Populations differ considerably in their use of various loan products. Most notably, black, Hispanic white, and lower-income borrowers, and those residing in areas with larger shares of minority populations, use nonconventional loans to purchase homes to a greater extent than other groups. Greater reliance on nonconventional loans may reflect the relatively low down-payment requirements of the FHA and VA lending programs. The HMDA data indicate that all groups were a little less dependent on nonconventional loans in 2011 than in 2010. Reduced reliance on nonconventional loans occurred for both home-purchase and refinance lending.

Table 14. Home lending to different populations, by characteristic of borrower and of census tract and by type and purpose of loan, 2010-11
Percent except as noted
Characteristic
of borrower
and of
census tract
2010 2011 Memo: Percentage
change in
number
of loans,
2010-11
Conventional Non-
conventional1
Total Memo:
Number
of loans
Conventional Non-
conventional1
Total Memo:
Number
of loans
A. Home purchase
Borrower
Race other than white only2
American Indian or Alaska Native 33.8 66.2 100 11,183 36.5 63.5 100 9,435 -15.6
Asian 73.4 26.6 100 119,762 74.3 25.7 100 104,626 -12.6
Black or African American 18.9 81.1 100 133,969 21.6 78.4 100 113,591 -15.2
Native Hawaiian or other Pacific Islander 32.4 67.6 100 7,671 35.1 64.9 100 6,661 -13.2
White, by ethnicity2
Hispanic white 26.5 73.5 100 207,108 29.2 70.8 100 195,778 -5.5
Non-Hispanic white 50.3 49.7 100 1,504,464 53.3 46.7 100 1,417,339 -5.8
Income ratio (percent of area median)3
Low 38.3 61.7 100 281,788 39.9 60.1 100 254,828 -9.6
Moderate 34.9 65.1 100 552,928 37.3 62.7 100 495,859 -10.3
Middle 41.4 58.6 100 567,223 43.9 56.1 100 519,898 -8.3
High 63.0 37.0 100 816,394 65.9 34.1 100 790,223 -3.2
Census tract of property
Racial or ethnic composition (minorities as a percent of population)
Less than 10 54.3 45.7 100 806,008 56.4 43.6 100 767,580 -4.8
10-49 45.6 54.4 100 1,105,335 48.8 51.2 100 1,025,746 -7.2
50-79 37.5 62.5 100 197,401 41.0 59.0 100 169,409 -14.2
80-100 31.4 68.6 100 109,589 33.7 66.3 100 98,073 -10.5
Income ratio (percent of area median)4
Low 39.7 60.3 100 25,879 45.0 55.0 100 21,128 -18.4
Moderate 35.9 64.1 100 242,761 39.8 60.2 100 206,299 -15.0
Middle 41.6 58.4 100 1,107,033 44.3 55.7 100 1,029,115 -7.0
High 58.1 41.9 100 819,505 60.7 39.3 100 791,254 -3.4
B. Refinance
Borrower
Race other than white only2
American Indian or Alaska Native 76.8 23.2 100 11,981 77.6 22.4 100 10,991 -8.3
Asian 95.3 4.7 100 232,177 95.8 4.3 100 204,917 -11.7
Black or African American 58.1 41.9 100 129,828 62.5 37.6 100 119,267 -8.1
Native Hawaiian or other Pacific Islander 75.5 24.5 100 9,925 77.3 22.8 100 8,595 -13.4
White, by ethnicity2
Hispanic white 75.1 24.9 100 190,507 79.0 21.0 100 176,431 -7.4
Non-Hispanic white 86.3 13.7 100 3,359,573 87.7 12.3 100 2,826,443 -15.9
Income ratio (percent of area median)3
Low 54.5 45.5 100 631,539 62.4 37.6 100 648,323 2.7
Moderate 85.6 14.4 100 635,461 87.9 12.1 100 529,877 -16.6
Middle 87.7 12.3 100 1,017,330 89.1 10.9 100 821,444 -19.3
High 93.2 6.8 100 2,231,764 93.7 6.3 100 1,840,400 -17.5

Note: First-lien mortgages for owner-occupied one- to four-family homes.

1. See table 4, note 1. Return to table

2. Categories for race and ethnicity reflect the revised standards established in 1997 by the Office of Management and Budget. Applicants are placed under only one category for race and ethnicity, generally according to the race and ethnicity of the person listed first on the application. However, under race, the application is designated as joint if one applicant reported the single designation of white and the other reported one or more minority races. If the application is not joint but more than one race is reported, the following designations are made: If at least two minority races are reported, the application is designated as two or more minority races; if the first person listed on an application reports two races, and one is white, the application is categorized under the minority race. For loans with two or more applicants, lenders covered under the Home Mortgage Disclosure Act report data on only two. Return to table

Table 14. Home lending to different populations, by characteristic of borrower and of census tract and by type and purpose of loan, 2010-11 --continued
Percent except as noted
Characteristic
of borrower
and of
census tract
2010 2011 Memo: Percentage
change in
number
of loans,
2010-11
Conventional Non-
conventional1
Total Memo:
Number
of loans
Conventional Non-
conventional1
Total Memo:
Number
of loans
Census tract of property
Racial or ethnic composition (minorities as a percent of population)
Less than 10 87.5 12.5 100 2,014,629 88.6 11.4 100 1,662,511 -17.5
10-49 84.7 15.3 100 2,114,604 85.9 14.1 100 1,825,725 -13.7
50-79 81.6 18.4 100 266,896 83.5 16.5 100 241,937 -9.4
80-100 72.9 27.1 100 119,965 77.4 22.6 100 109,871 -8.4
Income ratio (percent of area median)4
Low 74.6 25.4 100 23,202 79.9 20.1 100 20,390 -12.1
Moderate 77.0 23.0 100 301,623 80.3 19.7 100 264,107 -12.4
Middle 82.4 17.6 100 2,094,968 83.8 16.2 100 1,779,036 -15.1
High 90.0 10.0 100 2,066,948 90.7 9.3 100 1,753,976 -15.1
C. Home improvement5
Borrower
Race other than white only2
American Indian or Alaska Native 96.2 3.8 100 1,749 96.7 3.3 100 1,787 2.2
Asian 98.0 2.0 100 5,771 97.4 2.6 100 5,857 1.5
Black or African American 91.3 8.7 100 17,993 93.0 7.0 100 17,964 -.2
Native Hawaiian or other Pacific Islander 95.9 4.1 100 764 95.9 4.1 100 752 -1.6
White, by ethnicity2
Hispanic white 95.2 4.8 100 19,935 95.8 4.2 100 20,733 4.0
Non-Hispanic white 96.4 3.6 100 238,623 96.6 3.4 100 227,534 -4.6
Income ratio (percent of area median)3
Low 93.9 6.1 100 46,348 93.0 7.0 100 45,672 -1.5
Moderate 96.2 3.8 100 63,060 95.1 4.9 100 61,778 -2.0
Middle 96.2 3.8 100 78,086 95.2 4.8 100 75,804 -2.9
High 97.2 2.8 100 127,660 96.4 3.6 100 124,873 -2.2
Census tract of property
Racial or ethnic composition (minorities as a percent of population)
Less than 10 97.2 2.8 100 160,410 96.2 3.8 100 154,798 -3.5
10-49 95.7 4.3 100 117,947 94.8 5.2 100 116,021 -1.6
50-79 95.2 4.8 100 17,870 92.8 7.2 100 17,742 -.7
80-100 92.9 7.1 100 18,927 93.4 6.6 100 19,566 3.4
Income ratio (percent of area median)4
Low 92.2 7.8 100 3,263 87.5 12.5 100 3,393 4.0
Moderate 95.0 5.0 100 36,461 94.3 5.7 100 35,492 -2.7
Middle 96.1 3.9 100 177,310 95.7 4.3 100 170,938 -3.6
High 96.9 3.1 100 92,906 96.2 3.8 100 91,865 -1.1

3. Borrower income is the total income relied on by the lender in the loan underwriting. Income is expressed relative to the median family income of the metropolitan statistical area (MSA) or statewide non-MSA in which the property being purchased is located. "Low" is less than 50 percent of the median; "moderate" is 50 percent to 79 percent (in this article, "lower income" encompasses the low and moderate categories); "middle" is 80 percent to 119 percent; and "high" is 120 percent or more. Return to table

4. The income category of a census tract is the median family income of the tract relative to that of the MSA or statewide non-MSA in which the tract is located as derived from the 2000 census. "Low" is less than 50 percent of the median; "moderate" is 50 percent to 79 percent; "middle" is 80 percent to 119 percent; and "high" is 120 percent or more. Return to table

5. Consists of first- and junior-lien loans and loans without a lien. Return to table

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Credit Circumstances in Distressed Neighborhoods

Since the start of the housing downturn, access to mortgage credit has been an acute public policy concern, particularly for households with lower incomes or in neighborhoods that have been hardest hit by foreclosures. Mortgage originations have declined broadly since 2005, and, as we discussed in the review of last year's HMDA data, these declines have been greater in highly distressed neighborhoods. To determine if credit has yet begun to flow more freely in such neighborhoods, we use the HMDA data to compare mortgage credit flows from 2010 to 2011.

As in last year's review, we identify distressed neighborhoods using the scores produced by the Department of Housing and Urban Development (HUD) for the NSP.39 The NSP was created by the Housing and Economic Recovery Act of 2008 to provide funds for state and local governments seeking to support neighborhoods with high levels of property abandonment and foreclosure. In deciding which neighborhoods to target, HUD uses a statistical model that estimates the likelihood that the neighborhood is experiencing high rates of foreclosure and mortgage delinquency. The outputs of this model are used to assign to each tract an NSP score ranging from 1 to 20, with a higher score indicating a greater likelihood of distress and with the scores scaled so that each score point is given to 5 percent of census tracts. While an evaluation of the success of the NSP itself is well beyond the scope of this article, we can use these scores to classify census tracts according to the degree of distress they face.

The change from 2010 to 2011 in home-purchase lending for owner-occupied properties, broken down by quintiles of the NSP score, is shown in table 15. Lending declined 7.2 percent overall, though the declines were substantially greater in high-distress neighborhoods. In tracts with NSP scores of 17 to 20, home-purchase lending decreased 13.8 percent, compared with 3.3 percent in tracts with NSP scores below 5. The steeper decline in mortgage credit flows to highly distressed areas continues a trend that has been observed since the onset of the housing market downturn.

Table 15. Loan characteristics related to lending in areas grouped by Neighborhood Stabilization Program score, 2011
Percent change in home-purchase lending from 2010 to 2011
Characteristic NSP score1
1-4 5-8 9-12 13-16 17-20 All
Memo
Loans -3.3 -7.1 -9.3 -9.9 -13.8 -7.2
Applications -3.9 -7.3 -9.0 -10.1 -15.4 -7.8
Borrower
Income ratio (percent of area median)2
Lower -7.4 -9.6 -11.4 -13.6 -19.6 -12.3
Middle -8.4 -10.4 -12.2 -12.9 -16.5 -11.3
High -1.6 -5.1 -6.8 -5.1 -5.7 -3.8
Minority3 -4.7 -10.1 -11.2 -13.1 -14.8 -10.1
Originating institution
Bank -2.9 -7.0 -9.7 -10.3 -17.6 -7.1
Thrift -20.2 -28.1 -30.2 -26.4 -18.0 -24.1
Credit union 6.6 10.8 9.2 8.9 11.2 8.5
Independent mortgage bank 4.6 -.6 -3.2 -6.4 -11.2 -2.3
Top 10 organization -14.4 -16.6 -19.3 -18.5 -22.6 -17.1
Non-top 10 organization 2.6 -2.9 -4.9 -6.1 -9.9 -2.6

Note: First and junior liens for owner-occupied one- to four-family properties in metropolitan areas. Data are the percent change in the dollar value of lending.

1. The Neighborhood Stabilization Program (NSP) score is based on the NSP3 score created by the Department of Housing and Urban Development. The NSP score classifies census tracts into 5 percent "buckets" on a range of 1 to 20, with 1 being the best tracts and 20 being the worst in terms of a variety of factors, such as foreclosure rates. NSP scores determine eligibility for NSP funding; census tracts with the highest scores are considered the tracts with the greatest need for support. See text for further details. Return to table

2. Borrower income is the total income relied upon by the lender in the loan underwriting. Income is expressed relative to the median family income of the metropolitan statistical area (MSA) or statewide non-MSA in which the property being purchased is located. "Lower" is less than 80 percent of the median; "middle" is 80 percent to 119 percent; and "high" is 120 percent or more. Return to table

3. See table 14, note 2. Minority borrowers are borrowers other than non-Hispanic whites. Return to table

Source: Department of Housing and Urban Development; Federal Financial Institutions Examination Council, data reported under the Home Mortgage Disclosure Act.

Differences in the extent of decline are also observed across borrower income levels. Lending fell more substantially for lower- and middle-income borrowers (12.3 percent and 11.3 percent, respectively) than it did for high-income borrowers (3.8 percent). Indeed, for high-income borrowers, the decline in lending appears unrelated to the degree of neighborhood distress, as indicated by the nonmonotonic relationship between lending declines and NSP score quintile. However, for lower- and middle-income borrowers, the decreases were notably larger when neighborhood distress increased. Somewhat surprisingly, lending to middle-income borrowers fell more than it did for lower-income borrowers in the bottom three quintiles of the NSP score (scores of 1 to 12). In tracts with NSP scores above 12, lending to lower-income borrowers fell off by a larger percentage than it did for high-income borrowers.

Attributing these declines to supply- or demand-side factors is not straightforward. As shown in table 15, the number of applications for home-purchase loans fell by slightly more than the number of loan originations, a pattern that holds for almost all NSP quintiles. The sharper decline in applications suggests that reduced mortgage flows may primarily reflect a drop in demand; however, since potential applicants may have foregone applying because they suspected their application would be denied, the sharper fall in applications is insufficient to prove that these declines represent demand-side factors alone. Most likely, these changes reflect a combination of changes in supply and demand.

One supply factor that may be influencing how mortgage credit is flowing is the mix of lenders extending credit. In percentage terms, the largest changes involved thrift institutions, whose lending fell by almost one-fourth in 2011, and credit unions, whose lending increased by over 8 percent. While these institution types accounted for only a small share of lending in 2011 (13 percent; data not shown in table), in neither case was there a clear relationship between the change in lending and the degree of neighborhood distress. Instead, the more rapid decline in lending to distressed neighborhoods appears to involve lending by commercial banks and independent mortgage companies. Both institution types experienced larger declines in lending to tracts with higher NSP scores. While lending by commercial banks was down in 2011 for all NSP quintiles, lending by independent mortgage companies increased in tracts in the least amount of distress (the bottom quintile of NSP scores) in 2011 and fell 11 percent in tracts in the most distress. Nevertheless, both institution types had a spread of about 15 percentage points between the changes in lending in the highest and lowest NSP quintiles.

In addition to types of lenders, we can also examine lending activity by largest lenders. Home-purchase lending by the 10 largest lenders in 2011 fell more sharply in 2011 (17 percent) than lending by other financial institutions (2.6 percent). However, lending by both declined more in highly distressed neighborhoods than in neighborhoods experiencing less distress.

The results of this analysis suggest that highly distressed neighborhoods continue to experience reduced mortgage flows, which mirrors the pattern observed for the 2005-10 period discussed in last year's review. These declines were particularly pronounced for lower-income borrowers. And while it is difficult to apportion these declines to demand and supply considerations, the sharper declines in distressed areas appear, for the most part, to have been widespread across lenders.

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Differences in Lending Outcomes by Race, Ethnicity, and Sex of the Borrower

One reason the Congress amended HMDA in 1989 was to enhance its value for fair lending enforcement by adding to the items reported the disposition of applications for loans and the race, ethnicity, and sex of applicants. A similar motivation underlay the decision to add pricing data for higher-priced loans in 2004, although such data serve other purposes, including to help identify lenders active in the higher-cost or higher-risk segments of the mortgage market and provide information on the volume and locations of borrowers receiving higher-priced loans.

Over the years, analyses of HMDA data have consistently found substantial differences in the incidence of higher-priced lending and in application denial rates across racial and ethnic lines, differences that cannot be fully explained by factors included in the HMDA data.40 Analyses also have found that differences across groups in mean APR spreads paid by those with higher-priced loans were generally small.41 Here we examine the 2011 HMDA data to determine the extent to which these differences persist.

The analysis here presents aggregated lending outcomes across all reporting institutions. Patterns for any given financial institution may differ from those shown, and for any given financial institution, relationships may vary by loan product, geographic market, and loan purpose. Further, although the HMDA data include some detailed information about each mortgage transaction, many key factors that are considered by lenders in credit underwriting and pricing are not included. Accordingly, it is not possible to determine from HMDA data alone whether racial and ethnic pricing disparities reflect illegal discrimination. However, analysis using the HMDA data can account for some factors that are likely related to the lending process. Given that lenders offer a wide variety of loan products for which basic terms and underwriting criteria can differ substantially, the analysis here can only be viewed as suggestive.

Comparisons of average outcomes (both loan pricing and denials) for each racial, ethnic, or gender group are made both before and after accounting for differences in the borrower-related factors contained in the HMDA data (income; loan amount; location of the property, or MSA; and presence of a co-applicant) and for differences in borrower-related factors plus the specific lending institution used by the borrower.42 Comparisons for lending outcomes across groups are of three types: gross (or "unmodified"), modified to account for borrower-related factors (or "borrower modified"), and modified to account for borrower-related factors plus lender (or "lender modified").43 The analysis here distinguishes between conventional and nonconventional lending, reflecting the different underwriting standards and fees associated with these two broad loan product categories.44

Incidence of Higher-Priced Lending by Race and Ethnicity and Sex

As noted earlier, 2010 was the first HMDA reporting year for which all of the loans subject to higher-priced loan reporting used the new Freddie Mac PMMS threshold (the PMMS threshold was also used for the last three months of 2009). Before October 1, 2009, a Treasury-based threshold was used. The change in threshold makes it problematic to compare the reported incidence of higher-priced lending in 2010 or 2011 with the incidence reported for previous years. Nevertheless, in previous articles, we have employed a methodology that adjusted the Treasury-based spread to a spread over the 30-year fixed-rate mortgage APOR reported in the PMMS. For almost all of the period from 2006 to 2009, this methodology gave a good approximation of the incidence of loans with APOR spreads more than 1.75 percentage points above the PMMS (25 basis points higher than the cutoff for higher-priced reporting in 2010). Calculations using the "adjusted spread" showed that the estimated incidence of loans more than 1.75 percentage points above the PMMS is significantly reduced from 2006 to 2008 for all racial and ethnic groups and that the differences across groups are considerably smaller since 2008 than in the years prior.45 Data reported for the last three months of 2009 using the new threshold showed only modest differences across groups.

As noted earlier, the overall reported incidence of higher-priced lending was about 50 basis points higher in 2011 than in 2010 (data for 2010 not shown in tables). Pricing relationships observed in the 2011 HMDA data are very similar to those found in the 2010 data. The 2011 HMDA data indicate that black and Hispanic-white borrowers are more likely, and Asian borrowers less likely, to obtain conventional loans with prices above the HMDA price-reporting thresholds than are non-Hispanic white borrowers. These relationships hold both for home-purchase and refinance lending and for nonconventional loans (tables 16.A and 16.B). For example, for conventional home-purchase lending in 2011, the incidence of higher-priced lending was 7.8 percent for black borrowers, 7.3 percent for Hispanic white borrowers, and 1.3 percent for Asian borrowers, compared with 3.9 percent for non-Hispanic white borrowers.

Table 16. Incidence of higher-priced lending, unmodified and modified for borrower- and lender-related factors, by type and purpose of loan and by race, ethnicity, and sex of borrower, 2011
A. Conventional loan

Percent except as noted
Race, ethnicity, and sex Number of loans Unmodified incidence Modified incidence, by modification factor Number of loans Unmodified incidence Modified incidence, by modification factor
Borrower-
related
Borrower-
related
plus lender
Borrower-
related
Borrower-
related
plus lender
Home purchase Refinance
Race other than white only1
American Indian or Alaska Native 2,905 7.85 4.42 4.14 8,313 3.14 2.46 1.82
Asian 77,211 1.32 3.28 3.70 195,610 .31 .93 1.48
Black or African American 21,655 7.84 6.52 4.69 73,397 4.21 3.19 2.36
Native Hawaiian or other Pacific Islander 2,285 2.76 3.98 4.23 6,593 1.18 1.88 2.26
Two or more minority races 395 2.28 3.12 3.87 1,405 .85 2.06 1.96
Joint 15,158 2.91 4.17 4.16 48,823 .97 1.67 1.72
Missing 84,659 1.67 2.78 3.90 339,272 .74 1.09 1.64
White, by ethnicity1
Hispanic white 43,569 7.25 5.68 4.40 110,493 2.41 2.09 2.00
Non-Hispanic white 736,713 3.85 3.85 3.85 2,496,791 1.62 1.62 1.62
Sex
One male 274,116 3.92 3.92 3.92 655,790 1.79 1.79 1.79
One female 192,796 3.55 3.27 3.63 522,500 1.99 1.70 1.72
Two males 10,304 7.00 7.00 7.00 22,219 2.00 2.00 2.00
Two females 7,924 4.76 5.41 6.97 22,594 2.07 1.77 2.16

Note: First-lien mortgages for owner-occupied, one- to four-family, site-built properties; excludes business loans. Business-related loans are those for which the lender reported that the race, ethnicity, and sex of the applicant or co-applicant are "not applicable." For definition of higher-priced lending and explanation of modification factors, see text and table 9, note 3. Loans taken out jointly by a male and female are not tabulated here because they would not be directly comparable with loans taken out by one borrower or by two borrowers of the same sex.

1. See table 14, note 2. Return to table

Table 16. Incidence of higher-priced lending, unmodified and modified for borrower- and lender-related factors, by type and purpose of loan and by race, ethnicity, and sex of borrower, 2011
B. Nonconventional loan

Percent except as noted
Race, ethnicity, and sex Number of loans Unmodified incidence Modified incidence, by modification factor Number of loans Unmodified incidence Modified incidence, by modification factor
Borrower-
related
Borrower-
related
plus lender
Borrower-
related
Borrower-
related
plus lender
Home purchase Refinance
Race other than white only1
American Indian or Alaska Native 5,754 2.78 2.91 2.09 2,312 5.02 3.74 2.83
Asian 26,746 2.09 2.01 2.02 8,577 4.03 3.92 4.06
Black or African American 87,774 4.16 3.53 3.10 44,070 10.80 7.33 5.24
Native Hawaiian or other Pacific Islander 4,288 2.64 2.46 2.57 1,913 3.50 3.58 4.06
Two or more minority races 681 .88 1.35 1.59 308 4.55 5.33 4.21
Joint 15,364 1.75 2.37 2.51 9,617 2.67 4.50 4.58
Missing 74,377 2.89 3.57 2.30 55,264 2.32 3.06 4.64
White, by ethnicity1
Hispanic white 120,229 4.78 2.79 2.59 28,384 6.50 4.20 4.23
Non-Hispanic white 660,368 2.35 2.35 2.35 344,076 5.94 5.94 5.94
Sex
One male 359,311 2.91 2.91 2.91 147,966 4.72 4.72 4.72
One female 234,298 3.89 2.92 2.91 81,252 12.04 6.03 5.56
Two males 13,567 2.94 2.94 2.94 3,692 2.76 2.76 2.76
Two females 10,629 3.24 3.36 3.54 3,261 4.60 4.07 4.66

Note: See notes to table 16.A.

The gross differences in the incidence of higher-priced lending between non-Hispanic whites and blacks or Hispanic whites in 2011 are significantly reduced, but not completely eliminated, after controlling for lender and borrower characteristics. For example, the gross 2011 difference in the incidence of higher-priced conventional lending for home-purchase loans between Hispanic whites and non-Hispanic whites of 3.4 percentage points falls to only about 0.55 percentage point when the other factors available within the HMDA data are accounted for. The large gap in pricing between blacks and non-Hispanic whites is similarly reduced when other factors are considered. The pricing disparities across groups are significantly lower than the higher-priced incidence disparities observed from 2004 to 2007 using both the old Treasury-based threshold and our PMMS-based adjusted spread.

With regard to the gender of applicants, we find relatively small differences in the incidence of higher-priced lending between single applicants of different genders and dual applicants of different genders once all available factors are taken into account.

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Rate Spreads by Race, Ethnicity, and Sex

The 2011 data indicate that among borrowers with higher-priced loans, the gross APOR spreads are similar across groups for both home-purchase and refinance lending. This result holds for both conventional (table 17.A) and nonconventional lending (table 17.B). For example, for conventional home-purchase loans, the gross mean APOR spread was 2.49 percentage points for black borrowers and 2.76 percentage points for Hispanic white borrowers, while it was 2.49 percentage points for non-Hispanic white borrowers and 2.41 percentage points for Asian borrowers. Accounting for borrower-related factors or the specific lender used by the borrowers has little effect on the differences across groups.

Table 17. Mean average prime offer rate spreads, unmodified and modified for borrower- and lender-related factors, for higher-priced loans on one- to four-family homes, by type and purpose of loan and by race, ethnicity, and sex of borrower, 2011
A. Conventional loan

Percent except as noted
Race, ethnicity, and sex Number of higher-priced loans1 Unmodified mean spread Modified mean spread,
by modification factor
Number of higher-priced loans1 Unmodified mean spread Modified mean spread,
by modification factor
Borrower-
related
Borrower-
related
plus lender
Borrower-
related
Borrower-
related
plus lender
Home purchase Refinance
Race other than white only2
American Indian or Alaska Native 228 2.93 2.80 2.70 261 2.71 2.55 2.58
Asian 1,016 2.41 2.49 2.46 601 2.43 2.36 2.49
Black or African American 1,698 2.49 2.67 2.54 3,087 2.99 2.91 2.66
Native Hawaiian or other Pacific Islander 63 2.26 2.95 2.63 78 2.42 2.62 2.61
Two or more minority races 9 2.68 3.61 2.52 12 1.98 2.34 2.67
Joint 441 2.49 2.48 2.49 476 2.48 2.56 2.56
Missing 1,415 2.29 2.29 2.48 2,514 2.52 3.13 2.56
White, by ethnicity2
Hispanic white 3,160 2.76 2.71 2.55 2,660 2.84 2.56 2.55
Non-Hispanic white 28,356 2.49 2.49 2.49 40,456 2.53 2.53 2.53
Sex
One male 9,073 2.54 2.54 2.54 10,679 2.72 2.72 2.72
One female 5,767 2.48 2.48 2.51 9,937 2.80 2.73 2.72
Two males 721 2.58 2.58 2.58 445 2.54 2.54 2.54
Two females 377 2.55 2.51 2.52 467 2.68 2.56 2.49

Note: For definition of higher-priced lending and explanation of modification factors, see text. Loans taken out jointly by a male and female are not tabulated here because they would not be directly comparable with loans taken out by one borrower or by two borrowers of the same sex. For definition of average prime offer rate spread, see table 11, note 1.

1. See table 9, note 3. Return to table

2. See table 14, note 2. Return to table

Table 17. Mean average prime offer rate spreads, unmodified and modified for borrower- and lender-related factors, for higher-priced loans on one- to four-family homes, by type and purpose of loan and by race, ethnicity, and sex of borrower, 2011
B. Nonconventional loan

Percent except as noted
Race, ethnicity, and sex Number of higher-priced loans1 Unmodified mean spread Modified mean spread,
by modification factor
Number of higher-priced loans1 Unmodified mean spread Modified mean spread,
by modification factor
Borrower-
related
Borrower-
related
plus lender
Borrower-
related
Borrower-
related
plus lender
Home purchase Refinance
Race other than white only2
American Indian or Alaska Native 160 1.78 1.91 1.95 116 2.49 2.50 2.53
Asian 558 2.10 1.96 1.93 346 2.35 2.30 2.38
Black or African American 3,651 1.94 1.93 1.96 4,758 2.63 2.55 2.49
Native Hawaiian or other Pacific Islander 113 1.91 1.95 1.95 67 2.44 2.47 2.24
Two or more minority races 6 2.07 1.89 2.01 14 2.25 2.23 2.22
Joint 269 1.97 2.00 1.97 257 2.36 2.59 2.45
Missing 2,151 2.21 2.18 1.98 1,281 3.33 4.42 2.32
White, by ethnicity2
Hispanic white 5,749 1.88 1.92 1.96 1,845 2.47 2.39 2.44
Non-Hispanic white 15,531 1.96 1.96 1.96 20,442 2.44 2.44 2.44
Sex
One male 10,449 1.93 1.93 1.93 6,977 2.60 2.60 2.60
One female 9,114 1.99 1.95 1.93 9,785 2.63 2.65 2.64
Two males 399 1.90 1.90 1.90 102 2.17 2.17 2.17
Two females 344 1.85 1.84 1.92 150 2.30 2.16 2.23

Note: See notes to table 17.A.

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Denial Rates by Race, Ethnicity, and Sex

Analyses of the HMDA data in previous years have consistently found that denial rates vary across applicants grouped by race or ethnicity. This continues to be the case in 2011. As in past years, blacks and Hispanic whites had notably higher gross denial rates in 2011 than non-Hispanic whites, while the differences between Asians and non-Hispanic whites generally were fairly small by comparison (tables 18.A and 18.B). For example, the denial rates for conventional home-purchase loans were 30.9 percent for blacks, 21.7 percent for Hispanic whites, 14.8 percent for Asians, and 11.9 percent for non-Hispanic whites. The pattern was about the same for nonconventional home-purchase lending, although the gap in gross denial rates between blacks or Hispanic whites and non-Hispanic whites was notably smaller than for conventional home-purchase loans.

For both conventional and nonconventional home-purchase lending, controlling for borrower-related factors in the HMDA data generally reduces the differences among racial and ethnic groups. Accounting for the specific lender used by the applicant reduces differences further, although unexplained differences remain between non-Hispanic whites and other racial and ethnic groups. An analysis of refinance loans shows similar patterns, although the differences in gross denial rates between blacks and non-Hispanic whites and between Hispanic whites and non-Hispanic whites tend to be larger than for home-purchase lending. For example, the gross difference between black and non-Hispanic-white borrowers refinancing using a conventional loan was 20.5 percentage points.

Table 18. Denial rates on applications, unmodified and modified for borrower- and lender-related factors, by type and purpose of loan and by race, ethnicity, and sex of applicant, 2011
A. Conventional loan application

Percent except as noted
Race, ethnicity, and sex Number of applications acted upon by lender Unmodified denial rate Modified denial rate,
by modification factor
Number of applications acted upon by lender Unmodified denial rate Modified denial rate,
by modification factor
Borrower-
related
Borrower-
related
plus lender
Borrower-
related
Borrower-
related
plus lender
Home purchase Refinance
Race other than white only1
American Indian or Alaska Native 4,165 23.8 21.3 16.1 14,554 36.2 35.0 28.8
Asian 99,848 14.8 14.8 13.5 266,844 19.3 23.1 23.4
Black or African American 34,475 30.9 24.2 21.3 138,918 40.5 36.3 32.1
Native Hawaiian or other Pacific Islander 3,130 20.3 16.1 15.1 10,738 31.9 31.6 28.6
Two or more minority races 576 24.0 24.7 19.7 2,349 32.8 36.7 31.3
Joint 18,679 12.1 14.3 12.9 65,079 18.7 23.5 22.1
Missing 115,081 18.6 18.7 14.9 529,019 29.2 28.6 24.4
White, by ethnicity1
Hispanic white 60,885 21.7 16.2 15.7 179,810 32.0 28.5 26.6
Non-Hispanic white 894,159 11.9 11.9 11.9 3,362,076 20.0 20.0 20.0
Sex
One male 353,445 16.0 16.0 16.0 987,535 26.7 26.7 26.7
One female 245,656 15.6 14.3 14.8 767,689 25.8 24.4 24.6
Two males 13,586 17.9 17.9 17.9 31,981 24.5 24.5 24.5
Two females 10,332 17.6 15.3 14.5 32,124 24.0 23.5 23.7

Note: First-lien mortgages for owner-occupied, one- to four-family, site-built properties; excludes business loans. Business-related loans are those for which the lender reported that the race, ethnicity, and sex of the applicant or co-applicant are "not applicable." For explanation of modification factors, see text. Applications made jointly by a male and female are not tabulated here because they would not be directly comparable with applications made by one applicant or by two applicants of the same sex.

1. See table 14, note 2. Return to table

Table 18. Denial rates on applications, unmodified and modified for borrower- and lender-related factors, by type and purpose of loan and by race, ethnicity, and sex of applicant, 2011
B. Nonconventional loan application

Percent except as noted
Race, ethnicity, and sex Number of applications acted upon by lender Unmodified denial rate Modified denial rate,
by modification factor
Number of applications acted upon by lender Unmodified denial rate Modified denial rate,
by modification factor
Borrower-
related
Borrower-
related
plus lender
Borrower-
related
Borrower-
related
plus lender
Home purchase Refinance
Race other than white only1
American Indian or Alaska Native 7,408 16.7 18.8 18.0 4,115 35.6 37.7 32.6
Asian 35,278 18.6 17.1 15.6 14,906 32.6 33.6 32.3
Black or African American 120,493 22.0 20.2 19.2 83,469 38.9 39.6 36.5
Native Hawaiian or other Pacific Islander 5,554 17.2 17.4 17.4 3,165 30.5 33.1 32.5
Two or more minority races 939 20.0 19.5 18.5 632 39.6 39.8 31.0
Joint 18,604 12.3 14.3 13.4 14,265 24.6 32.0 31.0
Missing 101,560 20.7 21.4 18.0 110,551 42.6 40.9 31.1
White, by ethnicity1
Hispanic white 157,053 17.9 15.9 15.6 48,034 31.4 33.0 32.3
Non-Hispanic white 796,284 12.7 12.7 12.7 538,897 28.9 28.9 28.9
Sex
One male 453,381 15.9 15.9 15.9 253,578 33.8 33.8 33.8
One female 295,544 16.0 14.7 15.0 144,648 36.3 32.6 32.5
Two males 18,167 20.0 20.0 20.0 6,151 30.9 30.9 30.9
Two females 13,935 18.9 17.1 17.8 5,598 33.5 29.3 30.1

Note: See notes to table 18.A.

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Some Limitations of the Data in Assessing Fair Lending Compliance

Previous research and experience gained in the fair lending enforcement process show that unexplained differences in the incidence of higher-priced lending and in denial rates among racial or ethnic groups stem, at least in part, from credit-related factors not available in the HMDA data, such as credit history (including credit scores), loan-to-value ratios, and differences in loan characteristics. Differential costs of loan origination and the competitive environment also may bear on the differences in pricing, as may differences across populations in credit-shopping activities.

Despite these limitations, the HMDA data play an important role in fair lending enforcement. The data are regularly used by bank examiners to facilitate the fair lending examination and enforcement processes. When examiners for the federal banking agencies evaluate an institution's fair lending risk, they analyze HMDA price data and loan application outcomes in conjunction with other information and risk factors that can be drawn directly from loan files or electronic records maintained by lenders, as directed by the Interagency Fair Lending Examination Procedures.46 The availability of broader information allows the examiners to draw firm conclusions about institution compliance with the fair lending laws.

It is important to keep in mind that the HMDA data, as currently constituted, can be used only to detect differences in pricing across groups for loans with APRs above the reporting threshold; pricing differences may exist among loans below the threshold. This gap in the loan pricing information will be addressed in coming years as the Consumer Financial Protection Bureau implements the expanded data reporting requirements set forth in the Dodd-Frank Wall Street Reform and Consumer Protection Act of 2010, including the provision requiring the reporting of rate spread information for all loans.

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Assessing the Accuracy of Borrower Income Reported in the HMDA Data

During the housing boom of the 2000s, one underwriting practice that proliferated was the granting of mortgages with little or no documentation of income and assets. To investigate the extent to which borrower incomes may have been overstated on mortgage applications as a result of such practices, we compare the incomes reported for home-purchase borrowers in the HMDA data with the incomes of homebuyers taking out mortgages reported in Census 2000 and the ACS for 2005 through 2010.47 While incentives to overstate income on mortgage applications sometimes exist, no such incentive exists when reporting income for the census or ACS. Thus, the Census 2000 and ACS data may provide "true" measures of income of homebuyers with which to gauge the accuracy of income reported on mortgage applications.48

The Census Bureau annually conducts the ACS, a household survey gathering a wide variety of information, including overall family income, homeownership status, and mortgage status. Because the survey was conducted on a somewhat smaller scale prior to 2005, we use only ACS data for 2005 and after, and we use Census 2000 data to measure borrower income at the beginning of the decade.49 For each year of the analysis, we compute average family income at the state level for home-purchase borrowers in the HMDA data and for families in the ACS and Census 2000 data that appear to have recently purchased their home with a mortgage (those that reported they own their home, have a mortgage, and moved in the past year).50 We then compute the ratio of HMDA income to ACS income (or, from Census 2000, census income), state by state and for three different periods: 2000, 2005 to 2006, and 2009 to 2010. Ratios substantially greater than 1 imply widespread overstatement of income on mortgage applications.

Figure 3 suggests that income on mortgage applications was widely overstated in a number of states in 2005 and 2006, particularly California, Hawaii, Massachusetts, Nevada, and New York. In these states, average borrower income as reflected in the HMDA data was 30 percent or more above the average ACS borrower income. In contrast, HMDA borrower income was no more than 10 percent above borrower income as reported in Census 2000 in almost all states. Finally, in 2009 and 2010, we observe a return to consistent incomes across data sources, with borrower incomes reported in HMDA and the ACS within 10 percent of each other in almost every state.

Users of the HMDA data should be aware that borrower income was likely significantly overstated during the peak of the housing boom, particularly in some areas of the country. One potential implication of this finding is that lending to lower-income borrowers, as measured in the HMDA data, may be attenuated around the peak of the housing market.

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Transition to the 2010 Census Data and Revised Census-Tract Boundaries

Figure 3. Ratio of average income for home-purchase borrowers, as reported under the Home Mortgage Disclosure Act, to average homebuyer income from Census 2000 and to that from the American Community Survey of 2005-06 and 2009-10, by state
Accessible Version |  Return to text

Note: For information on data calculation, see text.

Source: Federal Financial Institutions Examination Council, data reported under the Home Mortgage Disclosure Act; Census Bureau.

Census data are used to evaluate the performance of lending institutions in complying with the CRA and the nation's fair lending laws. For example, family income data derived from the census are used to categorize census tracts by their relative median family income, and race and ethnicity data are used to characterize the minority population status of census tracts and other geographies.51 In the CRA context, the relative income of census tracts is used to identify which census tracts are considered lower income (low or moderate income) and, as a consequence, a focus of CRA attention. In the fair lending enforcement context, census-tract minority population characteristics are used, for example, to help detect potential redlining behavior, where, for example, a lender has a policy or practice that results in little or no lending in a geographic area because of its racial or ethnic composition.

Using census sources to identify income, population, and housing characteristics of census tracts and broader areas has become more complicated recently. Unlike Census 2000, which used a survey questionnaire that asked a great many detailed questions (often referred to as the "long form"), the 2010 census used a brief questionnaire (referred to as the "short form"). In particular, the 2010 census focused on gathering household population counts and race, ethnicity, sex, and age characteristic information, but it provides relatively little other information--and no data on household or family income.

In lieu of collecting extensive detailed information from every household once a decade in conjunction with the decennial census, the Census Bureau now annually conducts the ACS. The ACS collects detailed population, income, and housing information from a representative sample of about 3 million households using a long-form questionnaire. Because of a relatively small sample size, the annual ACS data do not provide sufficient information to establish reliable estimates of census-tract characteristics. However, the Census Bureau aggregates ACS data across years and publishes data for each census tract based on the most recent five-year combined ACS data. The first five-year ACS aggregate data made available were derived from the 2005-09 annual surveys and used the census-tract boundaries established for Census 2000. The more recent 2006-10 combined ACS data were released to the public in December 2011 and are available from the FFIEC at its HMDA website. The 2006-10 ACS data use the census-tract boundaries created for the 2010 census. Using five-year aggregated data derived from the ACS, it is possible to categorize each census tract by its relative median family income.

FFIEC Treatment of Updated Census and ACS Data

The FFIEC has announced that, for purposes of preparing HMDA disclosure reports and for CRA performance evaluations, the 2006-10 ACS data will be used to classify census tracts by relative median family income and that these classifications will not be changed for a period of five years.52 Five years hence, updated relative-income information will be derived from the combined 2011-15 ACS data, and census tracts will be reclassified according to their updated income profiles. Although, in principle, annual updates from the ACS could be used to reclassify census tracts by their relative incomes each year, the potential movement of census tracts from one relative-income category to another would greatly complicate CRA enforcement and make it difficult for lending institutions to plan and monitor their own activities.

A key aspect of the HMDA reporting rules is the requirement that lenders identify the census-tract locations of the properties involved in the applications and loans they report on each year. The 2011 HMDA data used census tracts as enumerated for Census 2000 and do not reflect any of the updated 2010 census or ACS data. Census-tract identifiers for the forthcoming 2012 HMDA data will be those enumerated for the 2010 census: Analysis of these data will use the 2010 census data and the 2006-10 ACS data.

There were substantial changes in the number and boundaries of census tracts between the 2000 and 2010 censuses. As a consequence of population growth and migration, as well as other factors, such as new road construction, the 2010 census includes many more census tracts than Census 2000, and the geographic areas of many census tracts used for Census 2000 have been altered. Overall, Census 2000 included about 66,300 census tracts; the 2010 census includes about 74,000 census tracts. About 46 percent of the 2010 census tracts have the same geographic boundaries as in 2000, and about 72 percent have a land area that is 95 percent or more identical to the area in 2000. For purposes of this article, the census tracts that have 2010 areas that are 95 percent or more the same as in 2000 are referred to as "substantially similar" census tracts.

The shift from the 2000 to the 2010 census has important implications for those using the HMDA data. Perhaps most important is the possibility that a loan related to a given property may have been identified as being in a census tract in a particular relative-income group one year, but a loan on that same property may be reclassified into a different relative-income category the next year simply because of the shift from the income data based on Census 2000 to the income data based on the 2006-10 ACS. Reclassification could occur because the income profile of the population in the census tract has changed (altering the numerator in the relative-income calculation), because the income profile of the broader area has changed (altering the denominator in the relative-income classification), or both.

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Evaluating the Effects of Census Data Changes

In order to gauge the potential effects of census data changes on the classification of lending activity, we undertook some simulations using the 2011 HMDA data. The analysis here focuses on the reclassification of census tracts due to changes in their relative family incomes and the reclassification of home lending (of all types) due to the reclassification of the census tracts where the properties associated with the loans are located. Because the location of branch offices may influence an institution's home-lending activity and because branch locations are an important component of CRA performance evaluations, we also assess the effects of the census data changes on branch officeclassification by census-tract income. Unlike lending, where an institution can potentially alter the geographic pattern of the home loan applications it receives by changes in marketing, outreach to real estate agents and homebuilders, and other techniques, branch office locations cannot be readily changed.

We evaluate the "pure" effects of updated population income estimates by comparing census-tract income classifications using Census 2000 data with classifications derived from the 2005-09 ACS surveys. Both Census 2000 and the 2005-09 ACS use the same census-tract boundaries. Also, to ensure that changes in MSA boundaries over the course of the past decade do not affect the analysis, we use the census-tract relative-income classifications as carried on the 2011 FFIEC HMDA data files. These files reflect the 2000 decennial estimates of median family income for each census tract but use current MSA boundary definitions. Thus, the only factors that can affect our estimates of income reclassifications are the updates to census-tract or broader area median family incomes that come about because of changes in family income estimates from shifting from Census 2000 to the more recent data based on the 2005-09 ACS.53

Census-Tract Reclassification

Our analysis indicates that the transition from the Census 2000 to the 2005-09 ACS data for classifying census tracts by relative income would result in significant changes in census-tract income category classification. For example, 17 percent of the census tracts that were classified as moderate income using the 2000 income data would be reclassified as middle income, and 1 percent would be reclassified as higher income (table 19). Because these census tracts would no longer be classified as falling in the lower-income category, lending and other activities, including branch office locations, in these census tracts would no longer be a focus of CRA attention. However, about 15 percent of middle-income census tracts would be reclassified as moderate income, and activities in these census tracts would gain emphasis in CRA performance evaluations.

Table 19. Effect of the transition to updated census data on classification of census tracts, home lending, and branch offices, by census-tract relative-income reclassification
Census-tract
relative-income
reclassification1
Census 2000 to 2005-09 ACS Census 2000 to 2006-10 ACS
Census tracts Loans Branch offices Census tracts Loans Branch offices
Number Percent Number Percent Number Percent Number Percent Number Percent Number Percent
Low to low 2,888 74 40,675 64 1,966 63 2,213 76 31,483 64 1,486 68
Low to moderate 860 22 16,682 26 718 23 624 21 13,270 27 478 22
Low to middle 110 3 2,910 5 157 5 58 2 2,441 5 118 5
Low to high 44 1 2,856 5 260 8 21 1 1,930 4 107 5
Memo: Total 3,902 100 63,123 100 3,101 100 2,916 100 49,124 100 2,189 100
Moderate to low 2,323 16 56,946 9 2,078 13 1,955 18 47,304 10 1,622 14
Moderate to moderate 9,208 65 410,331 65 10,624 66 7,060 65 301,313 65 7,912 67
Moderate to middle 2,411 17 151,120 24 3,171 20 1,813 17 104,672 23 2,139 18
Moderate to high 153 1 11,099 2 268 2 100 1 8,766 2 155 1
Memo: Total 14,095 100 629,496 100 16,141 100 10,928 100 462,055 100 11,828 100
Middle to low 108 0 2,430 0 159 0 80 0 1,795 0 113 0
Middle to moderate 4,777 15 314,565 9 6,993 14 3,784 16 237,760 11 4,967 14
Middle to middle 23,710 74 2,590,180 76 37,884 75 17,496 73 1,696,802 75 25,712 75
Middle to high 3,359 11 500,753 15 5,360 11 2,577 11 313,465 14 3,588 10
Memo: Total 31,954 100 3,407,928 100 50,396 100 23,937 100 2,249,822 100 34,380 100
High to low 8 0 64 0 21 0 0 0 0 0 0 0
High to moderate 36 0 1,342 0 71 0 23 0 1,042 0 47 0
High to middle 2,664 18 380,064 13 4,516 16 2,076 19 253,190 14 3,052 17
High to high 11,907 81 2,515,553 87 22,791 83 8,750 81 1,530,101 86 14,399 82
Memo: Total 14,615 100 2,897,023 100 27,399 100 10,849 100 1,784,333 100 17,498 100

Note: For an explanation of the transition to updated census data, see the text discussion "Transition to the 2010 Census Data and Revised Census-Tract Boundaries." Census tracts are as defined in the decennial censuses for 2000 (Census 2000) and 2010.

1. For definitions of census-tract income categories, see table 14, note 4. Return to table

ACS American Community Survey.

Source: For census-tract locations of properties related to home loans, Federal Financial Institutions Examination Council, data reported under the Home Mortgage Disclosure Act; for branch office locations, data derived from the Summary of Deposits as of June 30, 2011.

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Loan Reclassification

Results are similar when the analysis considers reclassification of home loans instead of census tracts, but some of the transitions are more pronounced. An analysis using the Census 2000 and the 2005-09 ACS data indicates that about 24 percent of the home loans extended in 2011 and classified as falling in moderate-income census tracts would transition and be reclassified as falling in a middle-income census tract and that 2 percent of the loans would transition to a higher-income census tract. At the same time, about 9 percent of the loans falling in middle-income areas would be reclassified as falling in moderate-income areas. However, in terms of the absolute number of loans, had the new census-tract relative-income classifications been used in 2011, there would have been a net increase in mortgage lending to low- and moderate-income neighborhoods of about 150,000 loans, about 22 percent higher than the number of LMI loans in 2011 under current census-tract relative-income classifications (data derived from table 19).

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Branch Office Reclassification

For our analysis of the effects of the transition from the Census 2000 to the ACS-based data on the classification of branch offices by census-tract relative income, we use the location of branch offices as reported in the Summary of Deposits (SOD) as of June 30, 2011. The SOD is an annual survey, compiled by the Federal Deposit Insurance Corporation (FDIC), of branch office deposits for all FDIC-insured banking institutions.54 The data include the location (state, county, and census tract) of each branch (and headquarters) office and the dollar amount of deposits that are allocated to that branch by the banking institution. For this exercise, we excluded the locations of automated teller machines (ATMs). Although ATMs are considered in CRA performance evaluations under the "services test," it seems unlikely that ATM locations have much influence on home-lending activity, the main focus of this article.55 In total, the branch office analysis included about 98,000 branch offices.

As in the analysis of census tracts and home lending described earlier, our analysis of branch office reclassification indicates that the switch from Census 2000 data to the more recent ACS-based income data would have a notable effect on the classification of branch offices by census-tract relative income. For example, 20 percent of the branch offices that were classified as located in a moderate-income census tract using the 2000 income data would be reclassified as middle income, and 2 percent would be reclassified as higher income, using the 2005-09 ACS data. Because these branch offices would no longer be classified as located in lower-income census tracts, they would no longer be a focus of CRA attention. However, about 14 percent of branches classified as being located in middle-income census tracts based on Census 2000 data would be reclassified as being located in moderate-income census tracts, and consequently, these offices would gain emphasis in CRA performance evaluations. Because there are more branch offices in middle-income census tracts than in low- or moderate-income census tracts, the transition to the updated census information will result in a net increase of about 3,400 branch offices in areas that are the focus of CRA attention.

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Appendix A: Requirements of Regulation C

The Federal Reserve Board's Regulation C requires lenders to report the following information on home-purchase and home-improvement loans and on financings:

For each application or loan

  • application date and the date an action was taken on the application
  • action taken on the application
    • approved and originated
    • approved but not accepted by the applicant
    • denied (with the reasons for denial--voluntary for some lenders)
    • withdrawn by the applicant
    • file closed for incompleteness
  • preapproval program status (for home-purchase loans only)
    • preapproval request denied by financial institution
    • preapproval request approved but not accepted by individual
  • loan amount
  • loan type
    • conventional
    • insured by the Federal Housing Administration
    • guaranteed by the Department of Veterans Affairs
    • backed by the Farm Service Agency or Rural Housing Service
  • lien status
    • first lien
    • junior lien
    • unsecured
  • loan purpose
    • home purchase
    • finance
    • home improvement
  • type of purchaser (if the lender subsequently sold the loan during the year)
    • Fannie Mae
    • Ginnie Mae
    • Freddie Mac
    • Farmer Mac
    • private securitization
    • commercial bank, savings bank, or savings association
    • life insurance company, credit union, mortgage bank, or finance company
    • affiliate institution
    • other type of purchaser

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For each applicant or co-applicant

  • race
  • ethnicity
  • sex
  • income relied on in credit decision

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For each property

  • location, by state, county, metropolitan statistical area, and census tract
  • type of structure
    • one- to four-family dwelling
    • manufactured home
    • multifamily property (dwelling with five or more units)
  • occupancy status (owner occupied, non-owner occupied, or not applicable)

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For loans subject to price reporting

  • spread above comparable Treasury security for applications taken prior to October 1, 2010
  • spread above average prime offer rate for applications taken on or after October 1, 2010

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For loans subject to the Home Ownership and Equity Protection Act

  • indicator of whether loan is subject to the Home Ownership and Equity Protection Act

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1. A brief history of HMDA is available at Federal Financial Institutions Examination Council, "History of HMDA," webpage, www.ffiec.gov/hmda/history2.htm  Leaving the Board . Return to text

2. It is estimated that the HMDA data cover about 90 to 95 percent of Federal Housing Administration lending and between 75 and 85 percent of other first-lien home loans. See U.S. Department of Housing and Urban Development, Office of Policy Development and Research (2011), "A Look at the FHA's Evolving Market Shares by Race and Ethnicity," U.S. Housing Market Conditions (May), pp. 6-12, www.huduser.org/portal/periodicals/ushmc/spring11/USHMC_1q11.pdf  Leaving the Board . Return to text

3. A list of the items reported under HMDA for 2011 is provided in appendix A. The 2011 HMDA data reflect property locations using the census-tract geographic boundaries created for the 2000 decennial census. The 2012 HMDA data will use the census-tract boundaries constructed for the 2010 decennial census. Thus, in this article, census-tract population and housing characteristics reflect the geographies established for the 2000 census data. Return to text

4. For information about the Consumer Financial Protection Bureau, see www.consumerfinance.gov  Leaving the Board . Return to text

5. The FFIEC (www.ffiec.gov  Leaving the Board ) was established by federal law in 1979 as an interagency body to prescribe uniform examination procedures, and to promote uniform supervision, among the federal agencies responsible for the examination and supervision of financial institutions. The member agencies are the Board of Governors of the Federal Reserve System, the Consumer Financial Protection Bureau, the Federal Deposit Insurance Corporation, the National Credit Union Administration, the Office of the Comptroller of the Currency, and representatives from state bank supervisory agencies. Under agreements with these agencies and the Department of Housing and Urban Development, the Federal Reserve Board collects and processes the HMDA data. Return to text

6. For the 2011 data, the FFIEC prepared and made available to the public 48,347 MSA-specific HMDA reports on behalf of reporting institutions. The FFIEC also makes available to the public similar reports about private mortgage insurance (PMI) activity. The costs incurred by the FFIEC to process the annual PMI data and make reports available to the public are borne by the PMI industry. All of the HMDA and PMI reports are available on the FFIEC's reports website at www.ffiec.gov/reports.htm  Leaving the Board .

The designation of MSAs is not static. From time to time, the Office of Management and Budget updates the list and geographic scope of metropolitan and micropolitan statistical areas. See Office of Management and Budget, "Statistical Programs and Standards," webpage, www.whitehouse.gov/omb/inforeg_statpolicy  Leaving the Board .

Return to text

7. The only reported items not included in the data made available to the public are the loan application number, the date of the application, and the date on which action was taken on the application. Return to text

8. Some lenders file amended HMDA reports, which are not reflected in the initial public data release. A "final" HMDA data set reflecting these changes is created two years following the initial data release. The data used to prepare this article are drawn from the initial public release for 2011 and from the "final" HMDA data set for years prior to that. Consequently, numbers in this article for the years 2010 and earlier may differ somewhat from numbers calculated from the initial public release files. Return to text

9. For the 2012 reporting year (covering lending in 2011), the minimum asset size for purposes of coverage was $40 million. The minimum asset size changes from year to year with changes in the Consumer Price Index for Urban Wage Earners and Clerical Workers. See the FFIEC's guide to HMDA reporting at www.ffiec.gov/hmda/ guide.htm  Leaving the Board . Return to text

10. There were 138 institutions that ceased operations and did not report lending activity for 2011, but these nonreporting companies accounted for only 0.89 percent of the 2010 loan application records submitted under HMDA. Return to text

11. Lenders report the date on which they took action on an application. For originations, the "action date" is the closing date or date of origination for the loan. This date is used to compile data at the monthly level. Generally, the interest rate on a loan is set at an earlier point, known as the "lock date." The interest rate series in the figure is constructed from the results of a survey of interest rates being offered by lenders to prime borrowers. Since a loan's pricing likely reflects the interest rate available at the time of the lock date, the timing of the loan volume and interest rate series may be slightly misaligned in the figure. Return to text

12. Those entering into binding contracts to purchase their homes by April 30, 2010, were eligible for the tax credit. For more information, see Internal Revenue Service, "First-Time Homebuyer Credit," webpage, www.irs.gov/newsroom/article/0,,id=204671,00.html  Leaving the Board . Return to text

13. Our analysis in an earlier article suggested that one-half of the home-purchase loans in 2009 qualified under the first-time homebuyer tax credit program. See Robert B. Avery, Neil Bhutta, Kenneth P. Brevoort, Christa Gibbs, and Glenn B. Canner (2010), "The 2009 HMDA Data: The Mortgage Market in a Time of Low Interest Rates and Economic Distress," Federal Reserve Bulletin, vol. 96 (December), pp. A39-A77. Return to text

14. See National Association of Realtors (2011), "NAR Home Buyer and Seller Survey Reflects Tight Credit Conditions," news release, November 11, www.realtor.org/news-releases/2011/11/nar-home-buyer-and-seller-survey-reflects-tight-credit-conditions  Leaving the Board . Return to text

15. See analysis of the factors influencing refinance activity in Robert B. Avery, Neil Bhutta, Kenneth P. Brevoort, and Glenn B. Canner (2011), "The Mortgage Market in 2010: Highlights from the Data Reported under the Home Mortgage Disclosure Act," Federal Reserve Bulletin, vol. 97 (December), pp. 1-60. Return to text

16. See United Press International (2012), "Investor Purchases Soar 65 Percent," UPI.com, March 30, www.upi.com/Business_News/Real-Estate/News/2012/03/30/Investor-Purchases-Soar-65-Percent/9321333117717  Leaving the Board . Return to text

17. Research using credit record data suggests that in states that experienced the largest run-up in home prices, investors accounted for about one-half of the home-purchase loans. See Andrew Haughwout, Donghoon Lee, Joseph Tracy, and Wilbert van der Klaauw (2011), "Real Estate Investors, the Leverage Cycle, and the Housing Market Crisis," Federal Reserve Bank of New York Staff Reports 514 (New York: Federal Reserve Bank of New York, September), www.newyorkfed.org/research/staff_reports/sr514.pdf  Leaving the Board . Return to text

18. Nonconventional loans play a small role in certain segments of the home-purchase market. For example, nonconventional loans accounted for less than 1 percent of the loans extended to non-owner occupants for the purchase of a home in 2011. Also, nonconventional loans made up a relatively small share (about 24 percent) of the loans used to purchase manufactured homes (data derived from table 5). Return to text

19. For more-detailed analysis on the rise of government-backed lending in recent years, see Avery and others, "The 2009 HMDA Data." Return to text

20. In 1993, the Mortgage Insurance Companies of America, a trade association, asked the FFIEC to process data from the largest PMI companies on applications for mortgage insurance. These data largely mirror the types of information submitted by lenders covered by HMDA. However, because the PMI companies do not receive all of the information about a prospective loan from the lenders seeking insurance coverage, some items reported under HMDA are not included in the PMI data. In particular, loan pricing information and requests for preapproval are unavailable in the PMI data. In the PMI data, the reported disposition of an application for insurance reflects the actions of the PMI companies or, in the case of a withdrawal of an application, the action of the lender. Return to text

21. For a more detailed analysis of the decline in PMI issuance, see Avery and others, "The 2009 HMDA Data." Return to text

22. For the other applications that did not result in a policy being written, either the application was withdrawn, the application file closed because it was not completed, or the request was approved but no policy was issued. Return to text

23. Unless a junior lien is used for home purchase or explicitly for home improvements, or to refinance an existing lien, it is not reported under HMDA. Further, home equity lines of credit, many of which are junior liens, do not have to be reported in the HMDA data regardless of the purpose of the loan. Return to text

24. Although one of the few sources of information on loan sales, the HMDA data tend to understate the importance of the secondary market. HMDA reporters are instructed to record loans sold in a calendar year different from the year originated as being held in portfolio, leading the reported loan sales to understate the proportion of each year's originations that are eventually sold. Return to text

25. Some loans recorded as sold in the HMDA data are sold to affiliated institutions and thus are not true secondary-market sales. In 2011, 8.6 percent of the loans recorded as sold in the HMDA data were sales to affiliates. Return to text

26. See U.S. Department of Housing and Urban Development (2012), Quarterly Report to Congress on FHA Single-Family Mutual Mortgage Insurance Fund Programs, FY 2011 Q4 (Washington: HUD, January 31), http://portal.hud.gov/hudportal/HUD?src=/program_offices/housing/rmra/oe/rpts/rtc/fhartcqtrly  Leaving the Board . Return to text

27. The information provided in the tables is identical to that provided in analyses of earlier years of HMDA data. Comparisons of the numbers in the tables with those in tables from earlier years, including statistics on denial rates, can be made by consulting the following articles: Avery and others, "The Mortgage Market in 2010"; Avery and others, "The 2009 HMDA Data"; and Robert B. Avery, Neil Bhutta, Kenneth P. Brevoort, Glenn B. Canner, and Christa N. Gibbs (2010), "The 2008 HMDA Data: The Mortgage Market during a Turbulent Year," Federal Reserve Bulletin, vol. 96 (April), pp. A169-A211. Also see Robert B. Avery, Kenneth P. Brevoort, and Glenn B. Canner (2008), "The 2007 HMDA Data," Federal Reserve Bulletin, vol. 94 (December), pp. A107-A146; Robert B. Avery, Kenneth P. Brevoort, and Glenn B. Canner (2007), "The 2006 HMDA Data," Federal Reserve Bulletin, vol. 93 (December), pp. A73-A109; Robert B. Avery, Kenneth P. Brevoort, and Glenn B. Canner (2006), "Higher-Priced Home Lending and the 2005 HMDA Data," Federal Reserve Bulletin, vol. 92 (September), pp. A123-A166; and Robert B. Avery, Glenn B. Canner, and Robert E. Cook (2005),"New Information Reported under HMDA and Its Application in Fair Lending Enforcement," Federal Reserve Bulletin, vol. 91 (Summer), pp. 344-94. Return to text

28. For more about the rule changes related to higher-priced lending, see Avery and others, "The 2009 HMDA Data." Return to text

29. See Freddie Mac, "Weekly Primary Mortgage Market Survey (PMMS)," webpage, www.freddiemac.com/pmms  Leaving the Board ; and Federal Financial Institutions Examination Council, "New FFIEC Rate Spread Calculator," webpage, www.ffiec.gov/ratespread/newcalc.aspx  Leaving the Board . Return to text

30. In previous articles exploring the distortions created by the old loan pricing classification methodology (see Avery and others, "The 2009 HMDA Data"), we used an adjustment technique that tried to address those distortions. The adjustment technique was similar to the new reporting rules, though it was also clearly inferior to them and could not have been implemented without access to date information, which is not part of the public use file. Without this adjustment, comparison of higher-priced data for loans covered by the old reporting rules with such data for loans covered by the new ones is not appropriate. Even with the adjustment, it is not possible to adjust the data for loans reported under the old rules to make them fully comparable to data reported under the new rules. For this reason, we restrict our discussion here to the 2010 and 2011 data. Return to text

31. Unlike the threshold rules used to report higher-priced loans, the threshold rules used to identify HOEPA loans did not change between 2009 and 2010, and thus the 2011 number of HOEPA loans is comparable to those of earlier years. Return to text

32. HOEPA does not apply to home-purchase loans. Return to text

33. For example, see Dakin Campbell and Hugh Son (2012), "Wells Fargo Dominates Home Lending as BofA Retreats: Mortgages," Bloomberg, May 3, www.bloomberg.com/news/2012-05-03/wells-fargo-dominates-home-lending-as-bofa-retreats-mortgages.html  Leaving the Board . Return to text

34. We include all first-lien originations recorded in the HMDA data, regardless of purpose, loan type, or property type. Return to text

35. For this analysis, we consider only those loans originated in the first three quarters of the year; loans originated in the last quarter of the year are less likely to be reported as sold simply because there is not much time to sell the loan. Return to text

36. The data are drawn using a methodology to ensure that the same individuals can be tracked over time, and that the data are representative of all individuals with a credit record as of the end of each quarter. For more information on these data, see Donghoon Lee and Wilbert van der Klaauw (2010), "An Introduction to the FRBNY Consumer Credit Panel," Federal Reserve Bank of New York Staff Reports 479 (New York: Federal Reserve Bank of New York, November), www.newyorkfed.org/research/staff_reports/sr479.pdf  Leaving the Board . It is important to note that all individuals in the database are anonymous: Names, street addresses, and Social Security numbers are not included in the data. Individuals are distinguished and can be linked over time through a unique, anonymous consumer identification number assigned by Equifax. Return to text

37. This credit score is generated from the Equifax Risk Score 3.0 model. The Equifax Risk Score 3.0 is a credit score produced from a general-purpose risk model that predicts the likelihood an individual will become 90 days or more delinquent on any account within 24 months after the score is calculated. The Equifax Risk Score 3.0 ranges from 280 to 850, with a higher score corresponding to lower relative risk (for more information, see www.equifax.com  Leaving the Board ). For the exercise here, we track the credit score of each individual as of the quarter before he or she took out a mortgage. Although the lender may have used a different score to underwrite the loan, it is likely that the scores used here are reflective of such scores. Return to text

38. Changes in lending to different groups over the 2006-10 period were presented in an earlier article. See Avery and others, "The Mortgage Market in 2010." Return to text

39. See Avery and others, "The Mortgage Market in 2010." Return to text

40. See Avery, Brevoort, and Canner, "The 2006 HMDA Data"; Avery, Brevoort, and Canner, "Higher-Priced Home Lending and the 2005 HMDA Data"; and Avery, Canner, and Cook, "New Information Reported under HMDA." Return to text

41. See, for example, Andrew Haughwout, Christopher Mayer, and Joseph Tracy (2009), "Subprime Mortgage Pricing: The Impact of Race, Ethnicity, and Gender on the Cost of Borrowing," Federal Reserve Bank of New York Staff Reports 368 (New York: Federal Reserve Bank of New York, April), www.newyorkfed.org/research/staff_reports/sr368.pdf  Leaving the Board ; and Marsha J. Courchane (2007), "The Pricing of Home Mortgage Loans to Minority Borrowers: How Much of the APR Differential Can We Explain?" Journal of Real Estate Research, vol. 29 (4), pp. 399-439. Return to text

42. Excluded from the analysis are applicants residing outside the 50 states and the District of Columbia as well as applications deemed to be business related. Applicant gender is controlled for in the racial and ethnic analyses, and race and ethnicity are controlled for in the analyses of gender differences. Return to text

43. For purposes of presentation, the borrower- and lender-modified outcomes shown in the tables are normalized so that, for the base comparison group (non-Hispanic whites in the case of comparison by race and ethnicity and males in the case of comparison by sex), the mean at each modification level is the same as the gross mean. Return to text

44. Although results here are reported for nonconventional lending as a whole, the analysis controls for the specific type of government-backed loan program (FHA, VA, or FSA/RHS) used by the borrower or loan applicant. Return to text

45. See Avery and others, "The 2008 HMDA Data." Return to text

46. The Interagency Fair Lending Examination Procedures are available at www.ffiec.gov/PDF/fairlend.pdf  Leaving the Board . Return to text

47. Others have conducted similar research, comparing HMDA data with American Housing Survey data for the years 1995 through 2007. Our analysis confirms and expands on theirs by comparing HMDA data with a different data source and by extending the analysis through 2010. See McKinley L. Blackburn and Todd Vermilyea (2012), "The Prevalence and Impact of Misstated Incomes on Mortgage Loan Applications," Journal of Housing Economics, vol. 21 (June), pp. 151-68. Return to text

48. There are circumstances when applicants for mortgages do not need to report all income to a prospective lender in order to qualify for a home loan. As such, incomes reported on mortgage applications tend to be lower than actual total household income in the absence of deliberately overstated income. Return to text

49. Census 2000 and ACS microdata were extracted from Steven Ruggles, J. Trent Alexander, Katie Genadek, Ronald Goeken, Matthew B. Schroeder, and Matthew Sobek (2010), Integrated Public Use Microdata Series: Version 5.0 (machine-readable database) (Minneapolis: University of Minnesota). Return to text

50. We use data only for metropolitan counties reported in the ACS and census microdata. This restriction helps ensure comparability between the two data sources since the HMDA data provide much better coverage of mortgage originations in metropolitan areas. In addition, results were suppressed for states with fewer than 50 households contributing to the statewide figure. Return to text

51. Relative income is the ratio of the census-tract median family income to the median family income of the broader area (either the MSA or the nonmetropolitan portion of the state) where the census tract is located. Return to text

52. For a discussion of the shift to the 2006-10 ACS data for census-tract relative-income classification, see Federal Financial Institutions Examination Council (2011), "FFIEC Announces the Use of American Community Survey Data in Its Census Data Files," press release, October 19, www.ffiec.gov/press/pr101911_ACS.htm  Leaving the Board . The classification may change if the Office of Management and Budget (OMB) establishes new MSAs or alters the boundaries of existing MSAs. The OMB is scheduled to release new MSA delineations in 2013. Return to text

53. Using the 2005-09 ACS income data in this exercise is not ideal since the actual income estimates used for CRA and HMDA purposes will be obtained from the 2006-10 ACS data. To address the possibility that the 2005-09 ACS income data and the 2006-10 ACS income data for individual census tracts differ significantly, and consequently affect reclassification estimates, we conducted a second analysis that is limited to the subset of census tracts that have substantially similar boundaries as defined for the 2000 and 2010 censuses. Results are in the final six columns of table 19. As shown in the table, the patterns are very similar whether the analysis is done using the 2005-09 ACS data and the 2000 census-tract boundaries or the 2006-10 ACS data using only the substantially similar census tracts. Return to text

54. See Federal Deposit Insurance Corporation, "Summary of Deposits," webpage, www2.fdic.gov/sod  Leaving the Board . Return to text

55. CRA compliance evaluations focus on three aspects of performance: lending, services, and investment. For more information, see Federal Financial Institutions Examination Council, "CRA Rating Search Frequently Asked Questions," webpage, www.ffiec.gov/craratings/ratings_faq.htm  Leaving the Board . Return to text

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Last update: December 18, 2012