Public HMDA 2019 Overview and What Lenders Should Know

Premier Insights - Fair Lending - Public HMDA 2019 Overview and What Lenders Should Know

Below, we provide a summary of the recently released 2019 HMDA data, and keys for understanding the importance of these data.

The Basics

Enacted by Congress in 1975, and implemented by Regulation C, the Home Mortgage Disclosure Act (HMDA) is considered “the most comprehensive, publicly available information on mortgage market activity.”  Its purpose is to help show whether lenders are serving the housing needs of their communities; give public officials information that helps them make decisions and policies, and shed light on lending patterns that could be discriminatory.  Additionally, HMDA data can be used by industry, consumer groups, regulators, and others to assess potential fair lending risks and for other purposes.

Institutions covered by HMDA are required to collect and report specified information about each mortgage application acted upon and mortgages purchased. The data include the disposition of each application for mortgage credit; the type, purpose, and characteristics of each home mortgage application or purchased loan; the census-tract designations of the properties; loan pricing information; demographic and other information about loan applicants, such as their race, ethnicity, sex, age, and income; and information about loan sales.

In 2015, under the Dodd-Frank Wall Street Reform and Consumer Protection Act of 2010, the Consumer Financial Protection Bureau issued a final rule that included changes to some data points and authorized the Bureau to collect new and revised data points effective January 1, 2018.  This final HMDA rule made four primary changes: (1) mandated reporting of open-end lines of credit (LOCs); (2) changed the transactional coverage definition from loan-purpose-based to one based primarily on whether the loan was secured by a dwelling; (3) modified definitions and values of some existing data points; and (4) required reporting of 27 new data points. (More information about HMDA data reporting requirements is also available at https://ffiec.cfpb.gov/.)

It is important to note that a significant number of lenders are exempt from these latest requirements, and instead, report the data points that they were reporting previously.  On January 18, 2018, the House passed H.R.2954, the Home Mortgage Disclosure Adjustment Act.  The bill exempts certain depository institutions from collecting and reporting various expanded HMDA data points in the CFPB’s 2015 amendments to Regulation C that became effective on January 1, 2018.

The 2019 HMDA data are the second year of data that incorporated changes made to HMDA by the 2015 HMDA rule.

The Data

On June 24, 2020, the Federal Financial Institutions Examination Council (FFIEC) announced the availability of data covering HMDA on 2019 mortgage lending transactions.  This data included 5,508 U.S. financial institutions from banks, savings associations, credit unions, and mortgage companies.  Providing information about the applicants, the property securing the loan or proposed to secure the loan in the case of non-originated applications, the transactions, and identifiers, the data include a total of 48 data points.   A complete list of these points can be found in Appendix A of the FFIEC’s Filing Instructions Guide for HMDA Data Collected in 2019.

Using the census tract delineations, population, and housing characteristic data from the 2011–2015 American Community Survey (ACS), the data reflect metropolitan statistical area (MSA) definitions released by the Office of Management and Budget in 2018 that became effective for HMDA purposes in 2019.  Comparisons across the data are limited due to changes in HMDA definitions, values, and thresholds and due to the changes in MSA and census tract boundaries and updates to the population and housing characteristics of census tracts, especially those that follow the decennial census and five-year updates based on the ACS data.

The data collected can help the public assess how financial institutions are serving the housing needs of their local communities and facilitate federal financial regulators’ fair lending, consumer compliance, and Community Reinvestment Act examinations.  With that said, the data alone cannot be used to determine whether a lender is complying with fair lending laws because data do not include some legitimate credit risk considerations for loan approval and loan pricing decisions.

2019 Data Summary

In 2019, the number of reporting institutions declined to 5,508, down by about 3% from 2018.  Including information on 15.1 million home loan applications, the data consisted of 12.5 million closed-end applications, 2.1 million open-end applications, and, for another 442,000 records, financial institutions did not indicate whether the records were closed-end or open-end because of EGRRCPA’s partial exemptions.

Closed-end loan applications increased by 21 percent, and the number of open-end lines of credit applications decreased by 9 percent.  Another 9.3 million applications resulted in loan originations. These originations included 7.9 million closed-end mortgage originations and 1.1 million open-end lines of credit originations, such as home equity lines of credit.  Additionally, because of the EGRRCPA’s partial exemptions, 335,000 originations did not indicate whether they were closed-end or open-end.  The data also include information on approximately 151,000 preapproval requests that were denied or approved but not accepted.

From 2018 to 2019, the total number of originated closed-end loans rose 26%, increasing by about 2 million originations.  Increasing by 78%, refinance originations for 1-4 family properties rose from 1.9 million.  Additionally, home purchase lending increased by 4% from 4.3 million.

For single-family, owner-occupied home purchases, the HMDA Data showed that low-to-moderate-income borrowers accounted for 28.6% of purchases – up from 28.1% in 2018. Refinance loans to low- and moderate-income borrowers for first lien, 1-4 family, site-built, owner-occupied properties decreased from 30% to 23.8% in 2019.

Accounting for 33.4% of all new mortgages in 2019, loans backed by the Federal Housing Administration, Department of Veterans Affairs or federal farm programs were up slightly as compared with 2018 data when they accounted for 33% of new mortgages.  VA shares of refinances increased, while the FHA market share for refinances fell slightly.  At the same time, non-depository lenders’ market share declined slightly from 57.2% in 2018 to 56.4% in 2019.

Up from 6.7% in 2018, black borrowers accounted for 7% of single-family home purchase loans in 2019, and home purchase loan share for Hispanic-White borrowers rose to 9.2% in 2019 as compared with 8.2% in 2018.  The percentage of home purchase loans fell from 5.9% to 5.7% for Asian-American borrowers.

In 2019, the data noted that Black and Hispanic-White applicants experienced higher denial rates than non-Hispanic-White applicants for conventional home mortgages, but the agencies noted that “these relationships are similar to those found in earlier years.”  Additionally, HMDA data “cannot take into account all legitimate credit risk considerations for loan approval and loan pricing.”

What Lenders Should Know

There are (2) items to be aware of when it comes to HMDA data.  The first applies to the institutions that are reporting all of the new data points, and that is the need for fair lending analyses of these data on a regular basis.  This is absolutely critical, and we have discussed this extensively.  It is vitally important to know what these data may suggest about an institution’s lending practices.  For such reporting lenders, frequent analyses should be an active part of fair lending risk management.

The second item applies to ALL lenders and pertains to redlining risk.  This includes understanding and analyzing the geographic distribution and racial/ethnic composition of HMDA applications and originations relative to these distributions and compositions of the lender’s market area(s).  It is essential to understand that this is important for all institutions, regardless of size.

The Consumer Financial Protection Bureau (CFPB) recently took action against a small lender in the Chicago area for redlining, Townestone Financial, Inc.  This entity averaged only 740 applications per year.  Although the complaint filed by the Bureau alleges marketing activities with racial overtones both implicitly and explicitly, a significant portion of the complaint focuses on the distribution of the lender’s HMDA data relative to the demographic composition as well as to other lenders.

Below, citing directly from the complaint, are some examples:

Page 12 – 45.  Townstone drew few applications from African-American applicants throughout the Chicago MSA during the relevant period.  From 2014 through 2017, Townstone drew about 2,700 applications, of which only 37 (1.4%) came from African-Americans in the Chicago MSA.  During the same period, other mortgage Case: 1:20-cv-04176 Document #: 1 Filed: 07/15/20 Page 12 of 18 Page ID #:12 13 lenders in the Chicago MSA drew 1,217,223 applications, of which 119,370 (9.8%) came from African-American applicants.

Page 13 ­- 46.  Similarly, Townstone drew almost no applications from prospective applicants applying for mortgage loans for properties in African-American neighborhoods. During the relevant period, Townstone drew an average of five or six applications each year (0.8%, 0.8%, 0.7%, and 0.9% of all Townstone applications) for properties in high-African-American neighborhoods, even though such neighborhoods made up 13.8% of the Chicago MSA’s census tracts. 

Pages 13 & 14 – 48.  Statistical analyses of Townstone’s mortgage-loan applications in the Chicago MSA, as compared to its peer lenders during the relevant period, show disparities between Townstone and its peers in drawing mortgage-loan applications for properties in African-American neighborhoods. These disparities are statistically significant and demonstrate that there were applicants seeking mortgage loans for properties in African-American neighborhoods in the Chicago MSA from Townstone’s peers in much higher proportions than from Townstone.  These disparities further show that Townstone had no legitimate, non-discriminatory reason to draw relatively few applications for mortgage loans for properties in these African-American areas. 

Page 49. Specifically, Townstone drew a significantly smaller proportion of mortgage-loan applications for properties in majority African-American neighborhoods than its peer lenders operating in the Chicago MSA. While Townstone drew 2.3%, 1.4%, 1.4%, and 1.3% of its applications for properties in majority African-American neighborhoods from 2014 through 2017, respectively, Townstone’s peers drew 8.2%, 7.6%, 7.7%, and 8.1%—3.6, 5.4, 5.5, and 6.2 times that of Townstone. 

Further information as well as the complaint can be found here: https://www.consumerfinance.gov/policy-compliance/enforcement/actions/townstone-financial-inc/.

Note above how comparisons are made (1) based on penetration to other lenders, and (2) in relation to the demographic composition of the market area.  It is imperative that all lenders understand their own data in a similar fashion.  Further, these data are measured annually and as such, trends over time are critical as well.

Depository Institutions

For Community Banks, such data should be evaluated at a minimum at both the CRA assessment area level as well as the REMA (Reasonably Expected Market Area) level.  The assessment area is well known and defined, but less is understood about the REMA.  We have discussed this in previous posts, and important information can be accessed here: https://www.premierinsights.com/blog/fdic-releases-guidance-on-redlining-risk-and-the-concept-of-rema.

Summary

The HMDA public data released annually contains important information for risk management and evaluation.  Institutions would be well served to use these data as tools for assessing and mitigating risk.  Failure to use these data otherwise creates fair lending risk.

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