As a nearly $9 million settlement between federal regulators and Trustmark National Bank makes painfully evident, few things present more unwelcome press for mortgage bankers and servicers than accusations of redlining or discrimination. Despite the inherent and omnipresent risks associated with discriminatory lending practices, the mortgage industry’s management of these risks too often ebbs and flows with the fickle tides of politics in the nation’s capital.
In fact, for much of the past two decades, fair lending was an active area of litigation by federal agencies and private entities. This changed during the Trump administration, when fair lending enforcement appeared to become relatively dormant.
Today, under the Biden administration, the mortgage industry is seeing an increased focus on fair lending enforcement. Originators and other mortgage professionals should understand what is occurring and why this is happening while mortgage companies should redouble efforts at remaining compliant with federal laws.
Established law
The federal fair lending laws include the Fair Housing Act, the Equal Credit Opportunity Act, the Civil Rights Act, the Community Reinvestment Act (CRA) and the Home Mortgage Disclosure Act (HMDA). The last one is especially important because it requires lenders to collect and disclose information on individual loan applications (e.g., sex, race, ethnicity, age and national origin of applicants).
It’s important to understand disparate impact theory of discrimination because it has become the basis of many fair lending cases over the years.
Since 2018, the Consumer Financial Protection Bureau (CFPB) has collected dozens of additional data points on individual loan transactions due to the Dodd-Frank Act’s expanded reporting requirements under HMDA, which is the primary data for building or defending fair lending court cases. In fair lending enforcement, the government has identified three types of discrimination:
Overt discrimination. A lender openly discriminates against a mortgage applicant or borrower on a prohibited basis.
Disparate treatment. A lender treats an applicant or borrower differently on a prohibited basis when offering and approving loan types, e.g., higher-priced loans are offered and approved more frequently for minority applicants than non-Hispanic white applicants with a similar credit profile.
Disparate impact. Unlike overt discrimination and disparate treatment, disparate impact deals with the outcome of a lending activity. The issue here is that a lender equally applies the same policies or procedures to all applicants, but these practices result in adverse effects for a protected class of applicants or borrowers. A classic example is when a lender analyzes its HMDA data to discover that it has disproportionately denied loan applications of protected-class applicants.
Under the 2013 rule, the lender bears the burden of explaining and rebutting the claim of disparate impact on a protected class, and to show a “business necessity” (i.e., the lender’s costs, profitability or competition). These claims, based on the disparate impact theory, rely heavily on statistical analyses as proof of discrimination. The Department of Justice (DOJ) has the authority to bring claims against mortgage lenders that engage in a practice or pattern of discrimination against members of protected classes.
The tricky thing here is that even if the lender can produce an analysis in its defense, the courts can find the lender in violation of the Fair Housing Act if another practice could serve the same purpose with less discriminatory effect. This leaves all lending institutions (both depository and nondepository) exposed to fair lending claims brought by a variety of government agencies, regulators and others.
Enforcement priorities
Let’s consider how CFPB does its fair lending enforcement work. The bureau engages and prioritizes risks which, as the bureau points out in its 2021 Fair Lending Report, entails the identification of emerging developments and trends through monitoring of the residential mortgage origination market.
If market intelligence identifies fair lending risks in a particular market, this information is used to determine the type and extent of attention required to address these risks. The prioritization process incorporates a number of additional factors, including results from analysis of HMDA and other data. CFPB looks for patterns of redlining (and whether lenders intentionally discourage prospective applicants living in or seeking credit in minority neighborhoods from applying for credit), and for patterns of discrimination in underwriting and pricing processes, such as steering.
If regulators conduct a data analysis that leads them to believe that a lender has engaged in a pattern of discouraging or denying applications on a prohibited basis, they must refer the matter to the DOJ. In addition, regulators can independently pursue their own administrative enforcement actions against the lender if the DOJ declines to pursue the referral. In addition, this past summer, there was a joint memorandum signed by HUD and the Federal Housing Finance Agency (FHFA) to jointly pursue fair lending enforcement.
The CFPB’s Fair Lending Report acknowledges the economic fallout of the COVID-19 pandemic, but also says that the bureau’s fair lending work is (and will continue to be) a critical component of the elimination of racial injustice. The report notes that the bureau’s Fair Lending Office will be front and center in the effort to advance racial and economic equity.
With rising interest rates, refinance opportunities will slowly dry up. Lenders and originators will soon be facing both smaller markets and increased regulatory oversight, as well as the threat of enforcement actions by numerous federal regulators.
Strategic compliance
One obvious tactic is to hire more compliance officers or invest in more compliance solutions. Lenders have been doing this. In fact, the compliance function has been elevated since the end of the housing crisis of the late 2000s. It remains more of a reactive function, however, than a strategic one.
In an era of tight markets and broader regulation assisted by advances in artificial intelligence and machine learning, lenders should think more strategically about their compliance process and take proactive measures to understand what’s ahead for them. Understanding and owning their story, market by market, is a smart first step that every lender could take. This includes looking at the number of applications from low- and moderate-income areas versus higher-income areas, and from protected-class applicants in context with their peers in the market; denial rates and reasons for denial among protected classes; as well as rates, fees and many more dimensions available for analysis in HMDA or CRA data.
A second and less obvious — but highly effective — tactic is to provide access to responsible credit remediation services to every consumer denied due to insufficient credit or those at risk of foreclosure. Some of the most responsible credit remediation services utilize HUD-certified nonprofit counselors to develop customized action plans. These help consumers to not only qualify for a lender’s programs or remain in their homes but also develop lifelong skills for credit management.
CRA and HMDA are the two main datasets disclosed each year to the public. It is low-hanging fruit for every lender to take steps to comb through the relevant public datasets so they can understand their own lending patterns in relation to their peers and also in the context of the communities they serve. This is the first and most important step available to all lenders, because the data is publicly available and everyone has access to it. HMDA and CRA analyses point to outcomes of lender decisions, which are the basis of fair lending court cases centered on disparate impact theory, negative publicity and enforcement actions by federal agencies.
HMDA and CRA are two massive datasets that are impossible to fully understand with simple queries or Excel analysis. They demand serious exploration with the assistance of powerful statistical software to help lenders derive necessary insights. Lenders should look for software-as-a-service solutions that do not require downloads or implementation but can be accessed immediately and on demand. This will allow team members to share insights with each other and engage in important conversations about the meaning of data, rather than spending enormous amounts of time prepping and crunching the data.
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The mortgage industry should applaud the efforts of the DOJ, the FHFA and the Office of the Comptroller of the Currency to align processes and share lender performance data whenever possible. Without question, the growing chorus of regulators that are determined to end discriminatory practices requires mortgage lenders, servicers and all entities involved in the origination process to increase their focus on fair lending efforts and ensure that they are overachieving in this area.
In this industry, the reality is that a single complaint, whether verified or not, can trigger an unwelcome investigation into lending patterns that may result in significant reputational and financial damage. Why not adopt a responsible, proactive approach that demonstrates your intent and desire to make the dream of homeownership available to all consumers? ●
Jeff Walker is the co-founder and CEO of CredEvolv, a fintech platform that revolutionizes the way consumers achieve and maintain good credit. CredEvolv’s mission is to turn “no” into “not yet” by breaking down the barriers to credit equity and guiding consumers who seek improved credit on a journey to sustainable, lifelong credit health. Prior to founding CredEvolv, Walker held a number of mortgage industry leadership positions, most recently with Fannie Mae.
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