Key Insights from the Townstone Financial Redlining Complaint

Key Insights from the Townstone Financial Redlining Complaint

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In a recent Complaint filed by the Consumer Financial Protection Bureau (CFPB) against Townstone Financial, Inc. (Townstone), the CFPB alleges that Townstone violated Fair Lending laws by redlining certain geographic areas. The Bureau also asserts that Townstone engaged in practices that discouraged, on the basis of race, potential applicants living in or moving to majority-minority census tracts in the Chicago metro area from applying for residential mortgage credit.

According to a recent article prepared by Mayer Brown, LLC, the complaint marks the first time a federal regulator has made public a redlining enforcement action against a non-bank mortgage lender.  This action seems to confirm the CFPB’s position that redlining actions are not limited to depository institutions subject to the Community Reinvestment Act (CRA), thereby opening the door to future redlining complaints against non-depository mortgage lenders.

This article points to several ways lenders can ensure a robust risk management effort related to potential concerns about redlining.

Discrimination Based on Public Comments

Townstone operates primarily in the Chicago metro area. Townstone management hosted a weekly radio broadcast from 2014 through 2017 as a primary part of its residential mortgage marketing strategy. The complaint describes frequent statements by Townstone’s representatives disparaging areas of the City of Chicago and surrounding communities having majority Black populations, thereby discouraging area residents from applying to Townstone for mortgage loans.

  • Lenders should:
    • Develop and maintain robust training programs to help ensure that mortgage company representatives who interact with the public to use language that demonstrates a commitment to compliance with the Equal Credit Opportunity Act (ECOA) and
    • Review periodically marketing policies, internal correspondence and public comments for statements that may be perceived as discouraging applicants on a prohibited basis.

Discrimination Based on Lending Data

When a regulatory agency such as the CFPB becomes aware of potential overt discrimination or disparate treatment by a mortgage lender and relevant lending data appears indicate redlining, it is reasonable to expect the regulator to investigate – at least to the extent of conducting empirical evaluations of readily available data about lending activity in the key geographic areas. In this instance, the CFPB reviewed Townstone’s HMDA data and reached key conclusions:

  • Townstone was significantly less likely to take applications for residential mortgages across census tracts with majority Black populations than peer lenders during the 2014 – 2017 timeframe.
  • As a result, Townstone was much less likely to originate loans to borrowers in these census tracts than peers. And, among the few originations it made, the CFPB indicates that more than half were to Non-Hispanic, White consumers.

There is no evidence in the complaint that Townstone monitored its risk of redlining during the 2014-17 period. If this is the full story, it is unlikely that Townstone was aware of its precarious position.

  • Lenders with robust compliance programs conduct periodic assessments of potential redlining risk:
    • A regression-based approach that identifies peer lenders in the metro area and assesses whether majority-minority regions were much less likely to have applications or originations, controlling for a range of factors linked to the lender’s marketing and business strategy.
    • Mapping derived from data analysis to present at least three critical factors relevant to redlining – (a) their own HMDA data by census tract; (b) comparable data for their peers; and (c) demographic data for the census tracts. These maps will a provide a clear picture of those tracts that majority-minority tracts and enable observers to see whether there is the appearance of redlining.
    • In our experience, identifying potential redlining risk means collecting data such as these facts:
  • The Chicago metro area has a population of 9.5 million spread across 2,176 census tracts.
  • 19 percent of the census tracts are majority Black; 14 percent are more than 80 percent Black.
  • In 2014, Townstone accepted 613 HMDA-reported applications for a first-lien mortgage on a Chicago area property.
  • Defining peer lenders as all HMDA-reporting institutions in the Chicago metro area with similar lending volume means there were 89 HMDA reporters that had total applications of 50 to 200 percent of Townstone’s 2014 volume. In total, these 89 lenders accepted 54,014 applications.
    • From these datapoints, we determined that the applications Townstone took were 70 percent less likely to have come from majority Black census tracts (2.3 percent) than their peers (7.6 percent).
  • Conducting regression modeling enables lenders to assess whether legitimate, socio-economic factors not related to race or ethnicity would explain these apparent disparities.
  • Factors such as median household income, population, housing stock characteristics and type of lender (e.g., a bank, credit union or independent mortgage company) explain some of these differences between Townstone and its peers.
  • Controlling for these factors, however, regression results pointed to Townstone being significantly less likely to have received an application in majority Black tracts than its similarly situated peers.
    • We conducted comparable analyses for 2015, 2016 and 2017 and reached essentially the same results using regression techniques: Townstone was significantly less likely to originate a loan in majority Black tracts than its peers in each of the four years.

We concluded that our regression-based methods would have alerted the lender’s compliance risk management team early on about potential redlining concerns.

Moreover, visual evidence through mapping of Chicago’s census tracts – shown below for 2014 – would have provided a picture confirming the regression findings. The mapping can also help lenders recognize their redlining risk early and position themselves to identify gaps and develop marketing strategies for high-risk geographies.

Townstone Financial 2014 Distribution of Applications in Central Region of Chicago

Managing Redlining Risk

For each of the issues addressed in the Townstone Complaint, we encourage lenders to be pro-active. In our experience, regulators will react more favorably when they see the product of good faith efforts to monitor and maintain compliance with ECOA. Examples of well-documented, solid Fair Lending compliance efforts include:

    • Policies and procedures that define compliance with Fair Lending / redlining laws according to the circumstances of their organization;
    • Ongoing, strong training that encourages compliance by everyone at the lender;
    • Evidence that senior management is monitoring marketing activity throughout all communities the lender serves;
      • As noted above, key monitoring activities include regression-based modeling and mapping of lending activity on a geographic basis that detects redlining risk.

 

  • Evidence that senior management and the board of directors are aware of the geographic distribution of loan applications and originations, especially in comparison to its peers; and
  • Indications that management and the board of directors strategize to ensure future marketing and lending efforts take into account the results of the lender’s monitoring efforts.

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ADI consultants have been working with financial institutions on Fair Lending compliance for more than 20 years.  We routinely perform the types of regression-based analyses and mapping designed to detect and prevent redlining risk discussed in this article. If we find such risks, we work with our client to help to refine their marketing strategies to manage redlining and other forms of Fair Lending risk.

About the Authors

Paul Strasberg

Paul is ADI’s Senior Economist and lead consultant in ADI’s Fair Lending analyses to accurately measure potential Fair Lending risk. You can contact Paul at pstrasberg@adiconsulting.com or 703.740.4907.

Diane Elliott

Diane, a former regulatory compliance examiner, is an analyst at ADI with experience in Fair Lending, HMDA, CRA, and Anti-Money Laundering compliance.  You can contact Diane at delliott@adiconsulting.com or 703.594.8245.

July 28th, 2020|