As any bank professional regulatory compliance professional knows redlining is the hottest issue today and has been since Attorney General Merrick Garland announced the “Combatting Redlining Initiative” in October 2021. Since then, the AG’s office has announced a record number of referrals by the prudential bank regulators accusing banks of redlining. We at GeoDataVision have reviewed a number of the redlining complaints filed by the DOJ and we have had the opportunity to work with a number of banks that have been evaluated by examiners for potential redlining. We think it is important to share with compliance professionals what we have learned and how it may help institutions avoid a referral to the DOJ for redlining accusations.

First, it’s of the utmost importance to maintain a risk management system that monitors potential redlining. Virtually every DOJ complaint alleges that institutions accused of redlining did not have an adequate risk management system in place. It’s bad enough to be accused of redlining. It’s worse to be accused of being ignorant.

Second, although the natural instinctive response to examiner questions about potential redlining is to take offense (after all, how many institutions deliberately redline?) and to assume an adversarial position, it’s far better to take a collaborative approach. This does not mean that you concede to accusations. It means that you take a “let’s work together to address your (examiner) questions and get to the bottom of what appears (to the examiner) to be redlining” approach. This should be a team effort. The last thing you want is an adversarial process.

We saw this approach work in a situation where potential redlining was raised by examiners. The bank said, “let’s dig beneath the numbers to see what is creating questions about potential redlining.” Sometimes examiners say, “Be prepared to tell your story.”  It’s easy to see the numbers. But knowing the numbers and understanding the numbers are two entirely different things. Ideally, your risk management system should have already identified a potential redlining risk and determined if it is real or not. If some data creates the appearance of redlining and you’ve uncovered an underlying explanation that exonerates your institution, be prepared to share that with examiners. If you uncover a real problem, develop a plan of action to correct it. 

Third, develop, implement, and document an active community outreach program to develop an understanding of the community, particularly the low- and moderate-income and minority communities. Sometimes this is referred to as a "Community Needs Assessment".

Fourth, a very big factor underlying the dramatic increase in redlining referrals and complaints is how the market is defined. For redlining analysis examiners use a concept called a “REMA”, or “reasonably expected market area”. The concept of a REMA is not defined in statute nor in regulation. It’s a concept that originated around 2009.

Until 2021, regulators in examiner manuals and in various webinars, explained the factors considered when defining a REMA for a financial institution. Among the parameters considered were how a bank delineated its CRA assessment area(s), the geographic dispersion of a lender’s HMDA mortgage applications, the location of any LPOs, and the areas covered by any marketing campaigns. This approach changed markedly after October 2021.

During 2022 examiners adopted a radical change and began considering REMA’s to consist of entire MSA’s or Metropolitan Divisions, or groups of counties in non-MSAs. For money-center banks this broad interpretation normally does not present a problem (although it may in some cases). But for many community banks this expansive interpretation results in unrealistically large REMAs and unrealistic REMAs mean unreliable if not misleading statistical analysis.

Fifth, as mentioned earlier, it’s important to not only know the numbers, but to understand the numbers. An excessively large REMA can lead to flawed statistical analysis in at least two different ways. First, many community banks may not have the resources to serve very large markets. This means a bank may be compared to lenders in a part of a MSA in which the bank has no facilities and has never considered to be its market. Second, even if a community bank does attempt to market to an entire MSA, its facilities and resources will not necessarily be spread evenly throughout the REMA and the REMA itself may contain uneven population demographics.

We have seen numerous situations in which a community bank includes 4 or 5 counties within its CRA assessment area and there has been a concentration of majority-minority tracts in one of those counties. The uneven geographic distribution of majority-minority tracts can undermine the validity of statistical analysis.

Sixth, the REMA concept as practiced today does not appear to allow for banks entering new markets. It seems that examiners expect a bank to immediately attain market penetration that can take years to achieve. This is a big flaw in statistical analysis if not recognized as a “hidden variable”.

When examiners apply the REMA concept, they always apply it to the entire market. This aggregated approach can create a very misleading statistical picture called Simpson’s Paradox in which statistical analysis of the aggregated market is contradicted by statistical analysis of the disaggregated market. Consequently, it is recommended that banks evaluate their redlining risk exposure by applying it to the aggregate market and also the disaggregated market to determine if the resulting statistical analyses are consistent or contradictory. If results are inconsistent, it’s a sign of what’s sometimes called, “the hidden variable”, that explains the inconsistency and paints a much more accurate picture of the true situation.

Recap

• Develop and maintain a risk management system that identifies risk and exposure before examiners do
• The collaborative approach usually works better than the combative approach
• Develop a community needs assessment
• Determine what your REMA may be and the consequences versus what your true market may be
• Be aware that when you open new branches in new markets you are exacerbating your redlining risk exposure because regulators don’t appear to recognize de novo markets in their statistical analysis models
• Understand statistical analysis – remember, it’s not enough to know the numbers. You must understand the numbers. Consequently, be aware of circumstances that may invalidate statistical analysis