Getting from Red to Green

By Kat Sanchez

Redlining enforcement actions remain prominent in the fair lending realm. So what is a responsible banker to do? We review our Home Mortgage Disclosure Act data to determine where we have risks. And perhaps delve into what might be causing disparities. But regulator expectations are increasing for how that analysis is performed. This article will provide some ideas on how you can strengthen your fair lending redlining program.

Redlining primer

Redlining is a form of discrimination that violates the Equal Credit Opportunity Act and Fair Housing Act on a prohibited basis, oftentimes on the basis of race. The core concepts are simple: Redlining is the practice of unlawfully denying credit to geographic areas with high concentrations of protected class residents. Redlining risk is the potential fair lending risk stemming from the disproportionate lack of lending to majority-minority census tracts within individual markets.

This article originally appeared as the cover story in the September/October 2019 issue of ABA Bank Compliance magazine.
Redlining takes on many forms, including the illegal practice of refusing to extend loans because of the predominant race, national origin, etc., of the residents of a neighborhood where the property is located. This also may include imposing loan terms that are less favorable, again, due to the race or ethnicity make-up of the property location. Some institutions overtly target certain applicants or areas with less advantageous products or services based on prohibited characteristics. In some instances, minority applicants would ordinarily qualify for a loan with an institution, except for the illegal practice of the institution denying the loan based on a prohibited basis. The term “redlining” is derived from the actual, literal practice of mortgage lenders drawing red lines around areas of a map where they refused to extend credit. Historically, these locations were in predominantly majority-minority census tracts.

Lenders are permitted to deny loans due to creditworthiness. However, lenders may not avoid extending loans based on where the property is located (for example, neighborhoods in majority-minority census tracts) or on a prohibited basis. The redlining challenge lenders face, from a compliance and fair lending risk standpoint, used to be where applications were made, in relation to the institution’s assessment area or “footprint,” as well as denials, market penetration, and branch location. But there is more to redlining risk than assessment areas, maps, and red sharpie markers. Understanding the bank’s footprint (inside or out) is achieved through root cause analysis and mitigates redlining risk.

To begin to understand a bank’s redlining risk, compliance officers often use software solutions with mapping tools to show the plot points where the bank made loans, where the bank received applications, and where branches or ATMs are located. All these data points are shown on a map which is overlaid against color coded areas to show the minority levels of the census tracts. Competitors or peer origination data, as well as income levels of the census tracts are often shown visually as well.

Redlining analysis

In addition to conducting a visual analysis, bankers use data analytics of applicant and loan volume and compare their activity to other peers in the market to determine their redlining risk level. The bank will need to determine how well it is penetrating the market compared to its peers.

Depending on the risk rating, a regulatory agency will conduct their own root cause analysis review on lending data. For example, the Office of the Comptroller of the Currency will perform a root cause analysis if a lender earns a “high risk” evaluation rating for three consecutive years. The areas for review may include the lender’s denials, originations, market penetration and branch locations and overall rating. Banks should be reviewing their records in each of these areas too.

Redlining root cause analysis

There used to be “easy” answers to explain potential redlining risk, where a lender’s assessment area included a large national park or a prison, to explain why applicant or loan volume was low. However, one area lenders should focus redlining risk mitigation efforts on is root cause analysis, or answering the “why” behind the traditional:

  • Who (applicants versus borrowers)
  • What (creditworthiness)
  • Where (location of a property)
  • When (the timing of when credit was extended)
  • How (a lender’s credit policy criteria)

Geography is still a key factor though. When in doubt… Google it! Outside of a lender’s standard mapping software, or the publicly available mapping via geocoding, inputting addresses into Google Maps helps to inform a lender’s redlining story. Google Maps includes satellite imaging that accounts for current data to explain why a lender may have limited lending in an area within their footprint. In addition to satellite imaging, Google Maps also provides updated street-level viewing for neighborhoods that is ordinarily unavailable through standard compliance-software modules. The purpose of root cause analysis should not be to only understand the institution’s redlining risk, but also to defend and explain the market area(s) strategy. Demonstrating awareness of an institution’s footprint by considering the above-mentioned variables, is key to root cause analysis.

Root cause analysis demonstrates an institution’s proactive approach to the consumers they service, the industry as a whole, and the shifting growth and evolution of their assessment areas. Root cause also factors in variables that may not ordinarily be considered in a standard mapping exercise to help explain lending practices. While the expectation remains that redlining prevention is part of an overall fair lending program, lenders should consider the often-overlooked root cause analysis as a critical strategic step in providing a holistic and comprehensive view of their lending practices. Root cause analysis enables institutions to maximize revenue and support community outreach, while at the same time mitigating potential fair lending redlining risk.

Root cause analysis should involve all key stake holders of the institution. This enables the entire institution to understand and take ownership of the holistic view of redlining risk.

Step 1: Look at your numbers

Lenders should look beyond assessment area maps and understand other variables, such as channels, by which applications are received. For example, a lender may have three distinct lending channels including retail, wholesale lending, and online applications. By analyzing and addressing redlining by channel, the lender may demonstrate that what appears to be redlining risk is explained by channels. In other words, a lender should perform an analysis of each channel within a given market rather than looking at the combination of channels together. In one market, the retail side could be driving your redlining risk while the wholesale and online areas are in line with expectations. You may have a different scenario in a second market where perhaps the online applications are skewing your results. It’s important to start with what your numbers are telling to help hone your analysis. In other words, it is important and valuable to understand alternative variables and segment the data population accordingly to get a more realistic view of the redlining risk.

It’s also important to stay focused on factors that could impact the particular redlining risk presented for the market. For example, if your analysis shows that your denial rates were significantly higher than your peers, you might focus on your credit practices. However, if your analysis points to a market penetration risk, then your root cause analysis should consider what might be preventing the bank from getting applications in high minority areas.

Step 2: Gather data about the market

Once you have a firm grasp on what the numbers are telling you, it’s time to learn everything you can about the market itself. A good place to start is information that is publicly available. For example, the U.S. Department of Housing and Urban Development’s Office of Policy Development and Research publishes a comprehensive housing marketing analysis for many markets that provides details on the underlying economic conditions and housing trends that could impact your ability to lend.

Gathering data about the market means considering:

  • Market demographics
  • Competition
  • Complaints
  • Internal factors (operations, for example)
  • Internal partners (Community Reinvestment Act team)

When reviewing publicly available data, be sure to review the market demographics. As an example, you may learn that the area is a hit with the younger crowd. While age is a prohibited basis by which lenders may not discriminate, lenders should review the age of applicants in their assessment areas to explain denial rates. If the properties in an urban area are valued at $750,000 and above, but the majority of residents are renters that are newly graduated from college with minimal starting salaries and student loan debt, they may not qualify for a loan based on debt-to-income ratio. In this situation a lender may want to consider developing a new product that supports first time home buyers. Alternatively, lenders should ensure that existing first-time home buyer programs are available and reasonably extended to all creditworthy applicants in their assessment areas, regardless of age.

When considering the external lending environment, be sure to take a look at the competition. Peer performance review is a standard practice of redlining analysis. Combined with an expanded understanding of the demographic or area, a lender’s peers—particularly if the peer has a unique or targeted business mode—is another meaningful variable for root cause analysis. For example, if English is not the predominant language in a market area, this could help explain low volume of applications. If a lender only has one branch location in an area that is predominantly Spanish-speaking, and the peer competitor lenders in the area have established, long term business models that are targeted to Spanish-speaking applicants, this would explain potential redlining risk. Lenders in this situation should consider ensuring the market managers and employees within these branches and areas understand who they are lending to and serving. Although a financial institution’s market strategy is set forth by executive management, the input from market leaders that are embedded in the actual footprint is critical. This input would also be valuable from a CRA perspective as assessment areas should be routinely reviewed and refreshed.

Lenders may also leverage complaints analysis as gathered and maintained by the Consumer Financial Protection Bureau. Complaint data related to mortgage lending activity is vital input into identifying similar issues, or avoiding them, when comparing one institution to its peers. As applicable to a lender’s business strategy, this information should be reviewed and included in root cause analysis for redlining risk.

You will also want to gather data that is particular to your institution. For example, how many branches do you have in the market. Branches increase market presence and provide consumer access to applications, and therefore extensions of credit from a lender. You may also consider the type of branches in the market. For example, traditional brick and mortar locations may lead to a different result than branches located in a grocery store. Branches have separate, notable branding, as well as more employees to handle volume. Branches that are embedded within storefronts, such as a grocery store, may be less well-known, and only have a limited number of staff or capabilities to intake applications. The type of branches a lender has should be considered when evaluating the root cause of redlining risk. Likewise, if an institution decides to launch a new, web-based application for mortgage loans in the calendar year that is only available via a proprietary, smart-phone based application, this could increase redlining risk. The lender should evaluate applications accordingly and document this as an explanatory variable. If it seems as though the majority of applications were concentrated in one area of a lender’s assessment area than another, could it be that the marketing campaign was targeted to a certain area and thereby neglecting the lender’s assessment area? Are smartphones more or less available and therefore used as access to credit for this institution? Overall, marketing strategy should be a factor when developing a lender’s redlining root cause analysis.

Another internal factor to consider is the bank’s credit standards. Particularly if the bank’s denial rate is high in a market, review your lending policies to determine if any underwriting factors could be discriminatory. It also helps to compare your standards to the market population. For example, there are several good websites that will provide data on information like the average credit score for an area. It may appear that the lender is not extending credit in certain areas of their assessment area, but understanding the average credit score in that area might help to explain why loan originations are low when compared to other neighborhoods. Likewise, denial rates would be explained through a review of the credit scores, independent of the lender’s judgmental underwriting.

When considering internal factors, lenders would benefit from a review of the performance of their operations and processing centers. Trends related to processing time and delayed closures, and whether these times vary by product type, may help to explain potential redlining. In some instances, affordable home loan programs take longer to process and close due to the level of effort related to documentation required, program qualification requirements (e.g., financial literacy education), etc. Loan officers may be reluctant to support these programs that would otherwise mitigate redlining risk if processing and operations related to these programs failed to monitor for efficiency.

Other internal partners may be able to help you research your redlining root causes. Consider partnering with the CRA team to inform on strategy as a constantly evolving cycle and solution to drive revenue and manage fair lending and redlining risk. One way to accomplish this is to develop a survey where standard questions related to the market territory are completed for each assessment area, by branch location, or market territory, etc. The objective of the survey is to identify high risk areas, opportunities for fair lending training, or opportunities for community outreach to the underserved. Compliance should support the first line by evaluating responses to the survey and determine which area(s) pose greater risk. Taking the higher risk assessment areas into consideration, Compliance may proactively monitor for increased redlining risk, and provide real-time feedback in the performance of that area via root cause analysis.

Taking action

After you’ve completed your root cause analysis, you’ll be better informed about what is causing the disparities that appeared in your analytical review. You can then determine whether the root causes are legitimate non-discriminatory factors or if you need to take action to correct a problematic factor. Be sure to document your research and these results.

Recent enforcement activity provides the industry with insight into what institutions and lenders can do now to ensure their fair lending programs consider all aspects of redlining risk, with a focus on root cause analysis to inform on the areas below:

  • Evaluate the institution’s CRA assessment area(s) and confirm the current footprint is reasonable and explained via results of the redlining root cause analysis.
  • Review the demographics in the assessment areas where branches are located to ensure majority-minority census tract areas have access to the institution’s lending, and/or develop a business case for opening or acquiring new branches to service the majority-minority census tracts.
  • Review the amount of credit the institution extends to majority-minority census tract areas and make the commitment to increase this amount year after year, including offering special interest rate reductions, closing cost and/or down payment assistance.
  • Review the institution’s marketing budget annually to ensure targeted marketing campaigns are initiated to support special loan products and appropriate outreach to underserved communities.
  • Review the investments to the majority-minority census tract areas and consider increasing current partnership commitments, and/or identify new opportunities with community-based non-profits that work with the majority-minority census tracts for affordable housing.
  • Require financial education outreach as part of the mandatory CRA activities of the institution, and target these volunteer opportunities in majority-minority census tracts to demonstrate the institution’s awareness of, and commitment to, the underserved neighborhoods in their footprint.
  • Document the redlining root cause analysis and ensure the overall fair lending program and institution’s business strategy (loan production goals, marketing strategy, community development, etc.) is inclusive of the results of the analysis.
  • Report redlining root cause analysis to executive management to obtain support for and buy-in of any proposed enhancements to the existing fair lending program, lending program, marketing strategy, community outreach, etc.

While the most recent federal redlining settlement does not include a civil money penalty, prior enforcement activity has demonstrated that redlining persists in majority-minority census tracts and underserved communities. Civil money penalties in recent years were issued for discrimination through redlining. While on the surface, it may appear that lenders have informed strategies via well-established CRA programs that in turn drives the fair lending program and mitigation of redlining risk, it is a best practice to continuously evaluate and understand and mitigate redlining risk via root cause analysis. From the majority language spoken in one area to the average credit score in another area, root cause analysis supports the fair lending program and provides a method of documenting efforts are made to extend credit to the community.

Kat Sanchez is a director in Protiviti’s risk and compliance practice based in Los Angeles. She specializes in consumer protection laws and regulations for the financial services industry and has nearly two decades of experience in the areas of regulatory compliance, banking, and consulting. She thanks Meg Sczyrba, CRCM, for her contribution to this article.