New Frontiers for Fair Lending: Race & Ethnicity-Specific Redlining Analyses

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There are often game-changers in the world of regulatory risk.

These can be described as unexpected developments with respect to how regulators may interpret guidelines and rules or otherwise evaluate financial institutions. These can be as broad as agency-wide or even multi-agency, or can be more localized as a particular field office or even individual examiner perspective on certain issues.

Institutions should be aware of trends, and most in the compliance world do a great job of staying abreast. As compliance practitioners know, however, being able to keep these things front and center for management in a dynamic environment is difficult.

Some of these game-changers we have addressed in previous articles, such as fair lending attention to consumer lending and the anticipated expansion of fair lending examinations into small business.

One that has not been addressed are developments into how redlining may be evaluated.

How Redlining is Used

In most instances, redlining has been typically used to evaluate all racial and ethnic protected classes as a group. Generally done at the census tract level, the total minority percentage of each census tract is calculated in order to designate tracts as minority-majority.

Lending activity, such as applications and originations are then evaluated against some measure, such as population, families, housing units, or lending by other institutions. 

More Specificity in Redlining

An area that has not received much attention is the possibility of focusing not on a catch-all category of “minority,” but on a particular race or ethnicity.

This involves analysis of a subset of minority-majority census tracts by examining those that comprise a majority of one particular group, such as majority-Hispanic. In some markets, there may not be a distinction between the two, i.e. minority-majority or majority-Hispanic may constitute the same tracts, but in other markets these can be very different.

An institution’s lending may look far different when viewed in this way versus simply majority-minority. 

Impact on Lenders

Depending on the demographic composition of an institution’s market areas and the degree of segregation in terms of the neighborhoods and communities, this area of fair lending risk possibly should be a priority if it has not been previously considered.

One challenge, however, is that this information is not currently available with the public HMDA data. While the public data has the income level and minority percentage for each record available within the HMDA data, it is not possible to identify specific groups. This makes it more difficult to do peer-type comparisons. With the HMDA data it is easy to examine and compare lender penetration by tract total minority percentage and income level, but not specific racial or ethnic groups.

Again, depending on an institution’s geographic footprint, this may or may not be an area of fair lending risk. It is one, however, that each institution should be aware of and assess and address any risk accordingly.


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