Archive:18 September 2014

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Big Data takes a Big Step: CFPB Offers Insight into Its Fair Lending Proxy Methodology

Big Data takes a Big Step: CFPB Offers Insight into Its Fair Lending Proxy Methodology

By: Melanie BrodyAnjali Garg*
*Ms. Garg is not admitted in D.C. She is supervised by Stephanie Robinson, a member of the D.C. Bar.

The Home Mortgage Disclosure Act requires residential mortgage lenders to collect race and ethnicity information about loan applicants, and lenders, regulators and others routinely use this information to statistically evaluate whether there is a risk that a lender has discriminated against borrowers on a prohibited basis. With regard to other types of credit, with respect to which federal law generally prohibits the collection of demographic information, lenders and other interested parties must impute credit applicants’ race and ethnicity using proxies. For example, a lender could use the racial composition of the census tract in which a consumer resides to assign an assumed race to the consumer. Although proxying provides a way to evaluate fair lending risk in the absence of actual demographic data, there historically has not been a generally-accepted methodology for performing the proxy process, and this has made it particularly challenging to evaluate fair lending compliance for non-mortgage credit products.

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