HUD’s Implementation of the Fair Housing Act’s Disparate Impact Standard

Published by the R Street Institute.

EDWARD J. PINTO and TOBIAS J. PETER                       ALEX J. POLLOCK

AEI Housing Center                                         R Street Institute

September 26, 2019

Department of Housing and Urban Development

Regulations Division

Office of the General Counsel

451 7th Street SW

Washington, DC 20410

Submission via www.regulations.gov

 

Dear Sir/Madam:

Re.: Docket No. FR-6111-P-02; RIN: 2529-AA98

HUD’s Implementation of the Fair Housing Act’s Disparate Impact Standard

Thank you for the opportunity to comment on this proposed rule on the Disparate Impact Standard. The authors of the comment have many years of experience in housing finance, as operating executives, analysts, and students of housing finance systems and their policy issues.  We believe this rulemaking has the potential to significantly improve the existing standard.

Our fundamental recommendation is that the consideration of disparate impact issues must be able to include credit outcomes, i.e. default rates, not only credit underwriting inputs.  Specifically:

  1. Mortgage lenders, including smaller lenders, should have the option to use a credit outcomes-based statistical approach, as defined below, which qualifies as a valid defense under the Disparate Impact rule. This would improve the fairness, operation, and statistical basis of the rule.

  2. HUD should develop a credit outcomes-based statistical screening approach that allows it to assess with a high degree of confidence, whether differences in mortgage lending results raise disparate impact questions for further review.

In both cases, the ability to use credit outcomes would enhance clarity and reduce uncertainty.

Problems with the Pure Input Approach

Applying its credit standards in a non-discriminatory way, regardless of demographic group, is exactly what every lender should be doing.  Typically, the question of whether this is being carried out has been approached by looking only at inputs to a lending decision.  This results in a focus on differing credit approval/credit decline rates between protected and non-protected classes.  The argument is then made that the existence of differing credit approval/credit decline rates between classes is evidence of discrimination even if a lender applies exactly the same set of credit underwriting standards to all credit applicants.[1]

Read in full here.

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