CFPB SBREFA Panel Outline on AVM Rulemaking Addresses Potential for Algorithmic Bias In Home Valuations

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The CFPB recently issued an outline entitled Small Business Advisory Review Panel for Automated Valuation Model (AVM) Rulemaking.  While the outline addresses an upcoming joint rulemaking to implement quality control requirements for AVMs, the CFPB specifically focuses on the potential for AVMs to pose fair lending risks to homebuyers and homeowners.  The CFPB issued the outline pursuant to a requirement under the Small Business Regulatory Enforcement Fairness Act that it collect small entities’ advice and recommendations on the potential impacts on small entities of proposals under consideration and feedback on regulatory alternatives to minimize these impacts.

The Dodd-Frank Act amended the Financial Institutions Reform, Recovery, and Enforcement Act (FIRREA) to provide for a joint rulemaking to require that AVMs meet quality control standards designed to: (1) ensure a high level of confidence in the estimates produced by automated valuation models,  (2) protect against the manipulation of data, (3) seek to avoid conflicts of interest, (4) require random sample testing and reviews, and (5) account for any other such factor that the agencies determine to be appropriate.  In addition to the CFPB, the other agencies required to engage in the rulemaking are the Comptroller of the Currency, Federal Deposit Insurance Corporation, Federal Housing Finance Agency, Federal Reserve Board and National Credit Union Administration.  The CFPB’s version of the joint rule will apply to non-depository institutions.

In the outline, the CFPB indicates that it is considering proposing, pursuant to the fifth quality control factor noted above, a requirement that covered institutions establish policies, practices, procedures, and control systems to ensure that their AVMs comply with applicable nondiscrimination laws.  In announcing the outline, the CFPB stated that overvaluing homes can put family wealth at-risk, create reselling challenges, and lead to higher rates of foreclosure.  The CFPB also stated that “[l]ow valuations can jeopardize home sales and prevent homeowners from refinancing, which makes it harder to build wealth or make repairs. Systematically low valuations driven by biased appraisers may exacerbate existing disparities in the housing market.”  Focusing on AVMs, the CFPB stated “[c]omputer models and algorithms are additional tools for mortgage lenders and appraisers to improve valuation accuracy.  However, automated valuation models can pose fair lending risks to homebuyers and homeowners.  The CFPB is particularly concerned that without proper safeguards, flawed versions of these models could digitally redline certain neighborhoods and further embed and perpetuate historical lending, wealth, and home value disparities.”

With regard to the adoption of a specific quality control factor addressing discrimination concerns, the CFPB seeks input on whether it should adopt an approach that would provide covered entities with flexibility to design fair lending policies, practices, procedures, and control systems tailored to their business model, or adopt an approach that would be more prescriptive and include specific requirements.  The CFPB also seeks input on whether the adoption of a specific nondiscrimination factor is unnecessary because compliance with applicable nondiscrimination laws with respect to AVMs is already encompassed within three of the first four statutory quality control factors noted above that require a high level of confidence in the estimates produced by AVMs, protection against the manipulation of data, and random sample testing and reviews.

The CFPB must receive written feedback from small entity representatives by April 8, 2022 in order for the feedback to be considered and incorporated into the Small Business Review Panel Report. The CFPB requests that other stakeholders wanting to provide written feedback do so no later than May 13, 2022.

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DISCLAIMER: Because of the generality of this update, the information provided herein may not be applicable in all situations and should not be acted upon without specific legal advice based on particular situations.

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