CFPB’s 2022 Fair Lending Report Focuses on Bias in Mortgage Lending, Redlining, Home Appraisals, Small Business Lending, and Shows Continued Skepticism of AI

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As shown by a new report, the Consumer Financial Protection Bureau (CFPB or Bureau) is focusing its fair lending work on mortgage origination and pricing, small business lending, redlining, and the use of artificial intelligence (AI) and machine learning models.

On June 29, the CFPB released its annual Fair Lending Report (Report) to Congress describing its fair lending enforcement and supervisory activities, guidance, and rulemaking for calendar year 2022. The Report satisfies the CFPB’s statutory responsibility to report annually to Congress on public enforcement actions taken pursuant to the Equal Credit Opportunity Act (ECOA).

According to the Bureau, its priorities for ECOA examination and enforcement actions are determined through a risk-based process, incorporating tips and leads from industry whistleblowers, advocacy groups, and government agencies, supervisory and enforcement history, consumer complaints, and results from analysis of Home Mortgage Disclosure Act (HMDA) and other data.

Notably, during 2022, the CFPB initiated 32 fair lending examinations or targeted reviews, which represents a 146% increase since 2020. Also during the last year, the CFPB, federal banking agencies, and the National Credit Union Administration (NCUA) cited 174 financial institutions for violations of ECOA and/or Regulation B. The Report also notes that during 2022, the CFPB investigated, or is actively investigating, potential discrimination in student lending, payday lending, credit cards, small business lending and mortgage lending, including redlining, “discriminatory targeting” (presumably related to marketing and advertising), and unlawful home valuation and mortgage pricing exceptions. The CFPB is also looking into potential discriminatory conduct under ECOA and the statutory prohibition on unfair acts or practices targeted at vulnerable populations and leading to bias in automated systems and models.

Assistant Director of the CFPB’s Office of Fair Lending and Equal Opportunity Patrice Ficklin issued a blog post announcing the release of the Report and highlighting the CFPB’s appraisal and redlining focus. “Families and entire communities are harmed by biased, inaccurate appraisals, as well as geographic discrimination, or redlining. Whether it takes the form of excluding neighborhoods with certain demographics from mainstream credit or targeting them with predatory products, the CFPB is combatting these unlawful practices to achieve meaningfully restorative outcomes for the affected consumers and communities.” The Report also notes that four of the five fair lending matters the CFPB referred to the U.S. Department of Justice during 2022 involved redlining issues.

The Report also repeatedly mentions the Bureau’s focus on the industry’s use of AI and machine learning — a practice that the CFPB has shown overt skepticism toward. The blog post states that “[c]onsumers and small businesses are not well-resourced to fight back against — and may not even know they are subject to — algorithmic bias, digital surveillance and data harvesting, dark patterns, and advanced technologies that are black boxes. The CFPB has increased its expertise in data science and analytics to ensure that we can identify fair lending violations at each stage of the credit lifecycle.” The blog post also notes that the Bureau will continue to take a “whole-of-government approach” to protecting consumers from harmful uses of artificial intelligence, citing to the interagency statement on enforcement efforts against discrimination and bias in automated systems issued in April 2023. The CFPB repeated its promise to hold creditors and third-party service providers accountable for fully complying with fair lending laws regardless of the technology they choose to use.

In addition, the CFPB highlighted its reports on the prominence of medical debt on consumer reports and the consumer finance challenges faced by rural communities as “shining a light on factors that may influence fair access to credit.

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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