[8] In 2021, Director Chopra again foreshadowed, [a]lgorithms can help remove bias, but black box underwriting algorithms are not creating a more equal playing field and only exacerbate the biases fed into them.[9], Given the increased use of black-box models and algorithms and under the leadership of Director Chopra, the Circular responded to the following question: When creditors make credit decisions based on complex algorithms that prevent creditors from accurately identifying the specific reasons for denying credit or taking other adverse actions, do these creditors need to comply with the Equal Credit Opportunity Acts requirement to provide a statement of specific reasons to applicants against whom adverse action is taken? The CFPBs short answer: Yes.[10], The CFPB confirms that ECOAs adverse action requirements apply equally to all creditors, regardless of the technology used for credit decisioning. 12 CFR part 1002 (supp. The FCRA also requires a creditor to disclose, as applicable, a credit score it used in taking adverse action along with related information, including up to four key factors that adversely affected the consumer's credit score (or up to five factors if the number of inquiries made with respect to that consumer report is a key factor). Pursuant to Regulation B, a statement of reasons for adverse action taken "must be specific and indicate the principal reason (s) for the adverse action." 5 Regulation B explains that " [s]tatements that the adverse action was based on the creditor's internal standards or policies or that the applicant, joint applicant, or similar party failed t. Moreover, no factor that was a principal reason for adverse action may be excluded from disclosure. The notice requirement fulfills a broader need as well by educating consumers about the reasons for the creditor's action. [7]See https://www.consumerfinance.gov/about-us/blog/innovation-spotlight-providing-adverse-action-notices-when-using-ai-ml-modelshttps://www.consumerfinance.gov/about-us/blog/innovation-spotlight-providing-adverse-action-notices-when-using-ai-ml-models/ that agencies use to create their documents. The CFPB also notes that it is considering the use of black-box models and algorithms beyond adverse action notices, referencing its recent spotlight on automated valuation models. vS" word/_rels/document.xml.rels ( j0Ei))l[UaI[}E C6{W#J&`]o4#y0u[F>'8h`dG $Gu#L(R3;/mK.x%s Rh&5i^;XPsh^4GP#zfvy rM,EIer8J?!q:di}!43LYK_1[98A/ PK ! The CFPB has announced a clear focus on fair lending, junk fees, voluntary protection products, and repossessions. [3] The CFPB has also represented that it hopes to facilitate the use of this promising technology [AI/ML] to expand access to credit and benefit consumers.[4] This support and these aspirations contrast starkly with the ominous tone of the CFPBs recent Circular, especially when juxtaposing its tone with that of a CFPB blog post published in 2020 during the prior administration by Patrice Alexander Ficklin, Director of the CFPBs Office of Fair Lending. 12 U.S.C. It is insufficient to provide vague or general statements that the adverse action was based on the creditor's internal standards or policies or that the consumer failed to achieve a qualifying score on the creditor's credit scoring system.[2]. better and aid in comparing the online edition to the print edition. The CFPB announced on March 16th that it will scrutinize discriminatory conduct that violates the federal prohibition against unfair practices in all consumer finance markets, including credit, servicing, collections, consumer reporting, payments, remittances, and deposits. See, e.g., As more technology platforms, including Big Tech firms, influence the financial services marketplace, the CFPB will be working to identify emerging risks and to develop appropriate policy responses. New CFPB actions portend increasing scrutiny and potential enforcement [11]See CFPB Acts to Protect the Public from Black-Box Credit Models Using Complex Algorithms | Consumer Financial Protection Bureau (consumerfinance.gov). Adverse action[s] include denying an application for credit, terminating an existing credit account, making unfavorable changes to the terms of an existing account, and refusing to increase a credit limit. 15 U.S.C. Creditors should be attentive to the potential for consumer harm that could arise out of the models or technology they choose to employ in the credit-decisioning process and take reasonable steps to ensure an understanding of and transparency in such models or technology. [12] [8] In 2021, Director Chopra again foreshadowed, [a]lgorithms can help remove bias, but black box underwriting algorithms are not creating a more equal playing field and only exacerbate the biases fed into them.[9], CFPB CONFIRMS THAT SPECIFIC REASONS FOR ADVERSE ACTION ARE REQUIRED, REGARDLESS OF THE TECHNOLOGY USED [9]See Remarks of Director Rohit Chopra at a Joint DOJ, CFPB, and OCC Press Conference on the Trustmark National Bank Enforcement Action | Consumer Financial Protection Bureau (consumerfinance.gov). This lack of access into or understanding of the models decisioning and rationale, can prevent creditors from being able articulate the specific reason(s) for an adverse credit decision. The Consumer Financial Protection Bureau (CFPB) has been contemplating data, algorithms, and machine learning for years. eCFR :: 12 CFR Part 1002 -- Equal Credit Opportunity Act (Regulation B) 9(b)(1)-4. Some Federal consumer financial laws are also enforceable by other Federal agencies, including the Department of Justice and the Federal Trade Commission, the Farm Credit Administration, the Department of Transportation, and the Department of Agriculture. Florida Enacts Bill Permitting Loan Originators to Work from Remote Locations, FTC Releases Annual Report to CFPB on 2022 Enforcement and Related Activities, OCC Fines Bank $15 Million over Deceptive Account Disclosures, FHA Releases Single Family Mortgage Related Resources in Multiple Languages, Agencies Seek Comment on Guidance on ROVs in Residential Transactions, Consumer Financial Protection Bureau (CFPB). establishing the XML-based Federal Register as an ACFR-sanctioned So while considering the fair lending and other implications of AI, algorithmic decision tools, machine learning, big data, and black-box models, consumer financial service providers also should keep traditional fair lending risks in mind. CFPB Issues Circular on Adverse Action Notice Requirements for Credit Using Consumer Reports for Credit Decisions: What to Know About Adverse [FR Doc. Those options no longer exist, and the blog now comes with a warning label: ECOA and Regulation B do not permit creditors to use technology for which they cannot provide accurate reasons for adverse actions. The OFR/GPO partnership is committed to presenting accurate and reliable 1002.9, para. Fischl [2]15 U.S.C. Report: CFPB monitoring developments in fair lending technology 1691(d)(2)(B). Network, Inc., a company using alternative data to make credit and pricing decisions. While some creditors may rely upon various post-hoc explanation methods, such explanations approximate models and creditors must still be able to validate the accuracy of those approximations, which may not be possible with less interpretable models. 1976 U.S.S.C.A.N. [6]See https://www.consumerfinance.gov/about-us/blog/innovation-spotlight-providing-adverse-action-notices-when-using-ai-ml-models/ C), comment 4 (emphasis added). This table of contents is a navigational tool, processed from the [2], In the Circular, the CFPB acknowledges that although financial institutions have long used complex underwriting and other computational methods for driving credit risk decisions, they are still able to provide specific adverse action statements to comply with ECOA. On May 26th, 2022, the Consumer Financial Protection Bureau ("CFPB") published a Consumer Financial Protection Circular (the "Circular"), confirming that creditors must provide specific reasons for taking adverse action against an applicant, even when the creditor relies on black-box models or complex algorithms for credit-making decisions. Circulars@cfpb.gov. Technology companies and financial institutions are amassing massive amounts of data and using it to make more and more decisions about our lives, including loan underwriting and advertising. Gen. Motors Acceptance Corp., PDF Consumer Financial Protection Circular 2022 -03 The regulation does not require that a creditor use the term adverse action in communicating to an applicant that a request for an extension of credit has not been approved. This lack of access into or understanding of the models decisioning and rationale, can prevent creditors from being able articulate the specific reason(s) for an adverse credit decision. Only official editions of the In 2020, the CFPB blogged that Regulation Bs flexibility can be compatible with AI algorithms, because although a creditor must provide the specific reasons for an adverse action a creditor need not describe how or why a disclosed factor adversely affected an application, how a factor relates to creditworthiness, or use any particular list of adverse action reasons. In Director Chopras April 2022 Congressional testimony, he said: The outsized influence of such dominant tech conglomerates over the financial services ecosystem comes with risks and raises a host of questions about privacy, fraud, discrimination, and more.. Previously, the CFPB has appeared supportive of AI, machine learning, and the use of alternative data in expanding consumers access credit. CFPB Says Creditors Must Provide Reasons For Taking Adverse Action, Even When Relying On AI, Previously, the CFPB has appeared supportive of AI, machine learning, and the use of alternative data in expanding consumers access credit. 1691(d)(2)(A), (B); 12 CFR 1002.9(a)(2)(i), (ii). Creditors who use complex algorithms, including artificial intelligence or machine learning, in any aspect of their credit decisions must still provide a notice that discloses the specific principal reasons for taking an adverse action. On July 26, 2022, the Office of the Comptroller of the Currency (OCC) issued anupdateto its 2013 policy statement on minority depository institutions (MDIs). The CFPB is keenly focused on the risks that these technologies present to individual consumers, small businesses, communities and the market as a whole, the agency said. principal reasons for any adverse action determination. 12 CFR 1002.9(b)(2). The CFPB also warns that a creditor cannot justify noncompliance with these requirements based on the mere fact that the technology it employs to . The statement of reasons must be specific and indicate the principal reason(s) for the adverse action.[16] c=1PR'PHb:F:U!HB8!43h9p!h}8jN53. You'll simply need to customize it to fit your own institution's credit policy before use. The CFPB cited adverse action violations in an enforcement action in September 2021, and in an amicus brief and advisory opinion in December 2021 and May 2022, respectively, argued that adverse action and other Regulation B and Equal Credit Opportunity Act protections apply to an "applicant" throughout the credit cycleand have since 1974. The CFPBs algorithm-related changes may reach all segments of the market for consumer financial services, from lending and marketing to credit reporting, appraisal practices, appraisal companies, deposit taking, and so on. I), sec. 12 CFR 1002.2(c). 708 F.2d at 146); CFPB Issues Circular Explaining the Adverse Action Notification 5536(a)(1)(B), and 18 other enumerated consumer laws, 12 U.S.C. They do not restrict the Bureau's exercise of its authorities, impose any legal requirements on external parties, or create or confer any rights on external parties that could be enforceable in any administrative or civil proceeding. On May 26th, 2022, the Consumer Financial Protection Bureau (CFPB) published a Consumer Financial Protection Circular (the Circular), confirming that creditors must provide specific reasons for taking adverse action against an applicant, even when the creditor relies on black-box models or complex algorithms for credit-making decisions. Consumer Financial Protection Circular 2022-03: Adverse action . CFPB Takes Adverse Action Against Machine Learning 1333 New Hampshire Ave NW About the Federal Register Treadway The CFPB has previously acknowledged the potential consumer benefits of AI and other technologies. Thus, ECOA and Regulation B do not permit creditors to use complex algorithms when doing so means they cannot provide the specific and accurate reasons for adverse actions. 1691(d)(3). Start Printed Page 35866 SUMMARY: The Consumer Financial Protection Bureau (CFPB) is issuing this advisory Consumer Financial Protection Circulars Podcast: Perspectives from two bank risk and compliance leaders, Podcast: The anatomy of a community bank ransomware attack, Podcast: Analyzing first-quarter earnings and 2023 annual meetings. electronic version on GPOs govinfo.gov. C), comment 3. 16. Her 2020 blog post evoked a spirit more accommodating of innovation by industry participants and experimentation with AI models, citing ECOA[5] in acknowledging that the existing regulatory framework has built-in flexibility that can be compatible with AI algorithms.[6], The CFPB, however, has since added a disclaimer to that 2020 blog post, warning that it conveys an incomplete description of the adverse action notice requirements of ECOA and Regulation B and that ECOA does not permit creditors to use technology for which they cannot provide accurate reasons for adverse actions, referring readers instead to the Circular. The adverse action notice requirements of ECOA and Regulation B, however, apply equally to all credit decisions, regardless of the technology used to make them.
Legal Ways To Get Revenge, Articles C