CFPB Provides New Guidance on Discrimination in Algorithmic Credit Decisions | Bradley Arant Boult Cummings LLP

As we have discussed several times this year in our Financial Services Outlook blog, the current leadership of the CFPB has emphasized lending equity. Seemingly once a month, or even more frequently at times, Director Rohit Chopra announced a new initiative addressing fair lending and discrimination in the financial services industry. In February, for example, the CFPB published a blog post to discuss possible discrimination in the assessment process, and in March the CFPB announced major changes to its oversight operations with respect to practices. “unfair” discrimination in the financial services sector. Also in March, Director Chopra released a statement regarding the final report of the Interagency Property Valuation and Equity (PAVE) Task Force and, in doing so, emphasized accuracy and non- -discrimination in the algorithmic evaluations of houses. To that end, Director Chopra and other CFPB staff have also made numerous recent public statements to express concerns about “algorithmic bias”, “digital redlining”, and “robotic discrimination”.

The trend continued this week, as the CFPB issued a circular (Circular 2022-03) on May 26, 2022, to clarify creditors’ responsibilities to consumers when relying on “box” underwriting models. black” or “algorithmic” to make credit decisions. Concurrent with the issuance of Circular 2022-03, the CFPB also issued a press release to explain the rationale for issuing new guidance regarding notice of adverse action creditor requirements under the Act. on Equal Credit Opportunity (ECOA). According to manager Chopra, “[c]Companies are not exempt from their legal responsibilities when letting a black box model make lending decisions,” such as “[t]The law gives every applicant the right to an accurate explanation if their credit application has been denied, and that right is not diminished simply because a company uses a complex algorithm that it does not understand.

Circular 2022-03 provides guidance to answer the following question: “When creditors make credit decisions based on complex algorithms that prevent creditors from accurately identifying specific reasons for denial of credit or making other adverse actions, do these creditors have to comply with equal credit? The Opportunity Act requirement to provide a statement of specific reasons to candidates against whom adverse action is taken? Given the CFPB’s recent review of algorithmic decision-making in lending, the answer to this question was, unsurprisingly, “Yes.” In responding to this question, the CFPB provided the following guidance:

  • “ECOA does not allow creditors to use technology that prevents them from providing specific and accurate reasons for adverse actions. Creditors’ use of complex algorithms should not limit the application of ECOA or other federal consumer financial protection laws. In making this clarification, the CFPB explained that creditors subject to Rule B to have to be able to provide a statement of the reasons for any adverse action that (a) is “specific” and (b) indicates the primary reason(s) for the adverse action.
  • Creditors cannot justify non-compliance with the ECOA on the basis of the simple fact that the technology they use to assess credit applications is too complicated, too opaque in its decision-making, or too new. There is no exception for breach of law because a creditor uses technology that has not been properly designed, tested or understood. Following these guidelines, creditors must be able to understand the nuances of the technology that provides credit decisions, as they must be able to communicate required information about adverse actions to consumers.
  • Critical, “[a] the creditor’s lack of understanding of its own methods is therefore not a valid defense against liability for violation of the requirements of ECOA and Regulation B.”
  • The CFPB has encouraged whistleblowers to come forward to provide information about “black box models” that violate various federal consumer protection laws, including the ECOA.

In our estimation, there are a number of practical impacts that will flow from these guidelines, including:

  • Financial services entities that use AI, machine learning, or other algorithmic coding to help make credit decisions are now clearly warned that they must comply with ECOA’s adverse action requirements. This will require knowing the main reason(s) for any adverse action in order to communicate this information to consumers.
  • Financial services entities cannot use ignorance as an excuse. This is important as many vendors are reluctant to provide the trade secrets/coding underlying their technology, and therefore it is sometimes difficult for financial services entities to understand exactly why an adverse action has been taken. It is clear in light of Circular 2022-03 that vendor management will now become a bigger issue – and compliant financial services entities will need to work with vendors to ensure transparency to enable full disclosures. action against consumers.
  • In addition to the ECOA/Regulation B impacts associated with these guidelines, it is important to remember that discrimination is now considered a UDAAP under recent CFPB guidelines. Therefore, the information that financial services entities are now required to understand to comply with the adverse action requirements is also likely to be measured for discrimination analysis purposes.


This most recent CFPB circular sits at the crossroads of two important regulatory trends: increased attention to fair lending and multiple statements on the importance of vendor management. Since most lenders seeking to use algorithmic credit decision-making will use external providers with the required technical capabilities, it is essential that lenders are prepared to require – as a term of a provider services agreement – ​​that the service provider has the ability to ensure that the adverse action notification requirement of Regulation B can be satisfied. Additionally, lenders currently using these models should take the time to ensure that their current providers provide unobtrusive reasons for the adverse action. Lenders should remember that ultimately a vendor’s ability to do business with them depends on their ability to facilitate compliance with the universe of federal laws and regulations.

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