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    CFPB Circular Sets Out Actions for Creditors Using Complex Algorithms

    May 26, 2022

    The Consumer Financial Protection Bureau (CFPB) launched a new Office of Competition and Innovation, published a circular on adverse action notification requirements for credit decisions based on complex algorithms, and issued an interpretive rule to clarify the scope of states’ ability to enforce federal consumer financial protection laws. The new Office of Competition and Innovation will support a broader initiative by CFPB to analyze obstacles to open markets, better understand how big players are squeezing out smaller players, host incubation events, identify ways to address commonplace obstacles to data-sharing, and, in general, make it easier for people to switch financial providers.

    The CFPB Circular sets out adverse action notification requirements in connection with credit decisions based on complex algorithms under the Equal Credit Opportunity Act (ECOA). Law-abiding financial companies have long used advanced computational methods as part of their credit decision-making processes and they have been able to provide the rationales for their credit decisions. However, some creditors may make credit decisions based on the outputs from complex algorithms, sometimes called “black-box” models. The reasoning behind some of these models’ outputs may be unknown to the model’s users, including the model’s developers. With such models, adverse action notices that meet ECOA’s requirements may not be possible. ECOA requires a creditor to provide a notice when it takes an adverse action against an applicant, to explain the specific and accurate reasons for that adverse action. The Circular makes it clear that federal consumer financial protection laws and adverse action requirements should be enforced regardless of the technology used by creditors. It stipulates that companies relying on complex algorithms must provide specific and accurate explanations for denying applications. Creditors cannot justify non-compliance with ECOA just because the technology they use to evaluate credit applications is too complicated, too opaque in its decision-making, or too new. Creditors who use complex algorithms—including artificial intelligence or machine learning technologies—to engage in credit decisions must still provide a notice that discloses the specific, principal reasons for taking adverse actions.

     

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    Keywords: Americas, US, Banking, Credit Risk, Regtech, Artificial Intelligence, Machine Learning, ECOA, Lending, Basel, CFPB

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