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CFPB: Borrowers Entitled to Explanation for Credit Denial, Even if Credit Decisions are Based on Complex Algorithms

CFPB: Borrowers Entitled to Explanation for Credit Denial, Even if Credit Decisions are Based on Complex Algorithms

Wed Jun 01 2022

By Ken Chase

<p>The Consumer Financial Protection Bureau (CFPB) <a href="https://www.consumerfinance.gov/about-us/newsroom/cfpb-acts-to-protect-the-public-from-black-box-credit-models-using-complex-algorithms/">announced on May 26</a> that lenders cannot avoid the requirement to provide borrowers with detailed explanations for credit application denials, even if those creditors are utilizing models that employ complex algorithms. In its new circular, the bureau confirmed that the Equal Credit Opportunity Act’s requirements still apply in those cases, even if the lending companies are using decision-making models that they may not fully understand.</p> <p>According to the CFPB circular, “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. There is no exception for violating the law because a creditor is using technology that has not been adequately designed, tested, or understood.”</p> <p>The bureau acknowledged that creditors’ use of algorithm-based models, sometimes referred to as “black-box” models may mean that the lender is not aware of all the reasons why the algorithms deny an application. The new ruling reinforces that the use of that technology cannot be lawful if it in any way prevents lenders from providing the explanations required by federal law.</p> <p>CFPB Director Rohit Chopra reminded consumers and lenders alike that, “Companies are not absolved of their legal responsibilities when they let a black-box model make lending decisions. The law gives every applicant the right to a specific explanation if their application for credit was denied, and that right is not diminished simply because a company uses a complex algorithm that it doesn’t understand.”</p>