Compliance Blog

Jun 13, 2022
Categories: Fair Lending

Fair Lending Obligations and Decision-Making Algorithms

A few weeks ago, the Consumer Financial Protection Bureau (CFPB or bureau) issued Consumer Financial Protection Circular 2022-03 to remind creditors of their obligations under the Equal Credit Opportunity Act (ECOA) and Regulation B regarding adverse action notices when algorithms or automated models are used in the decision-making process.

Section 1002.9(b)(2) of Reg B require a creditor to provide a list of reasons for adverse action and requires the list to be “specific and indicate the principal reason(s) for the adverse action. Statements that the adverse action was based on the creditor's internal standards or policies or that the applicant, joint applicant, or similar party failed to achieve a qualifying score on the creditor's credit scoring system are insufficient.” The commentary to this section adds “the specific reasons disclosed under §§ 1002.9(a)(2) and (b)(2) must relate to and accurately describe the factors actually considered or scored by a creditor” and also notes, “if a creditor bases the denial or other adverse action on a credit scoring system, the reasons disclosed must relate only to those factors actually scored in the system. Moreover, no factor that was a principal reason for adverse action may be excluded from disclosure.”

In other words, creditors are required to identify exactly why adverse action is taken and convey that information to an applicant. It is not enough for a creditor to tell an applicant that the decision was based on a complex series of models and algorithms. The CFPB’s reiterates these opinions in its circular.

Additionally, in its press release, the bureau explains the circular was issued specifically to make these two points:

  • Federal consumer financial protection laws and adverse action requirements should be enforced regardless of the technology used by creditors. For example, ECOA does not permit creditors to use technology that prevents them from providing specific and accurate reasons for adverse actions. Creditors’ use of complex algorithms should not limit enforcement of ECOA or other federal consumer financial protection laws.
  • Creditors cannot justify noncompliance with ECOA based on the mere fact that 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. There is no exception for violating the law because a creditor is using technology that has not been adequately designed, tested, or understood.

Credit unions looking to increase their use of models and algorithms for loan decision-making want to ensure they understand the system being used and can continue to identify the reasons relied upon.

About the Author