In a new policy statement, the CFPB made clear that lenders must specifically identify the reasons for adverse credit decisions, including in cases where the creditor utilized artificial intelligence or complex credit models to determine its credit decision.
In a Circular on the "Adverse action notification requirements and the proper use of the CFPB’s sample forms provided in Regulation B" of the Equal Credit Opportunity Act, the CFPB underscored that if the "reasons listed on the forms are not the factors actually used, a creditor will not satisfy the notice requirement by simply checking the closest identifiable factors listed." The CFPB stated that consumers may not anticipate types of data that may be used when a creditor utilizes complex algorithms and that in these cases "[s]pecificity is particularly important." The CFPB emphasized that the use of complex algorithms does not allow for creditors to evade their requirements under Regulation B and that adverse notices provide consumers with a "key educational tool" to either (i) improve their credit status or (ii) identify mistakes made by the creditor.
CFPB Director Rohit Chopra commented that artificial intelligence is "expanding the data used for lending decisions, and also growing the list of potential reasons for why credit is denied." He stated that "[c]reditors must be able to specifically explain their reasons for denial. . . . [t]here is no special exemption for artificial intelligence." (See also CFPB press release.)
It is well known that AI works in ways that are not fully understood. Compliance with the CFPB circular may not really be possible as the AI "decision" may be predicated on the interaction of a variety of factors that are not apparent to the potential lender. Perhaps this is an issue as to which the CFPB should request input, rather than establishing requirements that may not be achievable based on the technology.