CFPB Issues Guidance on Credit Denials Based on Predictive Technology

CFPB Issues Guidance on Credit Denials Based on Predictive Technology

Written By: Joel Palmer, Op-Ed Writer

The Consumer Financial Protection Bureau (CFPB) has issued legal guidance to lenders regarding the use of artificial intelligence (AI).

The guidance clarifies that lenders, including mortgage lenders, must provide specific reasons for taking adverse actions against potential borrowers and not rely solely on the results of AI.

“Technology marketed as artificial intelligence is expanding the data used for lending decisions, and also growing the list of potential reasons for why credit is denied,” said CFPB Director Rohit Chopra. “Creditors must be able to specifically explain their reasons for denial. There is no special exemption for artificial intelligence.”

The guidance is in response to the potential of creditors relying too much on the checklist of reasons provided in CFPB sample forms when using artificial intelligence. The bureau addressed the concern that lenders may rely too heavily on the checklist itself when giving an adverse action notice, even when those sample reasons do not accurately or specifically identify the reasons for the adverse action.

CFPB noted that using predictive decision-making technology, such as AI, in underwriting often results in using data harvested from consumer surveillance. As a result, a consumer may be denied credit for reasons that they believe shouldn’t be considered relevant to their finances.

The other concern is that an underwriter using AI may provide a vague reason to explain an adverse action because the decision was based solely on the technology and not on the underwriter’s individual judgement.

For example, a creditor can’t limit their explanation to a general reason such as “purchasing history” if they decide to lower the limit on a consumer’s credit line based on behavioral spending data. The explanation needs to provide more details about the specific negative behaviors that led to the reduction.

CFPB also warned lenders about selecting the “closest factors” from its checklist of sample reasons when issuing an adverse action. This is also a concern if underwriters are using AI and are hoping to comply with regulations by checking a box that’s close enough.

“Creditors must disclose the specific reasons, even if consumers may be surprised, upset, or angered to learn their credit applications were being graded on data that may not intuitively relate to their finances,” CFPB said.

In addition to this latest bulletin and last year’s circular, the CFPB has issued an advisory opinion that consumer financial protection law requires lenders to provide adverse action notices to borrowers when changes are made to their existing credit.

CFPB reminds lenders that the Equal Credit Opportunity Act (ECOA) and Regulation B require them to provide an applicant with a statement of specific reason(s) for an adverse action. In addition, these reasons must “relate to and accurately describe the factors actually considered or scored by a creditor.”

The bureau noted that it’s important to use specific reasons when explaining adverse actions, such as loan denials, because it helps improve a consumer’s chances to qualify for credit in the future. It is also a way to protect consumers from illegal discrimination, a major part of the ECOA and Regulation B.


About the Author

As an NAMU® Opinion Editorial Contributor, Joel Palmer is a freelance writer who spent 10 years as a business and financial reporter and another 10 years in marketing for the insurance and financial services industries. He regularly writes about the mortgage industry, as well as residential and commercial real estate, investments, and retirement income planning. He has also ghostwritten books on starting a business, marketing, and retirement income planning.


Opinion-Editorial (Op-Ed) Disclaimer For NAMU® Library Articles: The views and opinions expressed in the NAMU® Library articles are those of the authors and do not necessarily reflect any official NAMU® policy or position. Examples of analysis performed within this article are only examples. They should not be utilized in real-world application as they are based only on very limited and dated open source information. Assumptions made within the analysis are not reflective of the position of NAMU®. Nothing contained in this articles should be considered legal advice.