July 10, 2020
The Consumer Financial Protection Bureau ("CFPB") has published guidance on July 7, 2020 which highlights the potential use of Artificial Intelligence (“AI”) in the delivery of financial services—particularly in credit underwriting models. In addition to providing an overview of the ways in which AI is being used by financial institutions, the publication addresses: (1) industry uncertainty about how AI fits into the existing regulatory framework, especially for credit underwriting; and (2) the tools that the CFPB has been using to promote innovation, facilitate compliance, and reduce regulatory uncertainty.
As the publication notes, financial institutions are starting to deploy AI across a range of functions, including as virtual assistants that can fulfill customer requests, in models to detect fraud or other potential illegal activity, or as compliance monitoring tools. Credit underwriting is one specific area in which AI may have a profound impact. Credit underwriting models that are built upon AI have the potential to expand credit access by permitting lenders to evaluate creditworthiness of some of the millions of consumers who are “unscorable” using traditional underwriting systems. These new AI infused models and technologies will typically allow lenders to evaluate more information about credit applicants, which go beyond the information that the lenders would have been able to assess using traditional consumer reporting agency reports. In turn, consideration of such information may lead to more efficient credit decisions and potentially lower the cost of credit. On the other hand, however, AI may create or amplify risks of unlawful discrimination, lack of transparency, and privacy concerns. Further, bias may be found in the source data or model construction, which can lead to inaccurate predictions. Thus, in considering the implementation of AI, ensuring that the innovation is consistent with consumer protections will be critical.
Despite AI’s potential benefits, industry uncertainty about how AI fits into the existing regulatory compliance framework may be slowing its adoption, especially for credit underwriting. One vital issue is how complex AI models address the adverse action notice requirements in the Equal Credit Opportunity Act (“ECOA”) and the Fair Credit Reporting Act (“FCRA”). ECOA and FCRA require creditors to provide consumers with the main reasons for denial of credit or other adverse action. While these notice provisions serve important anti-discrimination, accuracy, and educational purposes, industry stakeholders may have questions about how institutions can comply with these requirements if the reasons driving an AI model decision are based on complex interrelationships. To alleviate this concern, the publication provides specific examples of the ways in which creditors can comply with ECOA and FCRA when issuing adverse action notices based on AI models.
In addition to concluding that the “existing regulatory framework has built-in flexibility that can be compatible with AI algorithms,” the publication goes on to outline the various tools that the Bureau uses to promote innovation, facilitate compliance, and reduce regulatory uncertainty, including:
In particular, the first two policies (TDP & CAS) provide for a legal safe harbor that could reduce regulatory uncertainty in the area of AI and adverse action notices. The third policy discusses the ways in which stakeholders can obtain No-Action Letters from the CFPB, which can effectively provide increased regulatory certainty through a statement that the CFPB will not bring a supervisory or enforcement action against a company for providing a product or service under certain facts and circumstances.
This latest publication is a good sign for industry participants as it reaffirms previous guidance published by the CFPB which shows that the Bureau is committed to helping spur innovation consistent with consumer protections. By working together, industry stakeholders and the Bureau may be able to facilitate the use of this promising technology to expand access to credit and benefit consumers.
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