The Consumer Financial Protection Bureau (CFPB) is currently monitoring the innovation of Artificial Intelligence (AI), and more precisely the subset of Machine Learning (ML) as part of their mission of consumer protection. The CFPB was tasked by congress to ensure that markets for consumer financial products and services are operating transparently and efficiently.
Financial institutions have already started to instill the use of AI in a range of functions such as virtual assistants that take customer requests, detecting fraud as well as other illegal activity, and compliance monitoring tools.
AI has the potential to use traditional underwriting techniques that could enable lenders to evaluate the creditworthiness of millions of consumers who are considered to be “unscorable”. It is said that 1 in 10 adults in the United States are considered credit invisible due to not having a credit record at the nation wide bureaus. Around 19 million other consumers have too little information to be evaluated by the widely used credit monitoring model. This technology would involve models that would allow the lenders to evaluate more information about credit applicants which could lead to more efficient credit decisions and the potential to lower the cost of credit.
On the downside, AI could potentially amplify risks that include unlawful discrimination and privacy concerns. The bias in the model could also lead to inaccurate predictions. An important issue to note is how the AI models will address the adverse action notice requirements in the Equal Credit Opportunity Act (ECOA) and the Fair Credit Reporting Act (FCRA). The FCRA requires that the creditors provide the consumers with the main reasons for their credit denial and other adverse actions. Questions of concern will arise concerning how these institutions will comply with the requirements when they are basing their information on complex interrelationships driven by the AI.
Hopefully financial institutions ponder how to most effectively take advantage of the AI’s potential benefits. It would be a good use of time for them to explore ways to engage with consumers with features that would allow access to educational components and sharing information with consumers on how the underwriting decisions are made and what data/factors are used.
Promising technology could allow for a better overall experience that would benefit the consumers.
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