The Role of AI in Financial Services: From Fraud Detection to Underwriting

Frequently Asked Questions

01.How is AI used in financial services?

Two of its main uses are scoring payments and accounts for fraud, and scoring applicants for credit or insurance risk. Fraud models flag and rank suspicious activity for an analyst to review; underwriting models estimate the chance of default or loss and help set the price. The two share data but answer to different rules, so they need separate model files.

02.Is AI credit scoring high-risk under the EU AI Act?

Presumptively, yes. Annex III of the EU AI Act lists AI systems that evaluate the creditworthiness of natural persons or establish their credit score, and expressly excludes systems used to detect financial fraud. Because credit scoring usually profiles applicants, the Article 6(3) exceptions are unlikely to help. After the Digital Omnibus amendments, the high-risk obligations reach these systems from 2 December 2027.

03.Do US lenders have to explain AI credit decisions?

Yes. Regulation B requires creditors to give, or make available on request, the specific principal reasons for adverse action, and saying the applicant failed to reach a qualifying score is insufficient. The CFPB withdrew its circular on complex algorithms in May 2025, but the regulation still requires reasons that describe the factors the creditor considered or scored, whatever model produced the decision.