AI product management · Industry brief

The FTC announced a request for public comment on July 1 regarding a proposed policy statement on how Section 5 of the FTC Act applies to AI systems. The statement addresses deceptive practices, specifically cases where AI companies make representations about their systems' accuracy, objectivity, or reliability while altering outputs inconsistently with those claims. The FTC emphasized that AI products remain subject to traditional consumer protection standards and that companies should clearly disclose when AI systems prioritize objectives different from user expectations. The agency has already pursued enforcement actions against AI companies for allegedly deceptive claims about accuracy and capabilities. (Source: JDSupra, citing FTC)

The Federal Reserve, FDIC, and OCC issued SR 26-2 earlier this year, replacing prior guidance on model risk management and requiring financial institutions to understand and manage their AI and machine learning models, including their design, assumptions, data, methods, limitations, performance, and monitoring. The FFIEC IT Examination Handbook warns that AI lacking transparency or explainability increases compliance and operational risk, while Regulation B requires creditors to provide specific reasons for adverse credit actions when AI is involved. The Financial Action Task Force, GAO, and NIST have similarly emphasized explainability and transparency as key expectations for AI used in banking, AML, and financial crime solutions, with regulators making clear that institutions must be able to explain how AI reaches decisions or the black-box defense is insufficient.