The new law S.B. 24-205 regulates AI system development, particularly for high-risk applications like mortgages. Rulemaking is in progress, with potential to influence other states. As AI evolves, compliance processes must also adapt. Lenders should automate compliance from the start of AI integration and form an AI governance committee that interacts frequently with the board. Vendor due diligence is critical for companies using third-party AI tools. Compliance and legal risks must be integrated into ROI models to ensure alignment with business goals.
Both speakers advised to incorporate legal and compliance risk into return on investment (ROI) models. It's not just about the cheapest model per token, Lee said. Does that model help you manage compliance and regulatory exposure?
Lee recommended establishing an AI governance committee with direct access to the board and the ability to meet more frequently than every quarter.
Lenders, servicers and capital markets teams should consider automating compliance tools from the outset of AI adoption, rather than treating it as an afterthought.
Brown said that vendor due diligence is another priority. Companies that build their own AI may control the rollout pace more effectively, but those buying third-party tools must scrutinize contracts, avoid overly long terms and know your developer to anticipate product changes.
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