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Magazine
Model Risk Management in the Age of AI and a Changing Regulatory Environment
As AI adoption accelerates, model risk management is being forced to evolve beyond traditional validation techniques. Paul Trinh discusses how generative AI and machine learning introduce new risks related to data, explainability, and governance. Effective oversight now requires interdisciplinary collaboration across technology, data, and risk teams. The article highlights the importance of adaptability, stronger infrastructure, and clearly defined human oversight. As model ecosystems expand, institutions must rethink governance frameworks to ensure they remain effective in managing increasingly complex and dynamic systems.
Apr 24, 2026
Paul Trinh, SVP, Cadence Bank
Tags:
AI and Technology (including Fintech)
The views and opinions expressed in this content are those of the thought leader as an individual and are not attributed to CeFPro or any other organization
- AI is expanding model risk scope
- Traditional validation methods are insufficient
- Interdisciplinary collaboration is essential
- Human oversight remains critical
- Governance frameworks must
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