SR 26-2 replaces the old checklist-based approach with materiality-based tiering, changing how banks validate models. It also names generative and agentic AI as out of scope for now, with an agency request for information reportedly on the way. That leaves model risk management leaders with the real work: deciding how much governance to build before the guidance catches up.
Hear from Nick Goble of Domino Data Lab for an open conversation with Jason DiPalma of KeyBank, Naresh Raheja, Former OCC Senior Risk Specialist and Examiner, and Lee Medoff, Former Head of Model and AI Governance at Fifth Third Bank on how model risk leaders are building governance and handling the generative and agentic AI gap.
The conversation covers where agentic AI governance stands today and where supervisors and institutions are likely to take it next. You hear about:
SVP, Senior Director Model Risk Governance
Jason DiPalma is Senior Director of Model Risk Governance at KeyBank, where he leads enterprise model risk governance practices. With 27 years of experience within the banking and financial services industry, Jason brings a multidimensional perspective shaped by leadership roles in accounting and finance, internal audit, and model risk management across both regional and global financial institutions.
Former OCC Senior Risk Specialist & Examiner
Naresh Raheja is an AI risk and MRM leader who advises firms on balancing AI innovation with prudent risk management across machine learning, Gen AI, and agentic AI models and systems. He is a former OCC Senior Risk Specialist and Examiner. At the OCC, he supervised large banks' model risk management, AI governance, and climate-related credit and operational risk practices. In that role, he also collaborated with the Federal Reserve, Financial Stability Oversight Council (FSOC), FDIC, and international financial regulators on several initiatives.
Former Head of Model and AI Governance
Lee Medoff is an AI and Analytics leader with 20 years of experience developing and implementing data-driven, advanced analytical solutions across the financial services industry. He began his career as a desk quant at JPMorgan Chase before joining the Bank Supervision Group at the Federal Reserve Bank of New York. He has significant additional experience in financial services risk management consulting, beginning with Moody’s Analytics, where he managed analytics delivery teams in both New York and India, and then as a senior manager within EY's Quantitative Advisory Services Group. Until recently, he was the Head of Model and AI Governance at Fifth Third Bank.
Solution Architecture for Financial Services & Insurance
Nick Goble, Ph.D. leads Solution Architecture for Financial Services & Insurance at Domino Data Lab, bringing more than ten years of experience across quantitative finance, derivatives modeling, and fintech innovation. At Venerable, Nicholas managed Quantitative Research and Development, where he established quant research capabilities from the ground up and guided teams in building sophisticated trading platforms and pricing engines. Before that, he was a Senior Quantitative Researcher at Chatham Financial, focusing on valuation methodologies and bringing machine learning models into live trading environments. Nicholas holds a Ph.D. in Physics from Case Western Reserve University.