📅 Wednesday, March 13, 2025
🕙 10:00 AM – 11:30 AM ET
📍 Virtual (Zoom)
Generative AI (GenAI) is transforming financial services, offering new opportunities for efficiency, compliance, and customer engagement. But with these innovations come new risks. How can financial institutions, technology providers, and regulators ensure that existing risk management frameworks are adaptive and fit-for-purpose in the GenAI era
Join the Alliance for Innovative Regulation (AIR) and Google Cloud for a 90-minute webinar exploring the latest insights and regulatory considerations for GenAI models.
In this virtual event, we will — amongst broader conversation — discuss a recently released white paper written in partnership by Google Cloud and AIR that seeks to address these questions. The program aims to foster thought and dialogue among regulators, the financial services industry, risk model vendors, and stakeholders interested in the performance, outputs, and compliance of GenAI models used in financial services. Join us as we discuss the report and related policy and regulatory considerations with key industry participants and financial regulation experts.
Brandon Milhorn, President & CEO, Conference of State Bank Supervisors (CSBS)
Daniel Gorfine, CEO, Gattaca Horizons
Chris Hopfensperger, Senior Manager, Google Cloud
David Stone, Director Financial Services, Office of the CISO, Google Cloud
Anna Gressel, Partner, Paul, Weiss, Rifkind, Wharton & Garrison LLP
Jo Ann Barefoot, CEO & Co-founder, AIR
WHITE PAPER • Adapting Model Risk Management for Financial Institutions in the Generative AI Era
AIR and Google Cloud jointly released this paper exploring how model risk management (MRM) frameworks and established governance practices can be applied to manage risks for financial institutions in gen AI contexts.
WHITE PAPER • AIR and Google Release Paper on Applying Model Risk Management Guidance to AI
The paper argues that MRM guidance, given its broad, principles-based approach, continues to provide an appropriate framework for assessing financial institutions’ management of model risk, even for Risk AI/ML models.
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