Model risk is a key area of focus for financial institutions as there are constantly ongoing developments which need to be incorporated into frameworks. With the growing use of AI and ML, grew the complexity of models within financial institutions and enhancements need to be made in the documentation and reporting of models to reduce any errors and ensure thorough governance. Additionally, there are concerns around data management for these models due to the current turbulent environment.

The GFMI 24th Edition Model Risk conference will enable attendees to delve deep into the integration and governance of AI and machine learning models, uncovering both the challenges and groundbreaking opportunities they present, as well as traditional models. Attendees will be able to explore robust solutions for efficient model documentation and reporting and gain invaluable insights on navigating the evolving regulatory environments.

Attending This Premier marcus evans Conference Will Enable You to:

• Provide an update on the regulatory guidance within MRM.

• Master third party model management, validation and audit.

• Breaking new ground: The validation challenges of NLP and LLM in finance.

• Build solid governance uniting diverse expertise across the MRM function.

• Unravel the model definition puzzle from an insurance perspective.

• Climate risk and ESG model validation: emerging regulatory trends.

Best Practices and Case Studies from:

• David Palmer, Senior Supervisory Analyst, Federal Reserve Board

• Shawn Tumanov, Director, Data & Analytics (AI) Governance, BMO Financial Group

• Aruna Joshi, Head of Model Risk Management, Visa

• Seyhun Hepdogan, Director of Analytics, Fifth Third Bank

• Michael Minnes, Head of Model Governance, MassMutual

• Akshaya Nambiar, Assistant Vice President, ESG & Climate, Model Risk Management, Deutsche Bank

For more information and registration discounts please contact: Ria Kiayia, Senior Digital Media and PR Marketing Executive at riak@global-fmi.com or visit: https://tinyurl.com/mr3xmfau