The GFMI 4th Edition Credit Risk Modeling conference taking place in New York, on February 5-7, 2025 will offer case studies, sessions and panel discussions to understand how credit risk modelers have navigated and overcome the changing credit cycle. One of the key issues addressed will be the scarcity of data to input into credit risk modelling. It will address how cutting-edge AI is being used to leverage data within credit risk modelling, and how credit risk modelers are planning to use AI, ML and Large Language Models. Another key theme will show case studies of effective ways to implement Credit Risk Modelling strategies against changes in Commercial Real Estate Lending.
Attending This Premier marcus evans Conference Will Enable You to:
- Evaluate the evolving regulatory landscape, How to Implement compliance within credit risk modelling
- Implement relevant macro-economic data to enhance credit risk modelling in 2025
- Evaluate how credit risk modelling strategies need to keep pace with changes in commercial real estate lending
- Adjust credit risk models to include interest rates to ensure dynamic credit risk models can adjust to latest economic environments
- Use AI and ML to enhance relevant and effective data within data acquisition
- Gain an update from regulators to ensure compliance in the current regulatory environment
Best Practices and Case Studies from:
- Mircea Pigli, Senior Vice President, Director, Credit Risk and Capital Management Modeling, Fifth Third Bank
- Daniel Eklove, Senior (Managing) Director, Credit Models & Methodology, Royal Bank of Canada
- Eugenia Walton, Director, Internal Audit, Model Risk, BNY
- Varun Nakra, Vice President at Credit Risk Modelling, Deutsche Bank
- Sean Keenan, Executive Director Stress Testing & Portfolio Analytics, Sumitomo Mitsui Banking Corporation
- Neil Desai, Director of Examinations, Federal Reserve Bank of Atlanta
For more information please contact: Ria Kiayia, Digital Media and PR Marketing Manager at riak@marcusevanscy.com or visit: https://shorturl.at/DiHDR
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