The GFMI Credit Risk Modeling, Management and Validation, Canada conference offers insight for credit risk professionals facing the challenges of a rapidly changing macroeconomic environment. Sessions will cover strategies to enhance credit risk model accuracy and resilience amid inflation, interest rate fluctuations, and climate-related risks. Attendees will learn best practices for developing and validating ECL, PD, and LGD models and explore the advantages of adopting alternative and behavioral data to strengthen forward-looking credit risk projections. Furthermore, delegates will explore how AI and ML can be responsibly integrated into credit risk frameworks to drive innovation, improve efficiency, and maintain strict regulatory compliance and model governance standards.

Attending This Premier marcus evans Conference Will Enable You to: 

  • Enhance predictive accuracy in credit risk models through advanced alternative data strategies
  • Discuss best practices to ensure safe, ethical, and fair adoption of AI models in credit risk frameworks
  • Address commercial credit risk vulnerabilities in a shifting macroeconomic landscape
  • Assess the impact of macroeconomic volatility on credit model assumptions and outputs
  • Enhance credit risk model performance through advanced stress testing practices to ensure accurate assessment
  • Apply machine learning and LLMs to address emerging credit risks and use case complexity

Best Practices and Case Studies from: 

  • Theresa Mundell, Managing Director, Credit Models and Data Science, ATB Financial
  • Elena Sobol, Director, market and counterparty credit risk, RBC
  • Anna Nauruzov, Director Credit Risk Management, Home Trust Company
  • Noel Lewis, Assistant Vice President, Credit Risk, VersaBank
  • Arsen Vaganyan, Director, Financial Risk and Modeling, First West Credit Union
  • Ardalan Shojaei, Chief Credit & Risk Officer, Fig Financial

For more information please contact Ria Kiayia, Digital Media and PR Marketing Manager at riak@marcusevanscy.com or visit: https://bit.ly/4mOXbiQ

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