Model Risk Management for Insurance
The practice of model risk management in insurance companies continues to evolve. Driven by regulatory changes and increased reliance on quantitative models, having a strong model risk management program is critical. By understanding and controlling model risk, insurance companies can reduce the potential for unforeseen losses across the organization. In this session, attendees will see how establishing strong model risk management, including robust effective challenge, resilient controls, and transparent assumptions and limitations, enables better decision-making across the organization. Attendees will also learn industry best practices around model validation and key concepts to improve their model risk program.
Key Learning Points:
- Recognize the benefits and motivations for implementing a robust model risk management framework
- Evaluate the critical steps to setting up a model risk management program
- Execute effective challenges (validation and audit) over various model types in insurance
- Analyze common effective challenge gaps to enhance the First, Second and Third Lines of Defense for model risk
Todd is a Managing Director in the Data Management and Advanced Analytics practice. As a leader in the Model Risk practice, Todd focuses on risk modeling and model validation for credit, market, operational and conduct/compliance risk. Recently, Todd has supported CECL and stress testing model development, validation and internal audit at more than 15 major banks. He has developed model governance processes and risk quantification processes for the world's largest financial institutions and is a subject matter expert for internal audit of the model risk management function.
Gregg is a Senior Manager in the Data Management and Advanced Analytics Practice, where he has conducted model risk validation projects for multiple clients within financial services industry. Greggy has over eight years of experience in data analysis and model risk management, focusing on model validation and audit, stress testing, and anti-money laundering. He has a Bachelor of Commerce majoring in Actuarial Studies from Macquarie University, and is a Fellow of the Institute of Actuaries Australia.
Deepali is a Manager in the Data Management and Advanced Analytics Practice, where she has conducted model risk and validation projects for multiple clients within the insurance and financial services industry. Deepali has over six years of experience in data analytics and model risk management, focusing on model development, validation and audit, actuarial validation, and anti-money laundering. She has a Master's degree in Actuarial Science from Columbia University and is in the process of becoming a fellow from the Society of Actuaries.
1 CPE Credit will be awarded for those viewing it live!