Session 1 : Model Risk and Common Pitfalls – Lessons from Model Risk Management
Presentation Type
Oral
Student
No
Track
Finance/Insurance Application
Abstract
This presentation will explore the intricacies of modeling best practices from the perspective of a model risk manager with experience in managing and mitigating model risk. The session will provide an overview of the critical considerations necessary for robust model development and deployment, focusing on the importance of rigorous development standards and monitoring. Attendees will learn about key areas where model development can face challenges, including the identification and assessment of potential risks throughout the model lifecycle.
The presentation will cover practical strategies for improving model development, such as incorporating thorough exploratory data analysis, leveraging model development best practices, and executing purposeful implementation and monitoring frameworks. Synthetic examples that mimic real-word scenarios will be shared to illustrate common pitfalls and successful mitigation approaches, providing attendees with actionable insights to improve their own modeling practices. By the end of the session, participants will have a deeper understanding of the complexities of model risk and the best practices that can help prevent adverse outcomes. This presentation is intended for students or professionals involved in model development, validation, and risk management, offering valuable guidance to navigate the challenges of an increasingly data-driven environment.
Start Date
2-7-2025 8:50 AM
End Date
2-7-2025 9:50 AM
Session 1 : Model Risk and Common Pitfalls – Lessons from Model Risk Management
Jacks' Place (Room 050)
This presentation will explore the intricacies of modeling best practices from the perspective of a model risk manager with experience in managing and mitigating model risk. The session will provide an overview of the critical considerations necessary for robust model development and deployment, focusing on the importance of rigorous development standards and monitoring. Attendees will learn about key areas where model development can face challenges, including the identification and assessment of potential risks throughout the model lifecycle.
The presentation will cover practical strategies for improving model development, such as incorporating thorough exploratory data analysis, leveraging model development best practices, and executing purposeful implementation and monitoring frameworks. Synthetic examples that mimic real-word scenarios will be shared to illustrate common pitfalls and successful mitigation approaches, providing attendees with actionable insights to improve their own modeling practices. By the end of the session, participants will have a deeper understanding of the complexities of model risk and the best practices that can help prevent adverse outcomes. This presentation is intended for students or professionals involved in model development, validation, and risk management, offering valuable guidance to navigate the challenges of an increasingly data-driven environment.