CECL Modeling Methodologies Q3 2017 Event
Change is good. The impact of Current Expected Credit Loss (CECL) requirements runs wide and deep and you’re going to need to have a big picture view of how your data, models and methodologies must be built to ensure the right information is being captured and reported.
Join Todd and Ben as they walk you through the details of how to use historical data, current conditions, reasonable forecasts and assumptions to estimate expected losses.
Key Learning Points:
- CECL Requirements and Applicability
- Challenges for CECL methodology and parameters development
- Can I leverage CCAR or Basel II models for CECL?
- CECL Modeling Methodology Comparison such as PD/LGD vs Vintage Analysis
- How to validate and audit CECL models and process
- Use cases and solutions from current client work
Todd Pleune is a Managing Director in the Model Risk practice of Protiviti’s Data Management and Advanced Analytics Solution. Todd focuses on risk modeling and model validation for Market, Operational, Credit, and Conduct Risk.
Benjamin Shiu has 18 years’ experience in developing, validating and reviewing credit risk stress testing and ALLL models. Before joining Protiviti, he worked for several top U.S. banks and focused on developing internal credit risk models, retail credit portfolio management strategies and wholesale credit model development.