Credit Loss Forecasting
The Challenge
- A leading financial institution wanted to comply with the CECL requirements and adopt a forward-looking and lifetime-based approach to forecast credit losses for their private label credit cards.
- They needed a reliable and effective loss forecasting model that could capture the impact of macroeconomic variables on credit behavior and estimate the lifetime of the credit cards.
The Solution
- We designed and developed two innovative loss forecasting models (Roll Rate and Vintage models) that incorporated both the estimated lifetime of the credit cards and the macroeconomic variables that affect credit behavior.
- We tested and validated both models to ensure that they were responsive to changing economic conditions and aligned with the CECL standards.
The Results
- Our loss forecasting models enabled the financial institution to improve their credit loss forecasting accuracy by 17%, compared to their previous models.
- This resulted in:
- Better risk management, as they could identify and mitigate the drivers of credit losses and monitor the expected credit performance under different scenarios.
- Improved capital planning, as they could allocate sufficient capital reserves based on their projected credit losses and optimize their profitability.
- Enhanced regulatory compliance, as they could meet the CECL requirements and report their credit losses in a transparent and consistent manner.