Case Study: Leading Retail Bank improves loss forecasting with Mu Sigma

Improved loss forecasting for a leading retail bank

Mu Sigma worked with a leading retail bank, one of the largest regional banks in the US with more than 15 lending portfolios. The bank needed to stress test its consumer, commercial, wealth, and small business portfolios within a three-month Fed deadline, but its existing loss reserving process did not account for macroeconomic changes and could not support stress scenarios.

Mu Sigma implemented a loss forecasting framework that replicated the bank’s current process while adding macroeconomic variables, recovery modeling, and portfolio growth components. Mu Sigma also built a tool to model losses across portfolios under different Fed stress scenarios. The solution improved loss reserve forecast accuracy by more than 10%, reduced reserves by more than 5%, and helped the bank successfully pass the Fed-mandated stress tests.