Credit union uses analytics to optimize credit card rates,
increases projected card revenue by nearly $300K
Background
A Washington based credit union with $3 billion in assets and 185,000 members, was interested in determining if there were potential benefits of increasing credit card interest rates.
Solution
- CU Rise conducted a detailed assessment of their current credit card portfolio. The data-driven analytics helped to design potential new credit card scenarios.
- A new APR structure was recommended based on FICO scores. Rates would increase for members with low FICO scores, and lowered for members with high FICO scores.
- CU Rise created high and low parameters for the rates that would maintain retention of high-risk members (low FICO) and profitability of low-risk members (high FICO).
- Different profitability and cost-benefit scenarios were built to help STCU fully understand the impact of the rate changes.
Approach
Results
- STCU pinpointed the most successful scenario, which segmented new and existing cardholders into high, medium, and low risk categories and optimized rates accordingly.
- The revenue increase from this scenario is projected to be nearly $300K.