Challenge:
One of PAG’s large clients in the United States purchases credit card portfolios from other US-based financial institutions. Our client was looking for highly effective forecasting methods to determine loss rates, growth curves, and other critical metrics to increase its profit margins through a more accurate determination of portfolio profitability, thus impacting its offered purchase price.
PAG Solution:
We re-engineered and overhauled its forecasting process, designing a data template and schema for standard portfolio purchases that would provide more detailed information on what drives credit card profitability.
We then used our GOBLIN platform to ensure data from the prospective portfolio was received quickly and in a ready-to-analyze format. Using our years of experience in the card industry and our proprietary forecasting models, we utilized different forecasting techniques (e.g., exponential smoothing, complex weighted averages) to increase the speed and accuracy of our client’s portfolio evaluation process. This allowed the client to focus on portfolios with more upside and avoid ones with limited profit potential.
Client Benefits:
- PAG successfully increased the speed of the valuation process from approximately three weeks to five business days under the current redesigned process. These changes enabled our client to evaluate more portfolios and turn around bids much faster, getting a leg up on other interested acquirers.
- Our client has access to more streamlined data through GOBLIN and can run its own analysis and compare using our models.
- Our forecasting models had reduced variability in the observed loss curves by over 30%, with an average variance of only +- 2%.
- Our client has seen portfolio profits increase by an average of nearly 17% within a year of acquisition.
