First Financial Investment Fund is leveraging the predictive power of customer payment data to determine the expected value of medical portfolios they are identifying for purchase. Once the portfolios are purchased, the company will then use the statistical modeling to help determine the accounts that are most likely to pay and will prioritize collection segmentations and treatments accordingly to help improve operational efficiencies and recovery as well as reduce expenses. The models do not require the use of credit bureau data which helps organizations to comply with specific regulations and to keep costs at a minimum.

Matthew Maloney, chief investment officer of the First Financial Group of Companies, said, "Accurate bid determination is an essential element in running a profitable firm. We selected SunGard's AvantGard Predictive Metrics to help us value medical debt portfolios and benchmark against our proprietary cash-flow model predictions. Once we purchase a medical receivables portfolio, we will use predictive models to evaluate payment behavior in order to determine the propensity of accounts in the portfolios to pay. By utilizing a custom model application that blends SunGard data with our own proprietary models, we will be able to effectively prioritize our segmentation strategies and collections treatments to increase our liquidations."

"Overbidding on a medical debt portfolio that has little potential for recovery can result in significant losses and drain valuable resources," said Dwayne Banasiak, vice president business development, Predictive Metrics solutions, at SunGard's AvantGard business unit. "SunGard provides companies like First Financial Asset Management and First Financial Investment Fund with this information up-front to help improve bid accuracy and collection strategies for increased profitability."