The competitive landscapes of banking, finance and leasing face tight capital markets, delinquencies and write-offs, and severe resource constraints. Through advanced statistical modeling, FIS^™’ Predictive Metrics solution can help by accurately predicting the likelihood that a customer will become severely delinquent, go to loss, or file for bankruptcy.

• More accurately predict collection risk with statistical modeling and an industry-specific database.
• Dramatically reduce delinquencies, losses and operational costs.
• Improve overall cash flow and days sales outstanding (DSO).
• Leverage internal historical data with or without the coupling of external data for collections prioritization, for approval of additional leases or loans, or for credit line management.
• Improve productivity of collections efforts and reduce operating costs.
• Use statistical modeling to proactively address potential bad debt.

For hospitals, healthcare billing and collections, physician groups, labs, clinics and other providers, bad debt is growing due to climbing healthcare costs and regulatory and economic factors. The FIS^™ Predictive Metrics statistical modeling solution helps mitigate these challenges, improve collections, and optimize efficiencies and costs with statistical modeling that is specific to collecting medical debt.

• Quickly and accurately identify which patients are likely to pay and which medical debt should be outsourced to a collection agency, passed back or sold off.
• Reduce costs by prioritizing medical debt collection activities.
• Comply with regulations such as HIPAA and Pinto’s ruling with statistical modeling that does not rely on bureau data.
• More appropriately allocate resources, reduce costs and increase profits.

As delinquencies and losses continue, the utilities and telecommunications industries face increasing pressure to make debt collection a priority. The FIS^™ Predictive Metrics solution predicts inherent risk using payment behavior models specific to residential, commercial and industrial accounts for electric, gas and water utilities, as well as telecommunications services.

• Lower average days to pay (ADP) and write-offs, reduce utility and telecommunication debt collection costs, and better understand the cash at risk.
• Better allocate debt collection resources and manage collection costs.
• Identify the risk associated with each customer to determine the optimal collection strategy or deposits.
• Unlock the predictive power of your own customer data for debt collection.
• Reduce data acquisition costs.