Consumer collection agency Universal Fidelity has adopted SunGard’s AvantGard to help prioritise accounts for collections.
The solution uses statistical models to determine which accounts are most likely to pay and the expected value of the account, helping to increase recovery rates on credit card, medical, direct marketing, instalment loan and student loan debt.
AvantGard Predictive Metrics produces collection scores that leverage the statistical relationships found in the payment behaviours of consumers in a given debt portfolio. This has been shown to be more predictive than generic credit bureau data as it is unique to the specific debt to be collected.
The advanced models are run across the portfolio and, based on the output, collection agencies can determine which accounts have the highest propensity to pay, as well as know the forecasted value of the account, helping them to prioritise their collection activities and costs.
“Our goal is to quickly increase recovery rates for our customers while keeping costs down,” said Paul Farinacci, president and chief executive offer (CEO) of Universal Fidelity. “Prior to selecting SunGard’s AvantGard Predictive Metrics, we were prioritising collections based on an internal model that primarily took into account a debtor’s city location. Consequently, this model was not producing accurate scores and our collections costs were high.
“Statistical modelling is providing us with two outputs: accounts most likely to pay and the expected value of those accounts. We are using that information to help better allocate resources and target accounts more effectively in order to reduce our costs and deliver results to our clients.”
Dwayne Banasiak, vice president business development, Predictive Metrics solutions, at SunGard’s AvantGard business unit, added: “When a collection agency takes over collections for a corporation, utility, hospital or other entity, it must quickly determine which accounts to prioritise in order to increase liquidations.
“Time is the most valuable commodity and each day that goes by represents a decrease in the likelihood of recoveries. Calling the accounts that will have the highest likelihood of paying and knowing the payment value is vital to a cost-effective collection strategy.”
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