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Collections Firm Deploys SunGard Predictive Metrics Solution
Call Center Software Featured Articles
November 08, 2012


Collections Firm Deploys SunGard Predictive Metrics Solution


By Tracey E. Schelmetic
TMCnet Contributor

Today, collections is big business, as Americans rack up (and are slow to pay down) more debt. But today’s collection solutions are different then solutions 10 or 20 years ago, thanks to advanced analytics capabilities. AR solutions provider SunGard is announcing this week that consumer collections agency Universal Fidelity LP has chosen SunGard’s AvantGard Predictive Metrics to help prioritize 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, installment loan and student loan debt.

According to SunGard, the AvantGard Predictive Metrics produces collection scores that leverage the statistical relationships found in the payment behaviors of the 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. With advanced models running 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 prioritize their collection activities and costs, said the company.

“Our goal is to quickly increase recovery rates for our customers while keeping costs down,” Paul Farinacci, president and chief executive offer of Universal Fidelity LP, in a statement announcing the deployment. “Prior to selecting SunGard’s AvantGard Predictive Metrics, we were prioritizing 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 modeling 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,” added Farinacci.

“When a collection agency takes over collections for a corporation, utility, hospital or other entity, it must quickly determine which accounts to prioritize in order to increase liquidations,” said Dwayne Banasiak, VP of business development, Predictive Metrics solutions, at SunGard’s AvantGard business unit. “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,” he said.




Edited by Brooke Neuman

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