With consumer debt at an all-time high, financial institutions are being pressured to reclaim unpaid debt to rebuild cash reserves in a tightening market. Collecting this debt requires resources to execute the collection process – resources that are limited. Collections optimization from SAS, the leader in business analytics, helps companies maximize the return from collection efforts while reducing costs.

“Financial services institutions must re-gear their analytic techniques to adapt to a new playing field,” said Brian Riley, Research Director of Bank Cards at TowerGroup. “Rising unemployment, coupled with a protracted recession and increased credit costs make existing tools obsolete. Successful lenders that apply advanced analytics to optimize their strategies experience particularly strong results.”

Debt collection is delicate. Customers are sensitive to how, when and why they are contacted. Most debt collection approaches fail to identify who best to contact or which channels to use. Call centers – often the most effective communication method – are also the most expensive. Collections optimization from SAS, using predictive analytics, helps companies make effective use of their call centers and alternative methods of communication (SMS, IVR, email) that may also achieve successful results at low costs.

SAS delivers software and services that:

• Develop customer models  to understand who is most likely to respond, which communication channels will work best and how much payment to expect.
• Evaluate multiple channels simultaneously to determine which channels for individual customers will maximize return.
• Vary constraints and re-run scenarios to understand the impact of changing call-center capacity, altering contact policies, or adjusting other constraints – all via an easy-to-use interface.
• With SAS, collection managers can plan and prioritize outbound communications for best results, balancing the organization’s capacity with the likelihood that customers will respond. Optimizing the collections process can also lead to an improvement in the long-term relationship between the financial institution and its customers.

A premier financial institution in Australia uses optimization on its past-due customer accounts. Prior to using SAS, the bank’s collections team relied on instinct to determine which communication to assign to the various different contact channels. Now, they use collections optimization to apply a mathematical approach to decide which channel will maximize payment rates. Since introducing the new technology there has been a 300 percent return on investment.

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