Van Ru Case Study

Reduced Effort Yields Better Outcome

Does that seem counterintuitive? Not when you consider this: by knowing in advance where your efforts are most likely to succeed, you can save a tremendous amount of time and energy.

A bill is in collection. Can the customer pay something? Anything? An individual customer's ability to pay can change rapidly, and the collector wants to make sure that his bill is at the top of the list when the customer has money. The collector relies on his power of persuasion to convince the customer to make his bill a priority. But collectors have large portfolios, and it is impossible to stay in regular contact with each and every customer. How does the collector know the best place to focus his efforts?

Van Ru Credit Corp., a leader in the accounts receivable management industry, uses Intelligent Results PREDIGY platform to help identify the groups of accounts that are likely to yield the best results. With over 1,000 employees in six call centers, Van Ru serves a wide range of customers in healthcare, education, financial services, and other industries. To maintain their client focus, Van Ru needs to be able to adjust their strategies in order to best address different portfolios. PREDIGY enables them to make as many adjustments as needed, quickly and profitably. Don Helms, Van Ru's Director of Analytic Solutions, continues to expand the use of analytical applications built on the PREDIGY platform to improve collections performance and minimize effort expended.

The Challenge

In the past, Van Ru relied on industry standards when deciding where to focus their efforts. This often meant segmenting portfolios by amount owed or by region. There might be data from third-party credit reports. Experienced collectors could make educated choices about the likely success of collecting from certain accounts. These methods were useful, but didn't go far enough.

The collections business was also changing—more clients were collecting the easy accounts themselves, leaving companies like Van Ru with older accounts that had already been worked by others. And the percentage paid by the clients was decreasing. "In short," according to Don Helms, "the accounts were getting tougher and the rewards smaller." Wasted effort could easily mean losing money—the expense of the collection could exceed the amount collected. In this environment, the ability to focus efforts was becoming more and more important, and Van Ru looked for ways to better understand its portfolios.

Increasing Insight, Exerting Control

Van Ru believed that a better understanding of available data could be a crucial factor in its success, so they investigated ways to gain the insight needed to work their portfolios more effectively. One option they looked at relied on linear regression analysis created by consulting statisticians. Don Helms says, "PREDIGY can do linear regressions too, but it is so much more powerful than that—time and time again."

PREDIGY enables Van Ru to analyze specific portfolios in more in-depth ways. Don says, "The analytics can help identify which groups of customers within a portfolio will be most likely to pay." Once PREDIGY has helped identify the most promising groups of accounts, then operations can direct collectors to work those groups. The result: more money is collected on the portfolio, and less money is wasted on efforts that are unlikely to produce results. With PREDIGY, Don says, "we focus in a more intelligent way, and that yields more money. Van Ru, its clients, and its employees all benefit."

Next Steps: More Data, Even Better Insight

Right now, Don's focus is still on using PREDIGY to continue improving the performance of Van Ru's retail portfolios, where there's a lot of volume. He is looking at models related to client information at placement and then at data collected subsequently.

In addition to building new models, Don continues to adapt existing models using new data. These refined models can then provide even more accurate information. For example, with data collected over time, a model can be adapted to predict what groups of accounts are most likely to pay over a certain period of time.

New Directions

Don also sees an opportunity to use PREDIGY in the realm of student loans—an area that provides different challenges and—of course—opportunities. One big difference: the possibility of loan rehabilitation as an alternative to traditional collections.

In a rehabilitation scenario, the customer makes qualifying payments over a 9-month period, and the loan is then repurchased by a lender. Credit is re-instated on the entire loan, and the default can be erased. This scenario offers great benefits to everyone, but it can be difficult, and many customers aren't up to the challenge. The rehabilitation process takes a lot of effort on the part of the collector, so it's important to identify situations where success is likely. Don wants to use PREDIGY to create a model to identify people who are likely to make it through the intensive 9-month process. Van Ru can then offer other options to people who are unlikely to succeed with the rehabilitation process.

Ongoing Benefits

PREDIGY enables Van Ru's collectors to focus their persuasive skills on the customers who are mostly likely to be able to pay, and that provides benefits all around. Even better, these gains aren't static: as portfolios and the market continue to change, the data can continue to yield more and better information.

About Van Ru

Van Ru Credit Corp. has been in the receivables management business for over 50 years. It is headquartered in Des Plaines, IL. www.vanru.com.

Don Helms is the Director of Analytic Solutions at Van Ru. He has been with Van Ru for 9 years and has held several positions, including Director of Student Loans and Assistant General Manager.