3 Ways Data-Driven Analytics Helped Toyota Financial

dataToyota Financial Services boosted investment in big data analytics to revamp its collections processes, and it has already yielded results, according to Jim Bander, the captive’s national manager of decision science.

“We’ve been concerned with improving collections since 2009,” Bander said. “Certainly we got affected the same way all the other lenders did with the recession and we decided to make an investment in analytics.”

The program, which launched in August 2014, enables TFS to predict when and how a consumer wants to be contacted regarding missed payments. Using data gathered from the consumer’s contract and payment history, credit reports, and score cards purchased from third parties (including credit bureaus) the captive is able to determine high- and low-risk consumers and the best collection methods for each consumer.

TFS then uses the data to forecast “if a consumer takes action A, we will get response B,” Bander said. “We use prescriptive analytics to predict that to keep customers in their cars and to avoid hurting their credit,” he added.

The program allows TFS to work directly with consumers earlier in the process regarding troubled car loans. The company also developed a direct call model — Pass to Partnership — to listen to the consumer’s needs, ask what can be done to resolve the issue, and provide a payment extension in the appropriate situation, Bander said.

In the end, Bander highlighted three benefits of a data analytics-driven collections process:

  • Reduction bad credit losses

Toyota is able to reduce credit losses by contacting the customer on the right day, in the right forum, to prevent the consumer from rolling over to a later stage of delinquency. This system can also prevent the amount of skip charge-offs, according to Bander.

  • Decrease in operating expenses

The program allows for more controlled operating expenses because the prescription analytics allows TFS to achieve a business objective that is subject to those limits, Bander said.

  • Increase in marketshare

By lowering the amount of debt collections, the captive can increase its marketshare, Bander said. “An old adage in finance is that ‘you buy what you collect,’” he added. As TFS becomes more effective with its collections, the company can, in turn, offer better support to its dealers.

Before the launch of the collections program, TFS took a traditional “bucket-based” approach to handle missed payments. After a missed payment, the consumer received an automated call reminder, and after two, the consumer was assigned to a mid-stage representative. Finally, when the consumer rose to a later stage of delinquency, a single debt collector was assigned to the account, he added.

The new program allows for flexibility in consumer-collector interaction, which ranges from an automated call reminder to a personal call from a collector, depending on the consumer’s predicted preference.

The program is a win-win for everyone, Bander said. Toyota Financial Services has kept 10,000 customers from reverting to a higher stage of delinquency to date, and has been “able to keep 1,600 customers in their cars, and make millions of dollars for Toyota’s bottom line,” he added.

  Like This Post

One thought on “3 Ways Data-Driven Analytics Helped Toyota Financial

  1. […] the webinar, Bander shares five lessons learned from when TFS implemented a behavioral analytics-based program aimed at boosting collections […]

Leave a Reply