Note: This post is the first in a four-part series based on CCC’s research, “Pillars of a Customer-Driven Collections Strategy”. In this series, we’ll discuss the research findings and best practices that can help your organization adopt a more effective approach to debt collections—moving away from a pure quantity focus and toward a quality, customer-oriented collections strategy.
While we’re beginning to hear good news that the U.S. and global economies are poised to rebound, tough financial times—and the high delinquency volumes that accompany them—continue to have some big implications for collections in many organizations. To better understand this timely topic, CCC turned to our membership network, where conversations revealed not only a diverse set of challenges associated with the collections function, but also highlighted a wide range of strategies that companies pursue when it comes to collections.
In terms of strategy, most companies realize the insufficiency of a pure quantity-based approach that stresses “more calls, more dollars”—and often neglects the cost side of the equation. Such an unfocused model inevitably leads to poor decision-making and misallocation of resources, giving a “one-size-fits-all” treatment to all accounts, even those that will eventually self-cure.
Given that fact, many companies struggle to find the right way to segment their customers, mainly because they fail to pinpoint the root causes of delinquency—and modify their actions to address these specific causes. One way we’ve seen this root causing done successfully is through risk scoring: analyzing customer information to identify unique sources of delinquency, and adjusting collections tactics based on these sources. In practice, this strategy has three key components/steps:
1) Principled Regression – an algorithm uses historical payment data found in the CRM system (number of payments missed, age of account, age of arrears, etc.) to calculate the overall likelihood of delinquency, assigning individual scores that assess a customer’s charge-off risk (the likelihood that their debt will not be collected).
2) Routine Assessments – changes in a customer’s risk of delinquency are captured through regular reassessments that include the latest available account information, providing dynamic feedback into the riskiness of particular customers and flagging new high-risk accounts.
3) Targeted Efforts – the resulting risk score then dictates the collection channel used for a particular customer, ranging from a simple reminder letter of delinquency for low-risk customers to immediate termination of service for high-risk customers. The underlying logic for channel management in customer service holds true for collections, as well: first identify and separate customer needs, then match them to the appropriate channels.
This segmented approach is effective at both ends of the risk spectrum, efficiently allocating collections resources toward high-risk customers without damaging the customer experience for lower-risk customers through overly aggressive collections tactics (and there’s no shortage of collections horror stories around these heavy-handed methods).
What’s more, it fundamentally changes the nature of the collections function, creating better alignment between customer service and collections—a goal that many executives have struggled to achieve as enterprise standards for customer service continue to rise. This approach also lays a solid foundation for collections activities going forward, which we’ll discuss in greater detail in future blog posts.
Stay tuned to CCC Buzz for coming installment of our series on debt collections, and be sure to review our research brief to learn more.