“What we have here is a failure to communicate.”
This is the line from Cool Hand Luke that comes to mind whenever the subject of predictive analytics comes up in a meeting with both Collections Operations and Credit/Risk teams. Both groups are using the same words, but each group clearly interprets the meaning of those words very differently. I call this the Great Disconnect, as it seems to be universal across organizations -- creditors and agencies, large and small, sophisticated and unsophisticated -- and because it has had a profound impact on the use of analytics in collections.
One of the more obvious examples of this disconnect can be seen in a creditor’s collections operations. In my experience, most creditors (and I mean almost all) do not even have predictive models for their Late Stage and Recovery portfolios. These organizations have the analytic resources to create these models and long ago embraced the targeting power of modern predictive analytics in the majority of their credit/risk decisioning. So why have these organizations left collections, an area that has such a big impact to their bottom line financial performance, to languish in the Stone Age? I believe that by understanding the answer to this question, managers will be armed to make a significant positive impact on the financial performance of their organizations.
The Great Disconnect
The basis for the Great Disconnect is the different way that operations and credit/risk teams are trained and motivated. This can be illustrated by looking at one of the standard charts used in credit/risk training classes and reading it from the perspective of either a credit/risk manager or of a collections manager.
The chart is divided into four segments based on the balance and risk level of the accounts in the portfolio.
The portfolio from a credit/risk perspective
Let’s start by imagining that you are a credit/risk manager whose reputation (and bonus) is staked on a particular loss percentage. As a credit/risk manager, which one of the segments on this chart would be likely to impact the accuracy of your prediction the most if the economic conditions were starting to get worse? Everyone that I have ever asked this question of always picks the High Risk/High Balance segment. Since the collections operation of most creditors reports directly or by dotted line to the credit/risk group, you can imagine what the direction from above is, “Focus on the High Risk/High Balance accounts.”
Taking the collections perspective
Now let’s switch our perspective and imagine that you are the collections manager and your reputation (and bonus) is tied to collections performance. Which one of the segments in the chart would you want to focus on? People always answer that the collections manger should focus on the Low Risk/High Balance accounts, as that is the segment where their efforts will make the biggest impact. You might think of this as more of a “marketing” approach, where you focus your effort on those more likely to respond and de-emphasize the non-responders.
Dealing with the Great Disconnect
These are two very different and conflicting points of view, but the credit/risk managers are usually the ones who set the agenda. As a result, the direction has been to focus on the High Risk/High Balance group. From the collections operations perspective, this could be interpreted as “waste your effort on the accounts that aren’t going to pay,” which puts the collection operation in an impossible situation. If they follow that direction, they put their operation’s success (and their bonus) at risk.
The natural “compromise” solution that has developed over the years to deal with this conflict between the collections operation and the credit/risk team has been for the organization simply not to use models. The evidence of this compromise is that few organizations have or use predictive analytics in the late stages of collections and recovery operations. This is frustrating for both the credit/risk and the collections managers and has a negative impact on the performance of the operation.
Understanding the Great Disconnect is the first step toward fixing it. Fortunately, I think it’s relatively easy to fix, especially now that strategic predictive analytics products are available to help the credit/risk and the collection operations teams work together to facilitate targeting the right accounts. More on that next time.