Collection agencies that have not incorporated data analysis into their decision-making and strategic planning need to do so now and the ones that have need to be doing more of it, according to a panel of executives who spoke on a webinar earlier this week about data and how it is re-shaping the ARM industry.
The panelists for the webinar were:
- Sophie Benbenek, Head of Data Science, TrueAccord
- Jake Corlyon, Chief Executive Officer, Capital Collection Service
- Mike Hiller, Vice President – Collections, American Profit Recovery
- Michael Lages, President & Chief Financial Officer, Delta Outsource Group
Most collection agencies are sitting on a mountain of data that can be used to help improve contact rates, collection rates, and everything in between, the panelists agreed. The problem is often knowing where to start.
A lot of agency executives are “stuck in old ways of collecting,” Corlyon said. “But can you afford not be looking at your data?”
For most of its existence, debt collection has been seen as more art than science, as agencies have focused on the skills needed to negotiate with individuals and convince them to make payments on outstanding debts. Knowing the right time to call or send a letter was based on a gut instinct. But the industry is changing, slowly, and agencies should be looking at quantifiable metrics to help guide them through calling strategies, letter strategies, and even negotiation strategies.
“Data gives you the ability to understand how customers are using your system,” Benbenek said during the webinar. “Once you understand how customers are flowing through your system, you can see where the drop-off points are.”
At Delta Outsource Group, for example, one of the new data points that the company is monitoring is the amount of money that is collected on a first call between the agency and an individual. Known as the first-call yield, the company is looking at the metric as a measure of efficiency, Lages said. The company is analyzing which types of debt have higher first call yields, the impact of the size of the outstanding balance, and which collectors are best at getting payments on a first call.
“It’s going to help us re-structure our business,” Lages said. Knowing that data point will help the company “refine and optimize our business.”
It’s important to note that, in most cases, the data collection agencies have access to is not a good model for predicting the actual behavior of an individual, Hiller said. The analysis is a better tool for determining whether there is a connection or correlation between data points. For example, Hiller noted, there is a strong correlation between the agency talking to a “nearby” for an individual and that individual making a payment. But there is also a strong correlation between how strongly a collector attempts to secure a payment on a first call and whether that individual files some form of complaint afterwards.
“With any kind of analytics, it points you in a certain direction to where you need to pay attention,” Hiller said.