Frank Fiorille heads a team of approximately 250 risk management stewards at payroll, HR and benefits service giant Paychex. Prior to his arrival, the appetite for risk models at Paychex was low, and the company mostly viewed its operations through top-line revenue returns.
Fiorille assembled a small modeling team within the risk group to delve into the B2B database, from which 9 million people are paid every other week. The store contains 560,000 small businesses that “transact very similar to consumers,” he says. From that, models have rolled out predictive capabilities for collections, credit risk, operations and “hidden jewels” of insight for the company.
“We hired a few Ph.D.s to create this nimble modeling group. It’s nothing like you’d find at huge companies, but I like it that way. We’ve got our team together and we know who everyone is and we’re able to work closely and churn out some great model products,” Fiorille says.
Fiorille melded experiences at “very analytical” financial institutions with his education, including a risk degree from an inaugural program at the University of Pennsylvania Wharton School, for an approach that focuses on data-driven results visible to the C-suite as well as underwriters in the field. Before any risk algorithm is dialed up, Fiorille said the end goal must be conveyed so models can flourish – and be fixed – based on a shared business plan.
“They all don’t work, right? So you might have a really good idea, you think it’s a great plan that could be implemented and all that and you spend time and resources and you bring it down to the staff and start building something, but it just doesn’t work,” he said from his office at Paychex’s Rochester, N.Y. headquarters. “But having a clear understanding of objectives overall and to see the business demand for that model helps that success rate go up.”
Quotable: “Models are based on history and if history changes or if there is a significant reset of everything, sometimes those models don’t work. Given that we just went through a great recession, a lot of volatility and dynamic things are coming up right now, in the economy and in general. For our whole industry, the result might be that some of these models aren’t useful. It goes both ways.”
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