Imagine being able to tell a broker prior to a submission, “I can take this account in my underwriting portfolio,” instead of giving a broad appetite listing for the distributor to puzzle through.
Executive Summary
A machine learning model that flashes stop-and-go signals to underwriters in AXA XL's environment unit and a distribution tool that fills the U.S. business pipeline with carrier-selected accounts are two of the successes that underwriting leaders Matt O'Malley and Steve Stabilito attribute to a cross-functional focus on insights hidden in decades of insurance data. Here, they provide a high-level view of what it takes to win with data—curiosity, simplification, funding outside of business units, bite-size proofs of concept and communication.Michael (Fitz) Fitzgerald, Insurance Industry Advisor for SAS Institute Inc., served as guest editor for this article and others featured in CM's Q1-2024 magazine, "Leading the AI-Powered Insurer."
A grassroots effort by underwriters to incorporate data in their decision-making has turned the vision into reality at AXA XL, according to Matt O’Malley, AXA XL’s U.S. country manager and East zone manager, who described the benefits of a machine learning tool for pipeline management that was created from predictive relationships buried in the carrier’s data.
“The aha moment has been realizing what the conversion ratio has turned out to be,” O’Malley said. There’s “a difference between telling someone specifically, ‘I can really perform on this account based upon our data and analytics’ versus describing to a broker that this is generally what I want, and then leaving the broker trying to figure out as things come across their desk, ‘Does this fit what that person told me?'”
“Now, we’re able to do that across multiple lines of business,” O’Malley continued, explaining that the machine learning tool is able to identify where AXA may have interest in offering different lines of insurance to the same client. “This really brings an additional client lens to AXA. There are lots of places where we can engage and solve needs for clients that we hadn’t been addressing in the past. And it’s all coming from the data,” he said.
