How Underwriters Win Business With Data and ML at AXA XL

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."

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.

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.