Key takeaways
- Progressive described 14 billion telematics miles and 20+ years of driving data from its Snapshot program, and used H2O for four model families: customer churn, billing, fraud detection and threat analysis.
- The Progressive figures describe its program and its use of H2O, not a published loss-ratio or ROI result.
- H2O Driverless AI and H2O-3 build explainable models from trip data joined to policy and claims history, with reason codes on every prediction.
- The models sit on top of your policy and claims systems and feed your existing fraud screening, so the core you run today stays in place.
Turn driving data into a score your claims and SIU teams can use
Telematics gives you trip-level data on how, when and where each policyholder drives. The volume grows every day, and most of it never reaches the claims desk or the special investigations unit (SIU).
You are measured on claims fraud leakage and on the quality of every referral your SIU works. Fixed screening rules catch the patterns you already know, and each false referral costs an investigator's time.