The use case: how Progressive deploys H2O.ai
Progressive pairs H2O with SAS and its existing data stack to build many machine learning models quickly on telematics data from its Snapshot usage-based insurance program. The models also support churn, fraud, claims, and marketing work.
More reported results
Figures published in H2O.ai’s case study. They are not independently measured by usedby.
has returned over $500 million in discounts to customers
who save 10 to 20 percent on average
In the customer’s words
With H2O we are able to build many models in a much shorter period of time.Other AI tools used by Progressive
Other public relationships recorded on usedby.
Explore Progressive’s AI stack
H2O.ai users in Insurance & InsurTech
Companies in the same sector, with public evidence.
IFFCO-TokioConfirmed
Jewelers MutualConfirmed
NationwideConfirmed
State FarmObserved
Tokio MarineObserved
Zurich InsuranceObservedGo straight to the source
Based on H2O.ai’s published case study. We check the public evidence; the results are reported by the vendor.
h2o.ai- Last checked
- Nov 4, 2026
Open source capture What the story claims, and what we checked
What we compared with the page.
- The figure: 14 billionChecked
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- The passage quoted aboveChecked
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- Progressive uses H2O.aiChecked
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- The result itselfNot checked
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H2O let the team move beyond GLMs to more sophisticated machine learning and build many models in far less time. Snapshot devices capture speed, time of day, and hard-braking events, and more recently GPS, which the models turn into individualized risk scores that raise or lower a driver's rate.