The use case: how IFFCO-Tokio deploys H2O.ai
IFFCO-Tokio, a general insurer, deployed H2O AI Cloud on-premise and used automated machine learning to build fraud detection models that score motor insurance claims by fraud probability. It later built a second model for health insurance claims.
More reported results
Figures published in H2O.ai’s case study. They are not independently measured by usedby.
The models flag 100x more confirmed fraudulent claims each month than before, letting officers concentrate on high-probability cases while genuine claims move faster.
Within one month, customer retention rose 3 percent.
In the customer’s words
H2O AI Cloud is a platform that my team can learn by themselves. I find the platform to be very friendly for people who are not data scientists or have little knowledge of data science.H2O.ai users in Insurance & InsurTech
Companies in the same sector, with public evidence.
Jewelers MutualObserved
NationwideObserved
ProgressiveObserved
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
- Oct 24, 2026
Open source capture What the story claims, and what we checked
What we compared with the page.
- The figure: $1MChecked
Printed word for word on the page, near the name of IFFCO-Tokio.
- The passage quoted aboveChecked
Copied word for word from the page, near the name of IFFCO-Tokio.
- IFFCO-Tokio uses H2O.aiChecked
Confirmed line.
- The result itselfNot checked
We quote it; we did not measure it.
The fraud use case saves IFFCO-Tokio more than $1M USD, roughly 70M INR, every year. The models flag 100x more confirmed fraudulent claims each month than before, letting officers concentrate on high-probability cases while genuine claims move faster.