Case Study: IFFCO-Tokio saves over $1M annually on fraud with H2O.ai
Key results
The challenge
IFFCO-Tokio, a joint venture between Indian Farmers Fertilizer Co-operative and Japan's Tokio Marine Group, wanted to detect and predict fraudulent insurance claims. It needed to do so with a small in-house team of three developers with limited data-science experience, while keeping data on-premise for privacy reasons.
The solution
Guided remotely by an H2O.ai Kaggle Grandmaster, IFFCO-Tokio used H2O AI Cloud's automated machine learning with pre-built algorithms to build and deploy an on-premise fraud-prediction model for motor insurance claims in July 2021, later extending it to health insurance claims.
“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.”
SGSeema GaurChief Information Officer and Head of IT, IFFCO-Tokio
The results, in context
Using models built on H2O AI Cloud, IFFCO-Tokio sieved out fraudulent claims and expects to save almost 70 million Indian Rupees (about US$1 million) annually. Since the online-customer trial began in July 2021, customer retention increased by three percent.