Leading life insurance provider
BFSI players often collect data from multiple data sources and struggle with collating the entire data to
- Get a 360-degree view of the customer
- Calculate their risk averseness. Understanding how risky is each customer is important to pitch them relevant products, detect frauds, etc.
- BluePi has built a machine learning-based Customer Risk Profiling system.
- The primary objective is achieved by segmenting customers as high risk, medium risk and low-risk customers based on parameters like demographics, education, health details, policy attributes, etc
- The data was stored on S3 and the algorithm being used to solve the problem was implemented and trained on EMR using that data
The model helped client to:
- Propose the right solution to the customer based on his/her risk score
- Run targeted marketing and outreach campaigns
AWS Service used
EC2, S3, Redshift, EMR, Glue