Leading Life Insurance Company In Japan
- A high attrition in the customer base due to competition and miss-selling (45% is overall lapse rate)
- Expectation was to build an approach to retain policies and to set up an early warning system to identify a potential attrition cases to prevent further revenue leakage
Analytics Led Approach
- Attrition trends in the data over the years were analyzed and an approach was designed to provide a solution to contain further revenue leakage
- Predictive attrition model was built to predict the propensity of policies to attrite
- Given are high level process steps which were followed :
- Data Load Exploration
- Model variable Creation
- Analytical Model Development
- Business rules
- Raw data was mined, and a methodology was built for developing a predictive attrition model to provide a probability score to influence the decisions to follow the case by the customer.
- Model output was segmented to optimize the approach to follow the case and provided insights to treat each policy based on the segmented matrix Re-evaluate;Retain;Grow;Protect– for example, Retain is the quadrant high value and high risky policy, retaining such policies will optimize the effort as well as cost
- Primary users, retention team were provided with insights for customer retention..