Customer retention

Abdul August 18, 2020

Leading Life Insurance Company in China and Hong Kong

Problem Statement

• losing out on premium due to rider and policies lapsation.
• Overall lapsation of 16% in China and 13% in Hong Kong

Analytics Led Approach

• It was observed attrition trends in the data over the years and an approach was formulated to provide a solution to contain further revenue leakage
• Predictive attrition model was built to predict the propensity of policies to attrite
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• Given are high level process steps which were followed :
  • Data Load Exploration
  • Model variable Creation
  • Analytical Model Development
  • Business rules
  • possible provider frauds

Business Impact

• Identified policy to rider relations and their lapsation pattern
• Customized retention engine to fit survival model outputs
• Advanced analytical algorithms were used to develop predictive models .
• Provided list of customers based on the policy at risk of attrition for follow up and retain.

Critical Success Factors

• Identified attrition and revival opportunity of worth US $ 10 MN and $ 6 MN for China and Hong Kong respectively