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  • 1. Managed customer retention for Life Insurance co.BUSINESS OBJECTIVE: To improve policy persistency by proactively identifying policy holders likely to lapseand take pro active measures to keep them in portfolio. Improve Lapse Reduced Data Policy Analysis Prediction Policy Model Persistency Lapsation Customer Strategy to Develop level Single Targeted Reduce Framework View of Campaign Lapsation Data www.valiancesolutions.com
  • 2. Managed customer retention for Life Insurance co. Quantitative Analysis of Lapsation What are the reasons for attrition? What are patterns in customer attrition across different tenure of policy? How does the attrition rates change by changing factors? What is the probability of a customer to attrite? What channel or combination of channels which will deliver the most conversion? Analysis Frame: Model Validation The Lapsation model generated a probability for every active customer to lapse Top 30% of customers (when sorted descending by probability to lapse) had 75% of lapsers • The model was validated for the month of June. Top 30% of customers contained 78% of • lapsers • www.valiancesolutions.com
  • 3. Managed customer retention for Life Insurance co. •Proactive campaigning to customers having high likelihood to lapse •Customers were segmented basis the probability to lapse and APE band Risk_Group Probability of Lapsation H >0.18 APE BAND M 0.03-0.18 L <=0.03 18% 8% 14% Risk Group LE_18K 18K_25K GR 25K Total APE Band APE 15% 8% 7% H 40% H >25K M 18K-25K 10% 7% 13% M 30% L 30% L <=18K Total 43% 23% 34% 100% High Risk – Priority 1 Medium Risk – Priority 2 Customers were targeted first in this segment Low Risk – Priority 3