Reduce Policy Lapse

With iTuring, you can build extremely accurate lapse prediction models to identify which policyholders are likely to lapse and proactively identify potential policy lapsation. iTuring will not just help you predict risky policyholder but also provide causes of lapsation with detailed information and help you build an appropriate strategy to prevent revenue leakage.

For a leading General Insurance company in India, CyborgIntell used iTuring to build “Lapse Prediction for Fire Insurance” to prevent revenue leakage and develop a customer centric strategy for retention and improved customer experience. Assist the renewal team in identifying potentially risky customers with driving factors leading to a lapse and support their treatment strategy to retain them. Business retained 16% policyholders who were likely to lapse in the coming year, analysing just top 20% policyholders with high probability to lapse.

To improve loyalty, Insurer started using iTuring developed policyholder level risk causation metrics, to understand actual cause of lapsation for all risky policyholders. Developed treatment strategy to not just retain them but also provide dedicated representatives for superior customer experience. Insurer developed property level contact strategy and saved 9% erosion in their risky policy with 93% model accuracy.