Data Sciences -
Policy Lapsation



This video demonstrates how Data Sciences is able to pre-empt policy lapsation by gathering and analyzing key data points.

In this case, a large insurance provider in India, who faced a high rate of policy lapsation, wanted to proactively identify the policies that were likely to lapse for undertaking timely retention measures.

Data Sciences was able to identify the risky customer and customize strategies for retaining them by using Supervised Machine Learning, Propensity Models, and multiple algorithms.

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