Persistnecy Management - II in Anatomy of Decisions

In the previous segment, you learnt how important it is for an insurance company to make sure that its customers renew their policies. You also learnt how analytics can be used for a targeted reach out to make sure that the customers renew.  You are aware that exploratory data analysis is the first step for any analytics project. In the following video, Ashish will walk you through the analytics process and how analytics is used to make informed decisions.

In the above video, you learned that before analysing the data, you need to generate some hypotheses based on which you perform the EDA.  The EDA does help us in getting a broader perspective of data and we are in a position to understand it better. The model was built and the predicted variable used was the renewal propensity for a customer. The model’s output was shared with the contact Centre team who uses the list to start calling the customers well in advance.

You learnt that any improvement can not be attributed directly to the analytics team as there are multiple teams involved. However, at the end of the project, the 13-month persistency improved by about 20%

In the next segment, we will learn about another important issue, that is cross-selling the policies to the existing customers.