Insurance companies around the world operate in a very competitive environment. With various aspects of data collected from millions of customers, it is painstakingly hard to analyze and understand the reason for a customer’s decision to switch to a different insurance provider.
For an industry where customer acquisition and retention are equally important, and the former being a more expensive process, insurance companies rely on data to understand customer behavior to prevent retention. Thus knowing whether a customer is possibly going to switch beforehand gives Insurance companies an opportunity to come up with strategies to prevent it from actually happening.
Given are 16 distinguishing factors that can help in understanding the customer churn, your objective as a data scientist is to build a Machine Learning model that can predict whether the insurance company will lose a customer or not using these factors.
You are provided with 16 anonymized factors (feature_0 to feature 15) that influence the churn of customers in the insurance industry
https://www.kaggle.com/k123vinod/insurance-churn-prediction-weekend-hackathon
