Insurance Renewal Prediction

Background:

• A global insurance firm is facing minor decline in its motor insurance portfolio sales due to heavy competition in different regions. So, the company wants to take all measures to retain its existing customer base
• The Head of Marketing wants to know which customers are more likely to renew their existing policy and which ones who are likely to churn. The team has planned lucrative offers for both group of customers
• The data science team has the task of predicting the behavior of the insurer's customers in advance to potentially save a churn before it can happen.
• In the code notebook provided below, steps towards detailed Exploratory Data Analysis (EDA) and Machine Learning Modeling to predict churn has been shown in Python
• While the presentation deck covers storyline, presentation of insights to action and how the predictions of churn from the machine learning model can translate to profit in marketing revenue!

Resources:

• Link to presentation (case study)
• Link to code notebook