aspagnuolo / cross_sell_prediction

model to predict whether a customer would be interested in vehicle insurance

Health Insurance Cross Sell Prediction

Our client is an Insurance company that has provided Health Insurance to its customers now they need your help in building a model to predict whether the policyholders (customers) from past year will also be interested in Vehicle Insurance provided by the company.

The dataset consists of the following properties:

• id: unique identifier of the policyholder.
• Gender: gender of the policyholder.
• Age: age of the policyholder.
• Driving_License: 1 if the policyholder has a driving license, 0 otherwise.
• Region_Code: unique code for the policyholder's region.
• Previously_Insured: 1 if the policyholder already has a vehicle insured, 0 otherwise.
• Vehicle_Age: age of the vehicle.
• Vehicle_Damage: 1 if the policyholder has damaged the vehicle in the past, 0 otherwise.
• Annual_Premium: the amount that the policyholder must pay as a premium during the year.
• Policy_Sales_Channel: anonymized code of the channel used for the proposal (e.g. by email, by phone, in person, etc...)
• Vintage: number of days the policyholder has been a customer of the company.
• Response: 1 if the policyholder responded positively to the sales proposal, 0 otherwise.

The purpose of the model is to predict the value of Response.

The project is divided into three parts:

• exploratory data analysis (EDA);
• construction of different models to address the problem of class imbalance;
• choice of the best model.