An Insurance company that has provided Health Insurance to its customers. Now it wants to find out whether its customers from past year will also be interested in Vehicle Insurance provided by the company.
Building a model to predict whether a customer would be interested in Vehicle Insurance is extremely helpful for the company because it can then accordingly plan its communication strategy to reach out to those customers and optimise its business model and revenue.
We have the data of which contains details of customers like id , age, gender and also contains the details of the customers vehicle.
The dataset contains features like:
id :- Unique ID for the customer
Gender :- customers’ gender
Age :- Age of the customer
Driving_License :- Customer is having driving license or not
Region_Code :- Unique code for the region
Previously_Insured :- Whether the customer has insured previously or not
Vehicle_Age :- Age of the Vehicle
Vehicle_Damage :- Is the customer got his/her vehicle damaged in the past
Annual_Premium :- The amount customer needs to pay as premium in the year
PolicySalesChannel :- Anonymized Code for the channel of outreaching to the customer ie. Different Agents, Over Mail, Over Phone, In Person, etc.
Vintage :- Number of Days, Customer has been associated with the company
Response :- The customer is interested or not
Target Variable :
Response :- The customer is interested or not
Importing Libraries
Loading the dataset
Data Summary
Data Cleaning & Data Analysis
Feature selection
Implementing Various Classification Algorithms
HyperParameter Tuning
Final selection of the model
From this dataset of health insurance customers almost 95% of customers have a vehicle age that's less than 2 years. from our analysis, customers who has more than 2 years of vehicle age are more interested with vehicle insurance advertisment, while customers who has less then one year of vehicle age, only 4% of them are actually interesred with vehicle insurance
We found out that customer who already have vehicle insurance are almost have no interest in another vehicle insurance. Our analysis shows that 99.9% of customers that have a vehicle insurance is not interested in another vehicle insurance, while customer who doesn't have a vehicle insurance 22.5 % of them are interested with vehicle insurance
We also found out that a newer vehicle are more likely to have a vehicle insurance, with vehicle that's less than one year 66% of those are insured , vehicle that's older than one year but less than 2 years are 33% insured, while less than one percent of vehicle that's older than 2 years are insured. This should explain why customer who owns a newer vehicle are less likely to be intersted with insurance promotion, because they probably alredy have one.
Customers who never had vehicle damaged only 0.5 % of those customers are intersted with vehicle insurance, 87% of customers who never had any vehicle damaged already have a vehicle insurance.