Credit Card Users Churn Prediction

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What is Customer Churn? Customer churn means a customer’s ending their relationship with a bank/company for any reason. Although churn is inevitable at a certain level, a high customer churn rate is a reason for failing to reach the business goals. So identifying customers who would churn is very important for business

Context

The Thera bank recently saw a steep decline in the number of users of their credit card, credit cards are a good source of income for banks because of different kinds of fees charged by the banks like annual fees, balance transfer fees, and cash advance fees, late payment fees, foreign transaction fees, and others. Some fees are charged to every user irrespective of usage, while others are charged under specified circumstances.

Customers’ leaving credit cards services would lead bank to loss, so the bank wants to analyze the data of customers and identify the customers who will leave their credit card services and reason for same – so that bank could improve upon those areas

Objective

• Explore and visualize the dataset.
• Build a classification model to predict if the customer is going to churn or not
• Optimize the model using appropriate techniques
• Generate a set of insights and recommendations that will help the bank

Business Recommendations & Insights

• Lower transcation count on credit card , less revolving balance , less transcational amount are an indication that customer will attrite. Lower transcation indicate customer is not using this credit card , bank should offer more rewards or cashback or some other offers to customer to use the credit card more.

• As per the EDA if customer hold more product with the bank he/she is less likely to attrite.Bank can offer more product to such customers so they buy more products which will help retain such customers

• Customers who have been inactive for a month show high chances of attrition.Bank should focus on such customers as well.

• Avg utilization ratio is lower amongst attrited customers.

• As per EDA Customer in age range 36-55 ,who were doctorate or postgraduate ,or Female attrited more. One of the reasons can be some competitive bank is offering them better deals leading to lesser user of this banks credit card.

• As per the EDA Customers who have had high number of contacts with the bank in the last 12 months have attrited. This needs to be investigated whether there were any issues of customers which were not resolved leading into customer leaving the bank.