Credit Card Analysis

Authors

• Di Wu, CUNY Lehman CollegeFollow

Document Type

Case Study

Publication Date

Spring 5-31-2026

Abstract

A credit card business unit at a bank is facing a retention problem. More customers are leaving the bank's credit card services, and the retention manager wants to identify which customers are most likely to churn so the bank can intervene before the account is lost.

The bank has customer demographic, relationship, and transaction data for more than 10,000 credit card customers. The data includes age, gender, education, income category, card category, months on book, customer inactivity, contact frequency, credit limit, revolving balance, transaction amount, transaction count, and whether the customer attrited.

You are a business analyst on the bank's customer retention team. Senior management wants a practical, data-supported retention strategy. The team does not only need to know whether churn can be predicted; it needs to know which customer behaviors are most associated with churn and what actions the bank should take.

Comments

This OER was funded in part by the CUNY OER Initiative.

Creative Commons License

This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License

CUNY OER Funding

CUNY OER Initiative