Predictive Modeling for Customer Retention in the Banking Sector

Problem and General Objective

This dataset is originally found on the website https://leaps.analyttica.com/home, but it was obtained from https://www.kaggle.com/sakshigoyal7/credit-card-customers.

• The manager of a bank branch is worried about a growing number of customers leaving their credit card services
• The goal is to proactively predict which customers should be targeted for improved services to reverse their decision to leave
• The dataset contains information on 10,000 customers, including age, salary, marital status, credit card limit, and category
• Only 16.07% of customers who have left the service are included, making the dataset imbalanced
• Transformations will be necessary to address the dataset's imbalance

Specific objectives:

• Identify behaviors and characteristics of individuals who tend to leave or stay with the bank's service
• Generate a model that can predict whether a customer will leave or stay with the offered service
• Propose short and long-term actions that can better retain customers who are leaving based on the obtained information