Abstract:

The banking industry is well known for its competitiveness and dynamic operational environment, with different suppliers providing a wide range of products and services to attract and retain customers. Recent research shows that customer retention is an expanding issue in this sector. This study aims to predict customer churn in banking organizations using different machine learning algorithms. The study evaluates seven competing algorithms' performance and reports a bestperforming model that predicts customer churn. This study's findings would interest researchers and practitioners seeking to reduce customer churn in the banking industry.