Customer Churn Prediction in the Telecommunications Sector Using Explainable Artificial Intelligence
This paper proposes a comprehensive Machine Learning pipeline that bridges the gap between predictive performance and model interpretability and integrates SHAP-based Explainable Artificial Intelligence to provide both global and local interpretability, revealing that contract type, tenure, and technical support subscriptions are the primary churn drivers.