Banking Churn Prediction

Banks lose revenue when customers churn silently. Proactive retention needs an early-warning signal, not a post-mortem.

An ML model that predicts customer churn for banks, enabling proactive retention, reaching 85% accuracy with XGBoost.

Customer features are engineered from transactional and demographic data, then fed into a gradient-boosted XGBoost classifier tuned for high recall on the churn class.