Personal Loan Offer Marketing

The project aimed to optimize marketing strategies, enhance customer satisfaction, and improve resource allocation by developing Logistic Regression. Key features included Income, Age, Family, CCAvg, CD Account, Mortgage, Securities Account, Credit Card, and Online Banking. The model achieved high performance with an accuracy of 0.934 and an ROC AUC of 0.936. Income emerged as the most significant predictor of loan acceptance. This data-driven approach provides valuable insights for strategic decision-making in the banking industry.