Application of Machine Learning and Statistics in Banking Customer Churn Prediction

Abstract

Application of the core concepts of Machine Learning and Statistics for predicting whether the customer would leave the services of the bank in future or not. Machine learning model is trained by considering the data of 10,000 customers of the bank. Statistical Techniques are applied so as to investigate the data in depth and infer the relationships between different features or variables of data. The web application uses the trained model in the backend to predict the probability of the customer leaving the bank. Hence, the website can prove to be extremely useful for the bank managers and decision makers of the bank to get an idea of those customers who are likely to leave the services of the bank in future and can retain them by formulating some new policies.