Web Application for Banking Churn Prediction Using ANN

Customer in action or disengagement over a period of time is referred to as churn. In this project, we are developing an application that will automatically deliver offers to customers who are about to depart when it has been determined that they are leaving. With this, we have finished classifying various algorithms and identifying algorithm churn. To create the web application, we used 50,000 customers’ data and 29 distinct parameters. This project’s primary goal is to identify high-risk departing clients. We use an artificial neural network to solve the problem. We have discovered 98% accuracy and 0.1 loss as a consequence. The maximum accuracy is therefore discovered, and neither an overfitting nor an underfitting model is discovered. Additionally, an accurate forecast is discovered, allowing the bank to deliver offers to the consumer and lowering the churn rate. As a result, bank profit is increased. Python is being used to implement this project. Notification is sent by a telegram.