CHURN MODELLING

Computer Engineering

A churn model is a mathematical representation of how churn impacts our business. Churn calculations are built on existing data (the number of customers who left your service during a given time period). A predictive churn model extrapolates on the data to show future potential churn rates. Customer churn is an imperative issue that is frequently connected with the existing cycle of the business. In recent year, churn prediction is becoming a very important issue in Banking and telecom industry. Data set contains details of a bank's customers and the target variable is a binary variable reflecting the fact whether the customer left the bank (closed his account) or he continues to be a customer. This model is used to predict the fact whether the customer left the bank. The dataset is taken from Kaggle Churn modelling. It contains details of a bank's customers and the target variable is a binary variable reflecting the fact whether the customer left the bank (closed his account) or he continues to be a customer. In order to deal with this problem, the industry must recognize these customers before they churn. Therefore, developing a unique classifier that will predict future churns is vital.

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