Predicting churn and NPAs in banking industry

Abstract

Banking industry has been collecting large amounts of information with respect to their customers in the recent years. This information can be used to build data mining models to address various issues such as risk management, portfolio management, trading, customer profiling, and customer relationship management etc. This paper demonstrates the effectiveness of such models in predicting customer churn and non-performing assets.