Loan Customer Analysis System using Column-wise Segmentation of Behavioural Matrix (CSBM) - Mandal, Rakesh Kumar; Manna, NR (International Journal of Computer Sciences and Engineering, 2015)
In order to approve bank loans, modern day researchers and bankers are involved in different types of work related to analysis of the behaviour of the loan applicants. Customer data are collected to analyze their behaviour which may predict the possibility of repayment of the EMIs. In this paper, a new approach has been made to make this process fast. The data used to analyze customer behaviour are actually behavioural patterns. Artificial Neural Networks (ANNs) are very good tool to train a system for known patterns and which can later be used to identify unknown patterns. Two dimensional binary pattern matrixes are formed considering different behaviour of customers from different views. Matrixes are further segmented column-wise and each column is presented to Perceptron (ANN) in order to train the ANN for the known patterns. Later on, unknown patterns of customer behaviour can be presented to the net to reach to the decision to provide loan to a customer or not.