Loan Customer Analysis System using Row-wise Segmentation of Behavioral Matrix (RSBM) - Mandal, Rakesh Kumar (International Journal of Computer Sciences and Engineering, 2025)
Different types of studies are going on among researchers and different approaches are adopted by the bankers to analyze the behavior of the loan applicants to approve those loans. Bankers collect customer data to analyze their behavior in order to predict the possibility of recovery of the amount. Domain experts can think about a new approach to make this process fast. The data used to analyze customer behavior are actually patterns. And Artificial Neural Networks (ANN) are very good tool to train a system for known patterns and later can be used to identify unknown patterns. In this paper a two dimensional binary pattern matrix is formed on the basis of some questionnaires to identify different customer behavior. The matrix is further segmented row-wise and each row is presented to perceptron for training purpose of the ANN, which is used to complete the process of loan approval