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Loan Customer Analysis System using Column-wise Segmentation of Behavioural Matrix (CSBM)

Rakesh Kumar Mandal1 , N R Manna2

Section:Research Paper, Product Type: Conference Paper
Volume-03 , Issue-01 , Page no. 18-22, Feb-2015

Online published on Feb 18, 2015

Copyright © Rakesh Kumar Mandal , N R Manna . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Rakesh Kumar Mandal , N R Manna, “Loan Customer Analysis System using Column-wise Segmentation of Behavioural Matrix (CSBM),” International Journal of Computer Sciences and Engineering, Vol.03, Issue.01, pp.18-22, 2015.

MLA Style Citation: Rakesh Kumar Mandal , N R Manna "Loan Customer Analysis System using Column-wise Segmentation of Behavioural Matrix (CSBM)." International Journal of Computer Sciences and Engineering 03.01 (2015): 18-22.

APA Style Citation: Rakesh Kumar Mandal , N R Manna, (2015). Loan Customer Analysis System using Column-wise Segmentation of Behavioural Matrix (CSBM). International Journal of Computer Sciences and Engineering, 03(01), 18-22.

BibTex Style Citation:
@article{Mandal_2015,
author = {Rakesh Kumar Mandal , N R Manna},
title = {Loan Customer Analysis System using Column-wise Segmentation of Behavioural Matrix (CSBM)},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {2 2015},
volume = {03},
Issue = {01},
month = {2},
year = {2015},
issn = {2347-2693},
pages = {18-22},
url = {https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=3},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=3
TI - Loan Customer Analysis System using Column-wise Segmentation of Behavioural Matrix (CSBM)
T2 - International Journal of Computer Sciences and Engineering
AU - Rakesh Kumar Mandal , N R Manna
PY - 2015
DA - 2015/02/18
PB - IJCSE, Indore, INDIA
SP - 18-22
IS - 01
VL - 03
SN - 2347-2693
ER -

           

Abstract

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.

Key-Words / Index Term

Loan, Customer, ANN, Column-wise Segmentation, Perceptron, Behavioural Pattern

References

[1] Rakesh Kumar Mandal and N R Manna, "Hand Written English Character Recognition using Column-wise Segmentation of Image Matrix (CSIM)", WSEAS Transactions on Computers, Volume 11, Issue 5, May 2012.
[2] G.N. Swamy, G. Vijay Kumar, "Neural Networks", Scitech, India, 2007.
[3] L. Fausett, "Fundamentals of Neural Networks, Architectures, Algorithms and Applications", Pearson Education, India, 2009.
[4] Apash Roy and N R Manna,"Character Recognition using Competitive Neural Network with Multi-scale training", UGC Sponsor National Symposium on Emerging Trends In Computer Science (ETCS 2012) on 20-21 January 2012, pp 17-20.
[5] Apash Roy and N R Manna, "Competitive Neural Network as applied for Character Recognition " - International Journal of advanced research in Computer science and Software Engineering, Volume 2, Issue 3, 2012, pp 06-10.
[6] V Moonasar, Credit Risk Analysis using Artificial Intelligence: Evidence from a Leading South African Banking Institution. Available: www.academia.edu/502093/credit_risk_analysis_using_artificial_intelligence_evidence_from_a_leading_South_African_banking_institution.
[7] Ifeyinwa Ajah, Chibueze Inyiama, Loan Fraud Detection And IT-Based Combat Strategies, Journal of Internet Banking and Commerce, 2011, Vol. 16 No. 2, pp 1-13. Avialable at: www.arraydev.com/commerce/JIBC/2011_08/Ajah.pdf