Credit evaluation model of loan proposals for Indian Banks

Author

Purohit, Seema ; Kulkarni, Anjali

Author_Institution

Navinchandra Mehta Inst. of Technol. & Dev., Mumbai, India

fYear

2011

fDate

11-14 Dec. 2011

Firstpage

868

Lastpage

873

Abstract

The failure and success of the Banking Industry depends largely on industry´s ability to properly evaluate credit risk. Credit Evaluation of any potential credit application has remained a challenge for Banks all over the world till today. This paper checks the applicability of one of the new integrated model on a sample data taken from Indian Banks. The integrated model is a combination model based on the techniques of Logistic Regression, Multilayer Perceptron Model, Radial Basis Neural Network, Support Vector Machine and Decision tree (C4.5) and compares the effectiveness of these techniques for credit approval process.

Keywords

banking; decision trees; multilayer perceptrons; radial basis function networks; regression analysis; support vector machines; Indian banks; banking industry; credit evaluation model; decision tree; loan proposals; logistic regression; multilayer perceptron model; potential credit application; radial basis neural network; support vector machine; Data models; Decision trees; Logistics; Multilayer perceptrons; Support vector machines; Training; Credit Evaluation; Decision Process; Decision Tree; Integrated model; Logistic Regression; Multilayer Perceptron Model; Radial Basis Neural Network; SVM;

fLanguage

English

Publisher

ieee

Conference_Titel

Information and Communication Technologies (WICT), 2011 World Congress on

Conference_Location

Mumbai

Print_ISBN

978-1-4673-0127-5

Type

conf

DOI

10.1109/WICT.2011.6141362

Filename

6141362