DESIGNING AND FORMULATING EFFICIENT MODEL FOR CREDIT ALLOCATION MODEL- NEURAL NETWORK,
LOGISTIC AND LINEAR REGRESSION APPROACH

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MANSORY A.; AZAR A.

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: MODARRES HUMAN SCIENCES Year:2002 | Volume:6 | Issue:3(Tome 26) Page(s): 125-146

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Information Journal Paper

Title

DESIGNING AND FORMULATING EFFICIENT MODEL FOR CREDIT ALLOCATION MODEL- NEURAL NETWORK, LOGISTIC AND LINEAR REGRESSION APPROACH

Author(s)

MANSORY A. | AZAR A. | Issue Writer Certificate

Keywords

NEURAL NETWORKQ4

LOGISTIC REGRESSIONQ4

LINEAR REGRESSIONQ4

CREDIT ALLOCATIONQ4

Abstract

The main objective of all commercial banks is to collect the savings of legal and real persons and allocate them as credit to industrial, services and different priduction Companies. With respect to the importance of allocating credit to the companies having the necessary conditions, many models are presented for the evaluation of their credit risk. But many of these models are classic and the capacity of the company is not considered in the evaluation. In this paper we evaluate the credit risk and capacity of all companies and institutions are simultaneously analysed with using neural network model and some independent variables. For this purpose, we used the multilayer perception, linear and LOGISTIC REGRESSION models. The outcome of the model demonstrates that NEURAL NETWORK and logistic regression models have the same ability in predicting credit risk but the NEURAL NETWORK is very powerful in predicting the credit capacity of customers.

Cites

USING FUZZY ANALYTIC HIERARCHY PROCESS AND HYBRID OF HIGHER ORDER NEURAL NETWORK FOR EVALUATION CREDIT RISK OF CORPORATE

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APA: Copy

MANSORY, A., & AZAR, A.. (2002). DESIGNING AND FORMULATING EFFICIENT MODEL FOR CREDIT ALLOCATION MODEL- NEURAL NETWORK, LOGISTIC AND LINEAR REGRESSION APPROACH. MODARRES HUMAN SCIENCES, 6(3(Tome 26)), 125-146. SID. https://sid.ir/paper/7030/en

Vancouver: Copy

MANSORY A., AZAR A.. DESIGNING AND FORMULATING EFFICIENT MODEL FOR CREDIT ALLOCATION MODEL- NEURAL NETWORK, LOGISTIC AND LINEAR REGRESSION APPROACH. MODARRES HUMAN SCIENCES[Internet]. 2002;6(3(Tome 26)):125-146. Available from: https://sid.ir/paper/7030/en

IEEE: Copy

A. MANSORY, and A. AZAR, “DESIGNING AND FORMULATING EFFICIENT MODEL FOR CREDIT ALLOCATION MODEL- NEURAL NETWORK, LOGISTIC AND LINEAR REGRESSION APPROACH,” MODARRES HUMAN SCIENCES, vol. 6, no. 3(Tome 26), pp. 125–146, 2002, [Online]. Available: https://sid.ir/paper/7030/en

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