Research Article | OPEN ACCESS
Design and Explanation of the Credit Ratings of Customers Model Using Neural Networks
Sahar Amanati
Department of Business and Administration, Free Professional Training Center,
Allameh Tabataba
Research Journal of Applied Sciences, Engineering and Technology 2014 24:5179-5183
Received: February 11, 2014 | Accepted: May 04, 2014 | Published: June 25, 2014
Abstract
The aim of this study formed with purpose of providing a suitable model to investigate the credit behavior of consumer of speculation loan using neural networks for credit ratings. Nowadays, intelligent systems found many applications in different fields of banking and financing. One of main application of neural networks is review and approval of credits. Thus, at first factors affecting credit behavior of consumer was identified and then, consumers divided in three categories: on-time payer (good payer), bad payer and overdue (belated) payer. In the next step, neural network models designed using the training data was instructed and then tested with these experimental data. The results show that the credit behavior of the customers could be predicted using neural networks ranking models.
Keywords:
Credit ranking, facilities, neural network,
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Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Copyright
The authors have no competing interests.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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