Application of Artificial Intelligent in the Prediction of Credit Rating of Banks Customers (in Persian)
Mahdieh Akhbari and
Mohammad Akhbari
Additional contact information
Mahdieh Akhbari: Iran
Mohammad Akhbari: Iran
Journal of Monetary and Banking Research (فصلنامه پژوهشهای پولی-بانکی), 2010, vol. 2, issue 3, 157-182
Abstract:
This study examines a multi-objective fuzzy simplex-genetic algorithm being developed to predict the financial performance of legal customers of banks. Predicting the performance produced by the model was examined based on its ability to accurately identify credit default. Using available data from Keshavarzi bank for the period between 2001-2006¡ debt ratio¡ operational ratio¡ and return on equity were selected as descriptive variables¡ and on the other side¡ dependent variable was considered as a dummy variable. In order to train and validate the model¡ data were divided into two sets¡ model (in-sample) and test (out-of-sample). After running the algorithm¡ regardless the sensitivity and specificity ratios¡ the key variable were specified.
Keywords: Fuzzy Inference Systems; Simplex Algorithm; Genetic Algorithm Credit Rating (search for similar items in EconPapers)
Date: 2010
References: Add references at CitEc
Citations:
Downloads: (external link)
http://jmbr.mbri.ac.ir/article-1-41-en.pdf (application/pdf)
http://jmbr.mbri.ac.ir/article-1-41-en.html (text/html)
http://jmbr.mbri.ac.ir/article-1-41-fa.html (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:mbr:jmbres:v:2:y:2010:i:3:p:157-182
Access Statistics for this article
More articles in Journal of Monetary and Banking Research (فصلنامه پژوهشهای پولی-بانکی) from Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran Contact information at EDIRC.
Bibliographic data for series maintained by M. E. ().