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Modeling Credit Risk: An Application of the Rough Set Methodology

The Basel Accords encourages credit entities to implement their own models for measuring financial risk. In this paper, we focus on the use of internal ratings-based (IRB) models for the assessment of credit risk and, specifically, on one component that models the probability of default (PD). The tr...

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Main Authors: Medina, Reyes Samaniego, Cueto, Maria Jose Vazquez
Format: Article
Published: Universiti Utara Malaysia Press 2013
Subjects:
HG Finance
Online Access:http://repo.uum.edu.my/24987/
http://ijbf.uum.edu.my/index.php/previous-issues/149-the-international-journal-of-banking-and-finance-ijbf-vol-10-no-1-march-2013
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spelling my.uum.repo.249872018-10-25T00:20:46Z http://repo.uum.edu.my/24987/ Modeling Credit Risk: An Application of the Rough Set Methodology Medina, Reyes Samaniego Cueto, Maria Jose Vazquez HG Finance The Basel Accords encourages credit entities to implement their own models for measuring financial risk. In this paper, we focus on the use of internal ratings-based (IRB) models for the assessment of credit risk and, specifically, on one component that models the probability of default (PD). The traditional methods used for modelling credit risk, such as discriminant analysis and logit and probit models, start with several statistical restrictions. The rough set methodology avoids these limitations and as such is an alternative to the classic statistical methods. We apply the rough set methodology to a database of 106 companies that are applicants for credit. We obtain ratios that can best discriminate between financially sound and bankrupt companies, along with a series of decision rules that will help detect operations that are potentially in default. Finally, we compare the results obtained using the rough set methodology to those obtained using classic discriminant analysis and logit models. We conclude that the rough set methodology presents better risk classification results. Universiti Utara Malaysia Press 2013 Article PeerReviewed Medina, Reyes Samaniego and Cueto, Maria Jose Vazquez (2013) Modeling Credit Risk: An Application of the Rough Set Methodology. The International Journal of Banking and Finance, 10 (1). pp. 34-56. ISSN 1675-7227 http://ijbf.uum.edu.my/index.php/previous-issues/149-the-international-journal-of-banking-and-finance-ijbf-vol-10-no-1-march-2013
institution Universiti Utara Malaysia
building UUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Utara Malaysia
content_source UUM Institutionali Repository
url_provider http://repo.uum.edu.my/
topic HG Finance
spellingShingle HG Finance
Medina, Reyes Samaniego
Cueto, Maria Jose Vazquez
Modeling Credit Risk: An Application of the Rough Set Methodology
description The Basel Accords encourages credit entities to implement their own models for measuring financial risk. In this paper, we focus on the use of internal ratings-based (IRB) models for the assessment of credit risk and, specifically, on one component that models the probability of default (PD). The traditional methods used for modelling credit risk, such as discriminant analysis and logit and probit models, start with several statistical restrictions. The rough set methodology avoids these limitations and as such is an alternative to the classic statistical methods. We apply the rough set methodology to a database of 106 companies that are applicants for credit. We obtain ratios that can best discriminate between financially sound and bankrupt companies, along with a series of decision rules that will help detect operations that are potentially in default. Finally, we compare the results obtained using the rough set methodology to those obtained using classic discriminant analysis and logit models. We conclude that the rough set methodology presents better risk classification results.
format Article
author Medina, Reyes Samaniego
Cueto, Maria Jose Vazquez
author_facet Medina, Reyes Samaniego
Cueto, Maria Jose Vazquez
author_sort Medina, Reyes Samaniego
title Modeling Credit Risk: An Application of the Rough Set Methodology
title_short Modeling Credit Risk: An Application of the Rough Set Methodology
title_full Modeling Credit Risk: An Application of the Rough Set Methodology
title_fullStr Modeling Credit Risk: An Application of the Rough Set Methodology
title_full_unstemmed Modeling Credit Risk: An Application of the Rough Set Methodology
title_sort modeling credit risk: an application of the rough set methodology
publisher Universiti Utara Malaysia Press
publishDate 2013
url http://repo.uum.edu.my/24987/
http://ijbf.uum.edu.my/index.php/previous-issues/149-the-international-journal-of-banking-and-finance-ijbf-vol-10-no-1-march-2013
_version_ 1644284195345793024
score 13.211869

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