Credit scoring models using soft computing methods: A survey

During the last fifteen years, soft computing methods have been successfully applied in building powerful and flexible credit scoring models and have been suggested to be a possible alternative to statistical methods. In this survey, the main soft computing methods applied in credit scoring models a...

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Main Authors: Lahsasna, A., Ainon, R.N., Teh, Y.W.
Format: Article
Published: 2010
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Online Access:http://eprints.um.edu.my/14891/
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Institution: Universiti Malaya
id my.um.eprints.14891
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spelling my.um.eprints.148912015-11-25T07:11:28Z http://eprints.um.edu.my/14891/ Credit scoring models using soft computing methods: A survey Lahsasna, A. Ainon, R.N. Teh, Y.W. T Technology (General) During the last fifteen years, soft computing methods have been successfully applied in building powerful and flexible credit scoring models and have been suggested to be a possible alternative to statistical methods. In this survey, the main soft computing methods applied in credit scoring models are presented and the advantages as well as the limitations of each method are outlined. The main modelling issues are discussed especially from the data mining point of view. The study concludes with a series of suggestions of other methods to be investigated for credit scoring modelling. 2010 Article PeerReviewed Lahsasna, A. and Ainon, R.N. and Teh, Y.W. (2010) Credit scoring models using soft computing methods: A survey. International Arab Journal of Information Technology, 7 (2). pp. 115-123.
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic T Technology (General)
spellingShingle T Technology (General)
Lahsasna, A.
Ainon, R.N.
Teh, Y.W.
Credit scoring models using soft computing methods: A survey
description During the last fifteen years, soft computing methods have been successfully applied in building powerful and flexible credit scoring models and have been suggested to be a possible alternative to statistical methods. In this survey, the main soft computing methods applied in credit scoring models are presented and the advantages as well as the limitations of each method are outlined. The main modelling issues are discussed especially from the data mining point of view. The study concludes with a series of suggestions of other methods to be investigated for credit scoring modelling.
format Article
author Lahsasna, A.
Ainon, R.N.
Teh, Y.W.
author_facet Lahsasna, A.
Ainon, R.N.
Teh, Y.W.
author_sort Lahsasna, A.
title Credit scoring models using soft computing methods: A survey
title_short Credit scoring models using soft computing methods: A survey
title_full Credit scoring models using soft computing methods: A survey
title_fullStr Credit scoring models using soft computing methods: A survey
title_full_unstemmed Credit scoring models using soft computing methods: A survey
title_sort credit scoring models using soft computing methods: a survey
publishDate 2010
url http://eprints.um.edu.my/14891/
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