Credit Risk Models for Consumer Banking
碩士 === 元智大學 === 資訊管理學系 === 94 === Recently, the business focus of banking industry has been shifting from corporate banking to consumer banking because of the high profit and high interest spread. Due to the relatively small market scale, the consumer banking business is indeed a highly competitive...
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ndltd-TW-094YZU053960592016-06-01T04:15:08Z http://ndltd.ncl.edu.tw/handle/53073591460116383963 Credit Risk Models for Consumer Banking 銀行業消費金融信用風險模型之建置 Ju-Chen Cheng 鄭如珍 碩士 元智大學 資訊管理學系 94 Recently, the business focus of banking industry has been shifting from corporate banking to consumer banking because of the high profit and high interest spread. Due to the relatively small market scale, the consumer banking business is indeed a highly competitive business in Taiwan. From the risk management’s point of view, the purpose of this research is to build up a credit risks model for consumer banking. By building the model, the bank could evaluate the underlying risk exposures on its consumer banking business so as to come out strategies to decrease the probabilities of bad accounts and reduce the operating costs, eventually, to maximize the profits. In the thesis, we first collect customer information and their transaction records to form a research database. Several algorithms, known as data mining techniques, are applied to build up the credit risk models. The algorithms are CART, Back-propagation Neural Network, Logistic Regression and K-Mean Clustering. The critical success factors for building up a reliable and robust model are discussed in this thesis as well. Yi-Chuan Lu 盧以詮 2006 學位論文 ; thesis 62 zh-TW |
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碩士 === 元智大學 === 資訊管理學系 === 94 === Recently, the business focus of banking industry has been shifting from corporate banking to consumer banking because of the high profit and high interest spread. Due to the relatively small market scale, the consumer banking business is indeed a highly competitive business in Taiwan. From the risk management’s point of view, the purpose of this research is to build up a credit risks model for consumer banking. By building the model, the bank could evaluate the underlying risk exposures on its consumer banking business so as to come out strategies to decrease the probabilities of bad accounts and reduce the operating costs, eventually, to maximize the profits. In the thesis, we first collect customer information and their transaction records to form a research database. Several algorithms, known as data mining techniques, are applied to build up the credit risk models. The algorithms are CART, Back-propagation Neural Network, Logistic Regression and K-Mean Clustering. The critical success factors for building up a reliable and robust model are discussed in this thesis as well.
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Yi-Chuan Lu |
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Yi-Chuan Lu Ju-Chen Cheng 鄭如珍 |
author |
Ju-Chen Cheng 鄭如珍 |
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Ju-Chen Cheng 鄭如珍 Credit Risk Models for Consumer Banking |
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Ju-Chen Cheng |
title |
Credit Risk Models for Consumer Banking |
title_short |
Credit Risk Models for Consumer Banking |
title_full |
Credit Risk Models for Consumer Banking |
title_fullStr |
Credit Risk Models for Consumer Banking |
title_full_unstemmed |
Credit Risk Models for Consumer Banking |
title_sort |
credit risk models for consumer banking |
publishDate |
2006 |
url |
http://ndltd.ncl.edu.tw/handle/53073591460116383963 |
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