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題名 Construction of Classification Models for Credit Policies in Banks
作者 Shih, Kuang-Hsun ; Hung, Hsu-Feng ; Lin, Binshan
貢獻者 企管系
關鍵詞 credit policies; financial operation; classification models; decision support systems; DSS; bank credit ratings; multiple discriminate analysis; MDA; rough set theory; RST; customer relationship management; banking CRM
日期 2010.01
上傳時間 26-Feb-2014 13:49:22 (UTC+8)
摘要 The execution and outcome of credit rating policies of banks are highly relevant to banks` decisions in investments, loans, and their measurement of default risks. They also have impacts on capital flows and utilisation of corporate borrowers. Therefore, it is essential to establish a scientific, objective, and accurate model of credit ratings for Customer Relationship Management (CRM) of the banking industry. The correct results of customers` ratings can serve as an important reference in the CRM of banks. This paper applies two classification methods, Multiple Discriminate Analysis (MDA) and Rough Set Theory (RST), to analyse and compare a total of 70 entries of corporate credit data. The result shows that the RST classification model boasts better classifying effects and is suitable for the analysis of credit ratings in the banking industry. This paper also suggests that a decision support system should be established with a scientific classification model in order to assist in the decisions and judgements of decision makers.
關聯 International Journal of Electronic Finance, 4(1), 1-18
資料類型 article
dc.contributor 企管系en_US
dc.creator (作者) Shih, Kuang-Hsun ; Hung, Hsu-Feng ; Lin, Binshanen_US
dc.date (日期) 2010.01en_US
dc.date.accessioned 26-Feb-2014 13:49:22 (UTC+8)-
dc.date.available 26-Feb-2014 13:49:22 (UTC+8)-
dc.date.issued (上傳時間) 26-Feb-2014 13:49:22 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/64211-
dc.description.abstract (摘要) The execution and outcome of credit rating policies of banks are highly relevant to banks` decisions in investments, loans, and their measurement of default risks. They also have impacts on capital flows and utilisation of corporate borrowers. Therefore, it is essential to establish a scientific, objective, and accurate model of credit ratings for Customer Relationship Management (CRM) of the banking industry. The correct results of customers` ratings can serve as an important reference in the CRM of banks. This paper applies two classification methods, Multiple Discriminate Analysis (MDA) and Rough Set Theory (RST), to analyse and compare a total of 70 entries of corporate credit data. The result shows that the RST classification model boasts better classifying effects and is suitable for the analysis of credit ratings in the banking industry. This paper also suggests that a decision support system should be established with a scientific classification model in order to assist in the decisions and judgements of decision makers.en_US
dc.format.extent 123 bytes-
dc.format.mimetype text/html-
dc.language.iso en_US-
dc.relation (關聯) International Journal of Electronic Finance, 4(1), 1-18en_US
dc.subject (關鍵詞) credit policies; financial operation; classification models; decision support systems; DSS; bank credit ratings; multiple discriminate analysis; MDA; rough set theory; RST; customer relationship management; banking CRMen_US
dc.title (題名) Construction of Classification Models for Credit Policies in Banksen_US
dc.type (資料類型) articleen