Neurofuzzy Application in Creditworthiness Evaluation

碩士 === 朝陽科技大學 === 財務金融系碩士班 === 90 === Abract This paper applies Neurofuzzy in creditworthiness evaluation. the purposes are: (1) Neurofuzzy is employed to develop creditworthiness evaluation. (2) This study conducts the difference of credit rating results between bank and TCRI. (3) 80 business len...

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Main Authors: Sheng-Chun Chang, 張勝春
Other Authors: Kuen-Hwang Hwang
Format: Others
Language:zh-TW
Published: 2002
Online Access:http://ndltd.ncl.edu.tw/handle/26982283722193487013
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spelling ndltd-TW-090CYIT53040372015-10-13T15:01:28Z http://ndltd.ncl.edu.tw/handle/26982283722193487013 Neurofuzzy Application in Creditworthiness Evaluation 模糊類神經在銀行授信決策之應用 Sheng-Chun Chang 張勝春 碩士 朝陽科技大學 財務金融系碩士班 90 Abract This paper applies Neurofuzzy in creditworthiness evaluation. the purposes are: (1) Neurofuzzy is employed to develop creditworthiness evaluation. (2) This study conducts the difference of credit rating results between bank and TCRI. (3) 80 business lending cases at one branch of commercial bank at central Taiwan were employed to evaluate the performance of credit rating models in bank and TCRI. The empricial results show that(1)the creditworthiness evaluation of bank can be improve by applying Neurofuzzy. (2) TCRI may need adjusting in response to creditworthiness evaluation. (3)Nuerofuzzy can not support the identification of finance distress cases such few cases were employed. to improve the identify ability ,large data is necessary in learning phase for Nurofuzzy. Kuen-Hwang Hwang 黃焜煌 2002 學位論文 ; thesis 79 zh-TW
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language zh-TW
format Others
sources NDLTD
description 碩士 === 朝陽科技大學 === 財務金融系碩士班 === 90 === Abract This paper applies Neurofuzzy in creditworthiness evaluation. the purposes are: (1) Neurofuzzy is employed to develop creditworthiness evaluation. (2) This study conducts the difference of credit rating results between bank and TCRI. (3) 80 business lending cases at one branch of commercial bank at central Taiwan were employed to evaluate the performance of credit rating models in bank and TCRI. The empricial results show that(1)the creditworthiness evaluation of bank can be improve by applying Neurofuzzy. (2) TCRI may need adjusting in response to creditworthiness evaluation. (3)Nuerofuzzy can not support the identification of finance distress cases such few cases were employed. to improve the identify ability ,large data is necessary in learning phase for Nurofuzzy.
author2 Kuen-Hwang Hwang
author_facet Kuen-Hwang Hwang
Sheng-Chun Chang
張勝春
author Sheng-Chun Chang
張勝春
spellingShingle Sheng-Chun Chang
張勝春
Neurofuzzy Application in Creditworthiness Evaluation
author_sort Sheng-Chun Chang
title Neurofuzzy Application in Creditworthiness Evaluation
title_short Neurofuzzy Application in Creditworthiness Evaluation
title_full Neurofuzzy Application in Creditworthiness Evaluation
title_fullStr Neurofuzzy Application in Creditworthiness Evaluation
title_full_unstemmed Neurofuzzy Application in Creditworthiness Evaluation
title_sort neurofuzzy application in creditworthiness evaluation
publishDate 2002
url http://ndltd.ncl.edu.tw/handle/26982283722193487013
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