SME CREDIT SCORING AND THE DETERMINANTS OF CREDIT QUALITY -A CASE STUDY OF C COMMERCIAL BANK
碩士 === 元智大學 === 管理研究所 === 96 === As the opening of the banking industry happens during these years, many banks start to compete in the SEM business. However, SME financial information inconsistency and short business life cycle are typical problems faced by the banks. As a result, risk control has b...
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ndltd-TW-096YZU054570372015-10-13T13:48:21Z http://ndltd.ncl.edu.tw/handle/85096427028985771473 SME CREDIT SCORING AND THE DETERMINANTS OF CREDIT QUALITY -A CASE STUDY OF C COMMERCIAL BANK 中小企業授信信用評分表與授信品質之因素探討-以C商業銀行為例 Yu-Huei Tseng 曾郁惠 碩士 元智大學 管理研究所 96 As the opening of the banking industry happens during these years, many banks start to compete in the SEM business. However, SME financial information inconsistency and short business life cycle are typical problems faced by the banks. As a result, risk control has become am important issue for SME credit business. SME credit scoring, the threshold for SME credit business is studied in this research. Understanding the relationship between scoring variants and the credit quality helps to understand if the scoring table provides useful information for credit approval. Logistic Regression is applied to understand which variant is significant to credit quality. As a result, there are 6 significant variants. Although not every variant is significant in this research, but these variants are still valuable for credit approval references. Ja-Shen Chen 陳家祥 2008 學位論文 ; thesis 66 zh-TW |
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碩士 === 元智大學 === 管理研究所 === 96 === As the opening of the banking industry happens during these years, many banks start to compete in the SEM business. However, SME financial information inconsistency and short business life cycle are typical problems faced by the banks. As a result, risk control has become am important issue for SME credit business. SME credit scoring, the threshold for SME credit business is studied in this research. Understanding the relationship between scoring variants and the credit quality helps to understand if the scoring table provides useful information for credit approval.
Logistic Regression is applied to understand which variant is significant to credit quality. As a result, there are 6 significant variants. Although not every variant is significant in this research, but these variants are still valuable for credit approval references.
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author2 |
Ja-Shen Chen |
author_facet |
Ja-Shen Chen Yu-Huei Tseng 曾郁惠 |
author |
Yu-Huei Tseng 曾郁惠 |
spellingShingle |
Yu-Huei Tseng 曾郁惠 SME CREDIT SCORING AND THE DETERMINANTS OF CREDIT QUALITY -A CASE STUDY OF C COMMERCIAL BANK |
author_sort |
Yu-Huei Tseng |
title |
SME CREDIT SCORING AND THE DETERMINANTS OF CREDIT QUALITY -A CASE STUDY OF C COMMERCIAL BANK |
title_short |
SME CREDIT SCORING AND THE DETERMINANTS OF CREDIT QUALITY -A CASE STUDY OF C COMMERCIAL BANK |
title_full |
SME CREDIT SCORING AND THE DETERMINANTS OF CREDIT QUALITY -A CASE STUDY OF C COMMERCIAL BANK |
title_fullStr |
SME CREDIT SCORING AND THE DETERMINANTS OF CREDIT QUALITY -A CASE STUDY OF C COMMERCIAL BANK |
title_full_unstemmed |
SME CREDIT SCORING AND THE DETERMINANTS OF CREDIT QUALITY -A CASE STUDY OF C COMMERCIAL BANK |
title_sort |
sme credit scoring and the determinants of credit quality -a case study of c commercial bank |
publishDate |
2008 |
url |
http://ndltd.ncl.edu.tw/handle/85096427028985771473 |
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