商業銀行如何檢視信用評等表之良窳; The Research of How to Perform the Credit Rating Assessment Forms and Evaluate Advantage on Commercial Banks

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題名:	商業銀行如何檢視信用評等表之良窳;The Research of How to Perform the Credit Rating Assessment Forms and Evaluate Advantage on Commercial Banks
作者:	王粹馨;Trai-Hsin Wang
貢獻者:	財務金融學系碩士在職專班
關鍵詞:	違約機率差幅;Logistic迴歸分析;信用評等表;credit rating assessment forms;differences exist between the breaching probabil;Logistic regression analysis
日期:	2003-07-07
上傳時間:	2009-09-22 14:43:07 (UTC+8)
出版者:	國立中央大學圖書館
摘要:	近年來因經濟不景氣等因素，造成國內銀行逾放比率過高，不少銀行開始檢討修改其信用評等方法及徵授信政策，本研究旨在針對國內某全國性商業銀行新舊信用評等表，對授信企業違約與正常之預警區別性及授信政策之運用面探討；以民國80年至90年為實證期間，研究對象為台灣北區及中區之混合行業（含大、中小企業），隨機抽樣選取個案銀行北部及中部各六家分行之違約公司(40戶)發生違約事件前三年及正常公司(115戶)相同年度之財務報表、信用評等表資料，以平均數差異分析及Logistic迴歸分析方法對樣本實證分析，以是否具有區別受評公司信用優劣能力，來評估新舊信用評等制度之良窳。實證分析結果顯示：經由平均數差異分析，新舊制信評制度對違約及正常公司均具區別力；以新舊制度違約及正常公司信評平均數與中位數差幅比較，實證顯示無法區分比較何者制度較佳；以信用要素違約機率差幅比較，以新制之中位數來檢測正常公司與違約公司之違約機率值差距最大，新制度較有顯著區別預測效果；但以構面違約機率差幅比較，舊制度較新制度有較大的差距，舊制度區別性較佳；新制「信用評等表」以平均數差異分析，無法區分大企業與中小企業品質，二者信評平均數均在52分~53分之間，平均數差異分析得出結果並不顯著。以Logit模型計算違約機率及「型一」及「型二」分類誤差，新制在變數及構面其違約機率之區別正確率較佳；「負債比率」、「長短期借款佔淨值比率」、「營業額」於新制有顯著性差異，可有效提供預警效能。 As a result of the economic slowdown in the recent years, domestic overdue loan ratio has elevated to new highs. Many banks have begun to consider adjusting their credit rating and lending policies. This research aims to explore the revisions of credit rating assessment forms, alarming mechanisms of corporate breach, and credit policy implementations of selected commercial banks. The research period spans from 1991 to 2001, sampling six banks in northern and middle Taiwan that extended credit facilities to large and medium-sized businesses within various industries in similar regions. The financial statements and credit rating assessments of 40 breaching companies three years before the breach were compared with that of 115 normal companies. Mean average deviation analysis and Logistic regression analysis were used to test the ability of the revised credit assessment methods used by selected banks as compared to the original methods. The result shows that, through mean average deviation analysis, both the revised and original credit assessment methods were able to distinguish between the normal and breaching companies. Superiority between the revised and original methods could not be distinguished from the scale of differences between the means and the medians. Under credit factors, revised method has a better forecasting efficiency than the original; largest differences exist between the breaching probability of the normal and breaching companies using the median test. However, structural comparisons indicated that large differences exist between both methods and the original method is superior. Revised “credit assessment form” could not distinguish the business qualities between large and medium-sized corporations. MAD analysis showed insignificant differences as the means for both lied between 52 and 53 points. Using Logit model to calculate breaching probabilities and Type I/Type II errors, the revised method showed better accuracy in distinguishing breaching probabilities. Revised method showed significant differences on “debt ratio”, “long/short term debt to equity ratio” and “sales”. It provided a more efficient alarming mechanism.
顯示於類別:	[財務金融學系碩士在職專班] 博碩士論文

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