隨著商業活動的蓬勃發展、國際間貿易往來頻繁, 銀行所提供的服務及金融商品, 亦順應這些需求不斷增加, 其所扮演的角色及涵蓋的產業已非昔日可比擬; 若是金融產業遭受到衝擊、面臨危機, 很可能會對整個經濟體造成嚴重影響; 因此, 本文將探討何種解釋變數對於銀行營運發生狀況時, 有較佳的解釋能力。文中所選取的解釋變數主要有兩種: 其一來自於常被業界用來分析公司狀況的Altman Z-scores 模型, 本文將採用Altman 對於非 製造業所歸納出的四種財會比率變數, 另一種變數為KMV 模型利用Black and Scholes選擇權評價公式所導的違約距離(distance to default)。於過去的論文, 此兩種模型都常被探討其對公司發生危機時是否具解釋能力, 但於兩者間之比較則少有著墨; 故本文利用2000至2008年台灣的17間上市銀行為樣本, 於Logit 迴歸模型下, 同時以Altman Zscores模型的財會比率變數和KMV 模型的違約距離為解釋變數, 探討何者對於公司的營運狀況發生問題時, 有較佳的解釋能力。實證結果發現, 違約距離對於銀行營運變差的情況, 有較佳且顯著的解釋能力, 故透過檢視違約距離的高低, 將有助於銀行產業及早發現其營運之問題, 以避免情況惡化, 釀成更大的危機。 / As highly development in commercial activities and international trade become more frequently, the role of banks has become much more important than before. If banks are influenced by shocks, the whole economy might encounter serious financial crisis. Therefore, this research aims to discover what variable will have better explanatory power for banks’ operating situation. In the thesis, two kinds of explanatory variables are selected: one is based on the financial accounting ratios from Altman Z-scores model, and the other is distance to default which is derived from Black and Scholes’ option pricing formula. In prior thesis, both types of model have been usually discussed about their individual explanatory power to corporate default risk, but there are few papers comparing them and finding which one is better. Hence, this research takes 17 banks in Taiwan from 2000 to 2008 as samples, and puts them in the same Logit model to find which type of variables has better explanatory power for bank’s operating situation. According to the empirical result, distance to default would perform better than financial accounting ratios, so supervising the distance to default of banks will be useful for banks to find if there are problems in its operation and prevent it from becoming a big trouble in advance.