台灣地區商業銀行因企業為邁向國際化，從事高桿槓財務操作，其融資動機不似以往單純。辦理企業授信倘仍依循專家經驗主觀判斷，對企業營運及財務異常現象將無法即時掌握。為此，本研究利用Altman（1968）的Z-Score信用評分及KMV選擇權模型作為衡量信用風險評估工具。惟本研究在KMV模型之違約點細分為違約點1=公司負債總額;違約點2=公司短期負債;違約點3=公司短期負債+1/2長期負債，分別求出預期違約機率，作為兩模型在財務危機企業預測之比較。 實證對象選自2000年至2005年73家發生財務危機上市、上櫃公司，並以1:1配對方式選取同產業、主力產品之正常公司。採用logistic迴歸及檢定力曲線為檢驗模型。實證發現，KMV模型對財務危機預測能力顯著優於信用評分法，可有效提供簡速、科學且公正客觀之審核標準，作為本地商銀另項信用風險評估模型之選擇。 Since many corporations in Taiwan operate higher financial leverage to become globalizing enterprises, the purposes of applying loan aren’t as simple as before. If banks approve corporation loans based on specialists’ experience, they will unable to detect the credit risk of these companies in time. Therefore, this paper applied two models to measure the credit risk: “ Altman’s Z-Score （credit scoring）and KMV option model（option pricing）.” However, we defined the default point as point 1= the total debts; point 2= the short term debts and point 3= the short term debts +1/2 the long term debts to individually figure out the Expected Default Frequency . Using the data from 73 financial distressed Taiwan’s listed companies from 2000 to 2005, and used the 1:1 matching sample method to select data from similar companies to contrast. Then, we adopted two major comparative laws: logistic regression and power curve. The empirical results of two kinds of comparative methods all get the same conclusion that KMV option model is significantly better than Z-score. Moreover, it can provide a concise, scientific and objective verifying standard as another model to measure and manage the credit risk for banks in Taiwan.
