由於目前的經濟體制是自負風險的，若是一個企業發生財務上的危機，將會影響到企業本身、員工、往來的廠商、股東、債權人、甚至是整個社會，因此若是可以事先偵測到財務可能發生的危機，對每個層面都是有益的。每一種模型的提供都是為了能避免遭受損失，甚至能提早發現可能出現的失敗。因此本論文主要是利用財務比率的資訊，去衡量企業的財務危機，而期望能達到一個預警的目的。

本論文以區別分析法、SVM(Support Vector Machine)、BSVR(Bayesian Support Vector Regression)做為研究的模型。以財務危機發生前一年的財務比率做為選取的變數，利用不同的選取方法，我們選取出4組變數。以發生財務危機前一年的20筆正常公司與20筆財務危機公司為訓練樣本，10筆正常公司與10筆危機公司為測試樣本。

得到的結論為: 分別比較4組變數在區別分析模型下的表現，可以看出4組變數在變異數相等的模型下，至少有3組變數的預測正確率是理想的。在SVM模型中，可以看到4組變數在經過尺度化和給定參數 =1， =1/40後，有3組的正確率都可以達到95%以上。在BSVR模型中，可以看到變數的選擇對模型的預測能力是很重要的。

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