本研究係以國內某家S銀行個人房屋貸款客戶作為研究對象，分析探討其逾期放款違約發生之原因。並以該家銀行自民國91年至100年貸放之個人房屋貸款案件中，抽取正常戶600件、違約戶200件，共800件作為樣本，採用Logistic迴歸分析，以了解房屋貸款違約風險的主要影響因素。
由實證結果顯示，在性別、年齡、婚姻、教育程度、職業別、年所得、銀行總借款、月支出/月收入(此後簡稱D/I比)、及貸款型態等9個影響房屋貸款信用風險之變數中，教育程度、職業別與違約風險呈負相關；而年齡、銀行總借款、D/I比則與違約風險呈正相關；其餘各變數與違約風險間並無顯著關係；若以年所得、銀行總借款兩個變數來探討對違約風險之影響程度，實證結果顯示，年所得對違約風險有顯著負相關，銀行總借款對違約風險有顯著正相關；以年所得、D/I比兩個變數探討對違約風險之影響程度，實證結果顯示，年所得對違約風險有顯著負相關，D/I比對違約風險有顯著正相關；以銀行總借款、D/I比兩個變數探討對違約風險之影響程度，實證結果顯示，銀行總借款對違約風險並無顯著關係，而D/I比對違約風險則有顯著負相關；最後以年所得、銀行總借款、D/I比等三個變數探討對違約風險之影響程度，實證結果顯示，年所得對違約風險有顯著負相關，而銀行總借款、以及D/I比對違約風險則有顯著正相關。
最後，本論文乃建議銀行業者可依據房屋貸款者本身之經濟條件如年所得、銀行總借款、及D/I比等三個變數對違約風險間之影響程度建構一組羅吉斯迴歸模型，用來預先評估房屋貸款申請者未來可能發生違約風險之機率，做為銀行授予房貸准駁之參考。

This research uses a national bank S’s personal home mortgages as the research target. It analyzes reasons for default on non-performing loans to delinquent. In addition, out of this bank’s approved personal home mortgage applications from year 2002 to 2011, 600 normal applications and 200 default applications are extracted. It adopts Logistic regression analysis in order to understand the major influential factors of the default risk of home mortgages.
According to the empirical results based on the nine influential variables (including sex, age, marriage, education level, career type, annual income, bank’s total loan, monthly expense over the monthly income ratio (hereinafter abbreviated as D/I), and loan type), it shows that education level, career type, and default risk are negatively correlated. However, age, bank’s total loan, D/I ratio and default risk are positively correlated; other remaining variables have no significant correlations with default risk. Finally, if it uses three variables such as annual income, bank’s total loan, and D/I ratio to discuss the default risk’s influential level, annual income would have a significant and negative correlation with default risk, whilst bank’s total loan and D/I ratio have a significant and positive correlation with default risk. Hence, this paper suggests that bankers can use these three variables’ influential level to default risk and construct a set of Logistic Regression Analysis; then use to evaluate and predict home mortgages applicants’ future default risk’s probability as a reference for banks to set criteria to grant home mortgages.

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網路部份:
http://pip.moi.gov.tw/V2/E/SCRE0101.aspx
http://www.banking.gov.tw/ch/index.jsp
http://www.cbc.gov.tw/np.asp?ctNode=305&mp=1
http://www.dgbas.gov.tw/mp.asp?mp=1