鑑於以往房屋貸款授信風險評量模式，都採取問卷或隨機抽樣方式選取樣本資料，但為避免誤差產生，本研究採用國內承做房貸最多的銀行某分行2006年及2007年兩年期間，所有實際撥款的中長期房屋貸款案件，含中途清償銷戶案件共556件，全部作為研究對象。就銀行一般授信評估項目，包括貸款金額、貸款年數、貸款利率、性別、婚姻狀況、小孩數、教育程度、職業、年收入、貸收比、其他不動產、其他主從債務、有無動用循環信用等，再加上原住民等為研究變數，利用LR模式進行分析比較各變數對房屋貸款授信發生逾期的影響，以作為銀行貸款授信審核的參考。
本研究參與實證估計的14項變數中，僅貸款期限、借款人性別及是否有其他不動產等三項的結果顯示，對授信違約較不具影響；其餘包括貸款利率、教育程度、貸款與收入的比率、有無其他主從債務、原住民等顯著影響變數，及貸款金額、婚姻狀況、養育小孩數、職業、年收入、有無動用循環信用等重要相關變數。這些變數透過本研究實證估計其對逾期放款發生的影響程度後，銀行更能掌握借款人的條件及授信風險之所在；進而再一次確認其中的教育程度、貸收比、其他主從債務、職業、年收入、有無動用循環信用等項目，仍是銀行授信審核的重點，甚至應在授信風險評量的模式中加重這些項目的權值，以降低銀行授信的風險及避免逾期放款的發生。

In view of the previous mortgage credit risk assessment models, we have taken the questionnaire or random sampling selected sample data, but in order to avoid error generation. This study done for domestic bank loans up to a branch between 2006 and 2007 for two years, all cases of long-term housing loans actual allocations, including cases of cancellation repayment halfway, total 556 cases, All as research subjects, including the loan amount, number of years of the loan, the loan interest rate, gender, marital status, children number, education, occupation, income, loan-to-income ratio, other assets-real property, other main debt and from debt, the use of revolving credit etc., coupled with the aboriginal for the study variables, use LR model analysis to compare the influence of variables on housing loans in occurred overdue credit, as credit review reference in the bank loans.
14 variables of involved in the empirical estimation of this study, only in the term of the loan, the borrower gender , other assets-real property etc., and these three results show, for credit default less influential. including the remaining interest rate loans, education, loan-to-income ratio, other main debt and from debt, aboriginal etc., significant influence variables, and the loan amount, marital status, child-rearing, occupation, annual income, with or without the use of revolving credit, etc. variable., these variables through empirical estimate the extent of its impact on the occurrence of overdue loans. Banks better grasp of the borrower's condition and the risk of the borrower's credit. And then again to confirm where the level of education, loan-to-income ratio, other main debt and from debt, occupation, annual income, the use of revolving credit etc., Bank credit is still the focus of the audit, even heavier weight of these items in the credit risk assessment model, in order to reduce the risk of bank credit and avoid the occurrence of overdue loans.

一、中文部分
1、周俊賢(2003)，房貸信用評量分析，未出版碩士論文，國立高雄第一科技大學，高雄市。
2、周建福、于鴻福、陳進財（2004），銀行業房貸授信風險評估因素之選擇，中華管理評論—國際學報（Vol. 7, No. 2, Apr 2004）。
3、林哲輝（2007），房屋貸款授信評量模式之個案研究，未出版碩士論文，國立高雄第一科技大學，高雄市。
4、王梅雀（2008），銀行房屋貸款授信風險評估之研究，未出版碩士論文，國立嘉義大學，嘉義市。
5、高博祥（2008），我國銀行業房屋抵押貸款違約風險潛在因子之研究-以S銀行為例，國立高雄第一科技大學，高雄市。
6、蘇玉里（2010），房屋貸款授信風險因素之探討，未出版碩士論文，國立屏東商業技術學院，屏東縣。
7、趙秋玲（2011），銀行房貸授信風險控管之研究，未出版碩士論文，國立臺灣科技大學，台北市。
8、江國賢（2012），信用合作社逾期房貸因素之研究，未出版碩士論文，國立東華大學，花蓮縣。
9、楊謹鍹（2013），影響房屋貸款逾期因素之實證分析，未出版碩士論文，國立臺中科技大學，台中市。

二、英文部分
1、Gardner, M. J. and Mills, D. L. (1989), “Evaluating the Likelihood of Default on Delinquency Loans,” Financial Management, 18 (1), 55-63.
2、Lawrence, E. C., Smith, L.D. and Rhoades, M. (1992), “An Analysis of Default Risk in Mobile Home Credit,” Journal of Banking and Finance, 16(2), 299-312.
3、Steenackers, A. and Goovaer, M.J. (1989),“A Credit Scoring Model for Personal Loans,” Insurance Mathematics Economics, (8), 31-34.
4、Von Furstenberg, G. M. (1969), “Default Risk on FHA-Insured Home Mortgages as a Function of the Terms of Financing: A Quantitative Analysis,” Journal of Finance, 24(3), pp. 459-477.