| 摘要(英) |
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. |
| 參考文獻 |
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. |
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