銀行房貸授信發生逾期的影響因素

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题名:	銀行房貸授信發生逾期的影響因素
作者:	鍾煒豐;CHUNG,WEI-FENG
贡献者:	產業經濟研究所
关键词:	貸收比;主從債務;循環信用;逾期放款;Loan to Income Ratio;Debt of Main and From;Revolving Credit;Overdue Loans
日期:	2016-07-20
上传时间:	2016-10-13 14:02:00 (UTC+8)
出版者:	國立中央大學
摘要:	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.
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