The Empirical Analysis of Affecting Overdue Factors of Mortgage Loans

• Main Authors: Chin-Hsuan Yang, 楊謹鍹
• Other Authors: 王親仁
• Format: Others
• Language: zh-TW
• Published: 2013
• Online Access: http://ndltd.ncl.edu.tw/handle/v2mmf6

碩士 === 國立臺中科技大學 === 企業管理系事業經營碩士班 === 101 === The number of financial institutes is increasing as the estate market is heating up. For getting the entire builders mortgage loans business and other consumer needs, the financial industry will quickly approval loans for providing better service quality to meet consumer’s needs. Therefore, it is the issue that how to quickly screen out client’s situation and help loan officers to make the right decisions in order to decrease the overdue of mortgage loans. This study wants to investigate the affecting overdue factors to distinguish its implicit risk and know its attribute for giving the quantized indicator and the basis of making correct decision in order to reduce loan risk, non-performing loan ratio of mortgage loans. Therefore, financial institutes can raise their physical income and whole operational performance by means of increasing the quality, speed, efficiency of bank credit granting. Chi-Square Testing and Logistic Regression model will be applied to analyze factors and the probability of affecting mortgage loans overdue based on the data, 672 mortgage loans (578 of normal and 94 of abnormal) of a bank located at Taoyuan district during 2007 – 2011. The study found that seven significant factors, such as receive an education degree, occupational class, annual income, debt ratio, estimated value of collateral, loan amount, loan percentage, grace period have apparently influence on overdue probability of mortgage loans. The prediction accuracy rate of normal, abnormal and total mortgage loan cases is 94.6%, 71.2%, and 91.3% respectively. The prediction accuracy of mortgage loans will be improved if the data of independent variables were unmodified. Especially the prediction accuracy of abnormal mortgage loans will increase to 78.7%.