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This study randomly selects 49 samples from the branch of the case bank in southern Taiwan, from January 2011 to December 2015, for individual real estate loans. Additionally, this study uses the Logistic regression analysis to identify significant variables affecting the credit risk of individual real estate loans. We include 14 explanatory variables: gender, occupation, age, marriage situation, education background, ratio of expenses to revenue, loan rate, loan term, loan amount, use of loan funds, grace period, with or without the use of credit card and cash card loans, with or without guarantors, and with or without owner-occupied housing. Empirical results find that the factors of age, education background, ratio of expenses to revenue, loan rate, loan term, loan amount, and grace period significantly affect credit risk of individual real estate loans. Also, the correct prediction rate of the logistic model established by this study is approximately 85.71%.
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