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This study extends the Foreclosed House credit scoring system with further five Speculator characteristics, i.e. ｢ debt ratio ｣, ｢ whether the loan's residence and tender object is in different locations ｣ ,｢ the borrower of last three months by other banks because of the number of new mortgage query totaled more than three times ｣ , ｢ the borrower to apply for loans has more than one loan credit ｣ and ｢ the borrower to apply for loans had paid off the mortgages totaled more than three times within three years ｣ , in the logistic regression model to build a dichotomous prediction credit scoring model which can be adopted by financial institutes to prevent default risk of Foreclosed House mortgage loan and improve the quality of risky asset. The empirical results indicate that the overall accurate predict rate of the model with five Speculator characteristics (80.5%) is higher than the model without five Speculator characteristics (91.0%) indicating that characteristics of speculator has the most ability to predict default rate. [ABSTRACT FROM AUTHOR]

This study extends the traditional credit scoring system with further four factors, i.e. 「debt ratio」,「real-estate speculator」,「batch processing mortgage loan」and「size of the house」in the logistic regression model to build a dichotomous prediction model which can be adopted by financial institutes to prevent default risk of residential mortgage loan and improve the quality of risky asset. The empirical results indicate that the overall accurate predict rate of this new model is 89.3%, which is significantly higher than the traditional model (77.5%). Among the four factors, the factor of「real-estate speculator」has the highest odds ratio (24.49) indicating that factor of speculator has the most ability to predict default rate. [ABSTRACT FROM AUTHOR]