| Summary: | 碩士 === 國立臺北大學 === 國際財務金融碩士在職專班 === 106 === This study collects the data of Small and Medium Enterprise (SME) managers’ credit card credit status at the " Joint Credit Information Center " between 2009 and 2016 from a domestic commercial bank. There are 300 samples in total containing 150 non-performing loans and 150 normal credit loans.
The methodology of this study is using Logistic Regression Model to find out the relationship between SME managers’ credit card credit status and corporate credit default risk.
The results show that:
I. A significant correlation between occurrences of non-performing loans of SME and three factors, which are SME managers whom have“credit card overdue payment records”,“none credit card overdue payment records, but pay with minimum required amount”and“pay by installment payments”.
II. The rate of forecast accuracy of non-performing loans possibility is higher, when the model uses three foresaid variables with comparison one factors–credit card overdue payment records of SME managers.
Due to there is only one lagging indicator, which is credit card overdue payment records of SME managers, has been applied in the existing SME credit risk assessment model of population when it rates the default risk of SME. It is suggested that there are two more leading indicators, which are “none credit card overdue payment records of SME managers, but pay with minimum required amount” and “pay by installment payments”, should be added into the model as these two factors may also imply the risk of credit expansion. It not only optimizes the SME credit risk assessment model, but also upgrades the quality of credit assets. Meanwhile, it is also reducing the possibility of non-performing loans as well as strengthening the Capital Adequacy Ratio of financial institutions and its operation structure. Consequently, it helps to built up a robust financial market body of abstract starts here.
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