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Transactions: WSEAS TRANSACTIONS ON INFORMATION SCIENCE AND APPLICATIONS
Transactions ID Number: 42-276
Full Name: YaYueh Shih
Position: Assistant Professor
Age: ON
Sex: Female
Address: 580 Sinmin Rd., ChiaYi City 600
Country: TAIWAN
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E-mail address: moonshih@mail.ncyu.edu.tw
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Title of the Paper: Credit scoring model development in banking industry based on hybrid method
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Number of paper pages: 10
Abstract: Enterprises used to draw credit line from bank. However, the loan application process always takes much time, and thus that the evaluation techniques developed to enhance and to facilitate the loan approval process has become an outstanding issue of risk management among banks. The decision trees methodology is also popular in machine learning as a means of automated knowledge acquisition for data mining. Although decision trees have been successfully used in many applications, such as pattern classify, there are several problem, these problems arise mainly due to the splitting step used in practice in the top-down tree induction process. A hybrid model was proposed in this study for credit risk management, in our system neural networks are served only as a tool to reduce the decision table and filter its noise attributes while the final decision rules is generated from the reduced table by decision tree. The effectiveness of the approach was verified by the experi!
ments comparing with traditional decision tree.
Keywords: Neural Networks, Decision Trees, Data Mining, Credit Risk Management.
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