tailieunhanh - Neural Networks in Business Applications

Neural Networks in Business Applications presents about Customer Loan Classification, Bankruptcy Prediction, Exchange rate Forecasting, Input variables, The output variable, Training set and test set, Application design. | Neural Networks in Business Applications by Assoc. Prof. Dr. Duong Tuan Anh Faculty of Computer Science and Engineering, Ho Chi Minh City of Technology November 2011 Outline Customer Loan Classification Bankruptcy Prediction Exchange rate Forecasting Conclusions References F. D. Nittis, G. Tecchiolli & A. Zorat, “Consumer Loan Classification Using Artificial Neural Networks”, ICSC EIS’98 Conference, Spain Feb.,1998 . Wilson and R. Sharda, “Bankruptcy Prediction Using Neural Networks,” Decision Support Systems, Vol. 11, No. 5, June 1994, pp. 545-557. G. Zhang & M. Y. Hu, “Neural Network Forecasting of the British Pound/US Dollar Exchange Rate”, Omega, International Journal of Management Science, 26, 4(1998), 495-506. Loan Approval Problem Statement. Many stores are now offering their customers the possibility of applying for a loan directly at the store, so that they can proceed with the purchase of relatively expensive items without having to put up the entire capital all at once. Initially the offering of consumer loans was found only in connection with expensive purchases, such as cars, but it is now commonly offered at major department stores for purchases of washing machines, televisions, and other consumer goods. The loan applications are filled out at the store and the consumer deals only with the store clerks for the entire process. The store, however, relies on a financial company (often a bank) that handles such loans, evaluates the applications, provides the funds, and handles the credit recovery process when a client fails to fulfil the repayment schedule. For this study, there were 1000 records of consumer loan applications that were granted by a bank, together with the indication whether each loan had been always paid on schedule or there had been any problem. The provided data did not make a more detailed distinction about the kind of problem encountered by those “bad” loans, which could range from a single payment | Neural Networks in Business Applications by Assoc. Prof. Dr. Duong Tuan Anh Faculty of Computer Science and Engineering, Ho Chi Minh City of Technology November 2011 Outline Customer Loan Classification Bankruptcy Prediction Exchange rate Forecasting Conclusions References F. D. Nittis, G. Tecchiolli & A. Zorat, “Consumer Loan Classification Using Artificial Neural Networks”, ICSC EIS’98 Conference, Spain Feb.,1998 . Wilson and R. Sharda, “Bankruptcy Prediction Using Neural Networks,” Decision Support Systems, Vol. 11, No. 5, June 1994, pp. 545-557. G. Zhang & M. Y. Hu, “Neural Network Forecasting of the British Pound/US Dollar Exchange Rate”, Omega, International Journal of Management Science, 26, 4(1998), 495-506. Loan Approval Problem Statement. Many stores are now offering their customers the possibility of applying for a loan directly at the store, so that they can proceed with the purchase of relatively expensive items without having to put up the

• Quản trị mạng
• Neural Networks in Business Applications
• Customer Loan Classification
• Bankruptcy Prediction
• Exchange rate Forecasting
• Input variables
• The output variable
• Training set and test set