Study On The International E-commerce Credit Risk Early-warning Model Based On BP Neural Network

E-commerce have emerged and flourished under the rapid development of information technology after the internet was applied to business since the 1990s.It has changed the traditional methods of trading, shocked the traditional business models and methods of economic management and brought tremendous revolution to modern economic life and people's conception.This subject's study is under the condition of computer and network communication technology development and usage extensively among international commercial field. The transmission of commercial information and realization of the business procedure appears a great deal of new characteristics in E-business. These characteristics have changed traditional commercial operation law and mode and brought some new problems, especially international E-business credit risks are important subjects absorbed the attention and study in order to take reasonable precautions.This subject's study is based on the research of the E-business theories, credit risk theories and early-warning system theories. The thesis has 6 parts altogether. Chapter 1, introducing the background and significance, the Research Status at home and abroad research and innovation point; Chapter 2 and chapter 3, analyzing the theory of international e-commerce credit risk, warning management, BP neural network and verifying the feasibility of BP neural network's application to international e-commerce credit risk warning management; Chapter 4, building the index system of international e-commerce credit risk warning based on BP neural network, including the dynamic and static warning system and pointing out the methods and principles of index selection. Chapter 5, establishing warning model of international e-commerce credit risk based on BP neural network, including collection, selection and standardization of data, the structure of model, training and test of model. Chapter 6, pointing out the output and relative strategies of different degrees of credit risk.