A Premonition System of Operational Risk in Insurance Enterprises Based on Fuzzy Optimum Selection and Artificial Neural Networks
Zeng Zhongdong · Journal of Sichuan University · 2006
There are not many valid data because of the short history of Chinese insurance industry.This paper constructs a new model for obtaining a premonition system of operational risk in insurance enterprises by utilizing fuzzy optimum selection and the BP artificial neural network method,and provides the theoretical basis of the model.Then the three important sections in construction of the model are theoretically designed and deduced.These sections include a risk index predicting sub-system based on BP neural network,a risk evaluating sub-system based on fuzzy optimum selection and a risk warning sub-system based on neural network with fuzzy optimum selection.A case study shows that the model is effective and feasible.The model offers a new way of dynamic early warming of operational risk in insurance enterprises of China.