Financial Management Early Warning Modeling Analysis Based on RBF Neural Network Algorithm

Nowadays, the operation of enterprises is facing a variety of risk problems, among which the financial risk is the most concerned. Because once financial risks accumulate to a certain extent after not take timely measures, will certainly lead to a greater financial crisis. Since China joined the WTO, along with the opening of the banking industry, insurance industry and securities market, the financial risk management environment of enterprises in China has changed, that is, there are stricter requirements. Therefore, strengthening the early warning of enterprise financial crisis is the top priority of modern enterprise development. With the development of science and technology, only with the establishment of enterprise financial management early warning model scientifically, timely discovering the causes of financial crisis, and taking effective preventive measures, can we avoid the occurrence of financial crisis from the source. Based on the RBF neural network algorithm, we build the enterprise financial crisis early warning model, and use the advanced scientific and technological means to avoid the financial crisis. The paper uses the literature research method, quantitative analysis method and qualitative analysis method, expounds the basic theory, the financial crisis simulation experiment, comparing the traditional early warning model, the research results show that the built model has a high accuracy (78%, 75%), timely capture risk signals, help managers implement preventive measures, minimize the loss caused by risk, to avoid the return of financial risk.