Research On Financial Early Warning System For Listed Companies In China

With the continuous deepening of economic reform and the expansion of market size, China's listed companies are facing increasingly rigorous challenges. Since the end of 1986 China enacted the "Bankruptcy Law", bankruptcy has become an issue of wide concern in all society, especially with the application of information technologies, people pay more attention to the application of artificial neural network prediction algorithm. Analysis of the financial situation of listed companies not only is very important to protect the interests of investors and creditors, but also have significant impact on preventing financial crises for the operators and monitoring the quality of listed companies for government departments.The research of financial early warning started late in our country. In recent years our country although already has obtained the certain achievements, but compared with overseas companies, still has many problems. This article is divided into four parts. The first part is real-time information systems, in order to achieve timely collection of financial information, real-time monitoring purposes. The second part is internal control, which can control the entire process. The third part is the main part. According to the inducement of financial risk, early-warning system is divided into two parts: qualitative warning system and quantitative warning system. Qualitative warning system is aimed at environmental factors, which is not reflected in the financial statements; Quantitative system is aimed at the factors, which is reflected in the financial statements. According to the operational activities, quantitative warning system is divided into internal financing, investment and business activities. The main method is using financial indicators to analysis and judgment. The fourth part is the protection mechanisms of early warning systems. In order to achieve the purpose of the early warning, after compared the static and dynamic methods, this article chose the LVQ network model of artificial neural network. It can be proved that this method not only can make effective judgment, but also have the advantage of simplicity.