Design of Modern Enterprise Financial Crisis Warning System Based on Random Forest Algorithm

For enterprises, it is necessary and urgent to establish a system that can provide macroeconomic warning for them. This paper took manufacturing listed companies as a case, and introduced random forest algorithm into it. The process standards of data mining projects have been utilized to construct a financial warning model, and the warning effects of this model have been explored, thereby helping listed manufacturing companies establish an effective warning mechanism. It is hoped that this can provide timely warning signals to company managers and stakeholders. In the asset liability analysis of this article, companies experiencing financial crises have experienced significant changes in their asset liability ratio, reaching 130% in the 9th month, indicating a strong dependence on bank loans. This article established a sound financial early warning system for enterprises, which had practical significance both in theory and in practice.