Research on machine learning and financial risk early warning of listed companies based on random forest model

Abstract

This paper explores the application of machine learning technology based on random forest model in financial risk early warning of listed companies. By analyzing the data, we constructed a random forest model to identify potential financial risk factors. The study found that the random forest model showed high accuracy and stability in dealing with financial risk early warning issues. The model can effectively identify key indicators that affect the company's financial status and provide timely risk warning signals for investors and management. In addition, we also discussed the limitations of the model and the direction of future research, aiming to provide listed companies with a more accurate and effective financial risk early warning system, thereby helping companies to identify and respond to potential financial challenges as early as possible.