The application of big data in modern enterprise finance is becoming more and more common, and the research adopts the random forest algorithm to explore the enterprise financial risk status, so as to make personalized financial decisions. Construct the enterprise financial risk early warning model based on random forest and construct the financial risk early warning index system. The performance of the random forest model is tested by comparing the financial risk early warning effect of the random forest model with other models. Taking M company as an example, by analyzing its financial risk situation from 2019 to 2023, it puts forward targeted financial decision-making suggestions. The random forest model performs best in the financial risk early warning performance experiment, far outperforming other models. The financial risk status of Company M in 2019-2023 is dangerous, sub-safe, general, dangerous, and general. Although it has been improved in general, it is still in a fluctuating state and the development status is unstable. For the specific financial risk status of Company M, financial decision-making suggestions are proposed for the three aspects of solvency, operating capacity and development capacity.