Research on Real-Time Processing and Risk Management Methods of Enterprise Financial Big Data Based on Distributed Computing Framework

The risk of financial aspects intuitively reflects the development status and operating results of enterprises, enterprises must control the financial risk of this key link, so that the financial risk of a safe landing, to protect the stability and health of the enterprise.This paper selects the financial data of listed companies, and comprehensively analyzes the level of the company's financial performance from four aspects, namely, profitability, operating capacity, growth capacity and solvency indicators.Using Benford's law to test the quality of each data of each financial indicator, the Benford factor is introduced as a new explanatory variable, and combined with the company's financial risk early warning indicators to establish a random forest early warning model.The results show that profitability and growth capacity are the strengths of listed companies, while operational capacity and solvency are the weaknesses.The results analyzed by K-means clustering algorithm show that the sample companies are divided into 5 categories.And compared with the basic random forest model, the random forest model based on Benford's law can improve the accuracy of financial risk warning.Finally, the model with the best prediction effect is used to judge the financial status of G listed companies, get the early warning results, verify the accuracy and applicability of the model and put forward corresponding countermeasure suggestions.