Enterprise Financial Management based on Random Forest Algorithm

Abstract

The valuable information in the company's financial data is very important to evaluate the business situation of enterprises. Based on the five factors of cash flow, growth ability, operation ability, solvency and profitability, this paper determines the financial operation status of 27 enterprises, and proposes to use particle swarm optimization random forest algorithm to complete the classification and prediction of enterprise financial operation status. At the same time, the performance evaluation indexes of recall, accuracy, precision and F1 score algorithm are determined. Compared with other classification prediction methods. The accuracy, F1 value, precision, recall and AUC of PSO-RF algorithm are the best, which are 99.36%, 99.36%, 99.35%, 99.32% and 98.98% respectively. This study will help to realize the classification and prediction of enterprise financial operation.