Identification of Financial Risks in Enterprises Based on Logistic Models

Abstract

The diagnosis and identification of wealth risks and the construction of early warning models are crucial for operating enterprises, and have a profound impact on the management policies of the enterprise management and the work of the finance department. At present, there are many models used for financial risk identification and early warning in enterprises. However, in response to the low accuracy of existing models such as Z-score model, DE-SVM (Differential Evolution-Support Vector Machine) model in identifying and warning corporate risks, and the lack of significant impact on identifying corporate financial risks, this article referred to the logistic regression model to construct a corporate financial risk identification system. By studying 18 listed enterprises that have suffered losses for two consecutive years and 18 enterprises with normal financial conditions, financial indicators that can reflect significant differences between problem enterprises and normal enterprises were used as evaluation criteria to analyze the output results of the discriminant model. The results showed that the model had an accuracy of 94.68% in identifying financial risks in research enterprises, and had a good effect on identifying financial risks in enterprises. This study applied an efficient method for identifying corporate financial risks, enhancing detection accuracy to help enterprises more accurately assess financial risks and effectively prevent potential financial crises. The risk identification system based on the logistic regression model provides enterprises with effective risk management tools, aiding in the improvement of financial stability and maintaining competitiveness in complex market environments.