Prediction and Analysis of Corporate Financial Risk Assessment Using Logistic Regression Algorithm in Multiple Uncertainty Environment. (14th September 2022)

• Record Type: Journal Article
• Authors: Li, Xinyue; Yan, Saisai; Lu, Jiajia; Ding, Yanqiu
• Other Names: Kaifa Zhao Academic Editor.
• Is Part Of: Journal of environmental and public health. Volume 2022(2022)
• Publication Date: 2022-09-14
• Subjects: Environmental health -- Periodicals; Occupational diseases -- Periodicals; Public health -- Periodicals; 613.105
• DOI: 10.1155/2022/2733923
• Languages: English
• ISSNs: 1687-9805

Abstract

Abstract : Currently, the level of economic globalisation is expanding, which gives organizations more room to grow while also subjecting them to an increasing amount of pressure from the market. Companies are forced to deal with an increasing number of unclear aspects due to the unstable internal and external environments, which also increases the risks they confront. A management system for corporate financial risk is according to studies on early warning systems for financial risks. Its goals are to raise the standard of corporate financial management and boost economic advantages, identify concerns and potential hazards in the corporate financial management process, stop corporate financial crises in their tracks, and lessen the losses brought on by such crises. The financial risk management of the organization is predicted and examined in this research using the logistic regression model. The use of a logistic regression model allows for the simultaneous analysis of various risk factors, such as discrete and continuous variables, as well as the analysis of external variables' interactions and confounding. This method is suited for widespread usage in practice because it has shown exceptional outcomes in study that are 16.24% better than those of the conventional method.