Analysis on the Early Warning of Enterprise Financial Risk under the Method of Efficiency Coefficient——Take H Power Company as an Example

2020 ◽  
pp. 1-11
Author(s):  
Qiaoying Ding

The financial market is changing rapidly. Since joining the WTO, our country’s financial companies have faced pressure from dual competition at domestic and abroad. The complex internal and external environment has forced financial enterprise managers to improve risk prevention awareness, early warning and monitoring, so as to responding to emergencies and challenges in the financial market. However, traditional forecasting and analysis methods have problems such as large workload, low efficiency, and low accuracy. Therefore, this article applies intelligent computing to the forecast of financial markets, using related concepts of fuzzy theory and Internet intelligent technology, and proposes to establish a model system for financial enterprise risk early warning management and intelligent real-time monitoring based on fuzzy theory. This article first collected a large amount of data through the literature investigation method, and made a systematic and complete introduction to the related theoretical concepts of fuzzy theory and financial risk early-warning management, has laid a sufficient theoretical foundation for the subsequent exploration of the application of fuzzy theory in financial enterprise risk early warning management and intelligent real-time systems; Then a fuzzy comprehensive evaluation method that combines the analytic hierarchy process and fuzzy evaluation method is proposed, taking a listed company mainly engaged in automobile sales in our province as a case, the company’s financial risk management and modeling experiment of the intelligent real-time system; Finally quoted specific cases again, used the fuzzy comprehensive evaluation method to carry out risk warning and evaluation on the PPP projects of private enterprises in our province, and concluded that the project risk score is between 20-60, which is meet the severe-medium range in the risk level. Research shows that the use of fuzzy theory and modern network technology can make more accurate warnings and assessments of potential and apparent risks of financial enterprises, greatly improving the safety of financial enterprise management and reducing the losses caused by various risks.


2021 ◽  
Author(s):  
Wenqi Zhao ◽  
Jinyi Li ◽  
Junwei Wang ◽  
Wenjing Zhao

Author(s):  
Ali Serhan Koyuncugil

This chapter introduces an early warning system for SMEs (SEWS) as a financial risk detector which is based on data mining. In this study, the objective is to compose a system in which qualitative and quantitative data about the requirements of enterprises are taken into consideration, during the development of an early warning system. Furthermore, during the formation of system; an easy to understand, easy to interpret and easy to apply utilitarian model that is far from the requirement of theoretical background is targeted by the discovery of the implicit relationships between the data and the identification of effect level of every factor. Using the system, SME managers could easily reach financial management, risk management knowledge without any prior knowledge and expertise. In other words, experts share their knowledge with the help of data mining based and automated EWS.


2014 ◽  
Vol 687-691 ◽  
pp. 4922-4925
Author(s):  
Liang Liu ◽  
Chun Ling Li

The briefly review and the development of the financial risk early warning theory is first discussed in this study and the domestic and foreign research is analyzed as a brief summary. Secondly, the concept of financial risks, financial crisis and the financial early warning is defined. Financial fragility as a starting point is used to establish the rationality model of the financial risk early warning system. The early warning indicators is selected on the basis of the 12 indicators of macro-financial risks, 15 net financial indicators is selected to represent the financial markets according to the characteristics of China's financial markets. In the empirical part, the previous empirical analysis method is chosen to build the financial risk early warning signal system. In order to display China's financial risk profile, the proper model for the calculation is made on the basis of empirical analysis. Thus, in order to minimize the local financial risk, the early warning system should be established by the local government, together with some other necessary measures.


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