Enterprise’s internal control for knowledge discovery in a big data environment by an integrated hybrid model

Author(s):  
Fu-Hsiang Chen ◽  
Ming-Fu Hsu ◽  
Kuang-Hua Hu
2021 ◽  
Vol 2021 ◽  
pp. 1-6
Author(s):  
Ran Wei ◽  
Sheng Yao

With the deepening of business informatization, all kinds of business application data are rapidly gathering, which promotes enterprises to enter the era of big data. Enterprises begin to build the concept of big data, deepen the understanding of big data, extract potential data value, and improve the operation ability of enterprises and information systems. At the same time, big data brings internal control information to the system, which is becoming more and more challenging, so enterprises pay more and more attention to the security of the information system. This paper aims to introduce the enterprise financial risk identification and information security management and control under the big data environment and master the enterprise financial risk identification method so that the enterprise can adapt to the needs of the times competition faster and better. This paper introduces the method of identifying financial risk in the background of big data by classifying the methods of financial risk identification and designing the factor model. Through the experimental investigation of the company's financial asset rate, the enterprise financial risk situation is displayed, and the enterprise can improve the internal management to control the financial risk within a certain range. The experimental results show that from 2016 to 2020, the internal control and asset rate of the enterprise affect the financial risk of the enterprise, 82% of the operators only have a reasonable debt structure and sufficient solvency, the operator can operate in a safe state and then maintain a low financial risk, and the operator should also take measures to prevent the occurrence of risk in advance and realize the business goal of maximizing benefits.


2017 ◽  
Vol 39 (5) ◽  
pp. 177-202
Author(s):  
Hyun-Cheol Choi
Keyword(s):  
Big Data ◽  

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