Author(s)

Zijun Lin ¹

Affiliation(s)

¹ Warwick Business School, University of Warwick, Coventry, CV4 8JB, UK

Corresponding Author

Zijun Lin

ABSTRACT

In the context of globalization and digitalization, the risks faced by enterprises have become increasingly complex and diverse, making traditional risk management methods insufficient to cope with the rapidly changing market environment. Data analysis technology plays a crucial role in enterprise risk management as a modern tool. This study explores the specific applications of data analysis in enterprise risk management, covering aspects such as risk identification, assessment, and prediction, with a focus on how big data and machine learning technologies enhance enterprises' risk response capabilities. Furthermore, through case analyses in financial and operational management, this paper demonstrates the effectiveness of data-driven risk management strategies and discusses the challenges and future trends of data analysis in enterprise risk management. The research indicates that data analysis can not only help enterprises identify risks more accurately but also enable automated risk control through intelligent methods, providing strong support for sustainable development.

KEYWORDS

Data analysis, enterprise risk management, risk identification, risk prediction

CITE THIS PAPER

Zijun Lin, Research on the Application of Data Analysis in Enterprise Risk Management. Financial Engineering and Risk Management (2024) Vol. 7: 10-16. DOI: http://dx.doi.org/10.23977/ferm.2024.070602.

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