Financial Risk Management Based on Big Data Technology
Year: 2024
Type: article
Abstract: In the past decade, the financial industry has shown a trend of rapid development, with traditional financial institution models gradually being replaced by a coexistence of traditional and various emerging financial forms. As the operating models in the financial industry undergo corresponding changes, the types and quantity of risks that may exist within the industry continue to increase. The complexity of financial risks is gradually becoming more pronounced, with factors such as changes in laws and regulations, lack of credit assessment, and data loss or leaks in internet financial trading platforms potentially leading directly to financial risks. Employing traditional work models and methods for financial risk management often makes it difficult to achieve the desired risk control outcomes. Currently, big data technology has been widely utilized in the insurance, banking, and other sectors of the financial industry. Major financial institutions continuously innovate the traditional methods of analyzing and processing data information by leveraging big data, transforming the way financial data exists in the industry. Only by actively adapting to the trends of the times and flexibly applying big data technology to practices such as credit assessment and risk alerting can financial risk management innovation be comprehensively promoted, resulting in effective control of complex financial risks. Based on this, this paper analyzes the changes and characteristics of financial risk management in the era of big data, discusses the important role and specific applications of big data technology in the field of financial risk management and proposes relevant strategies for enhancing financial risk management in the big data environment, aiming to advance the progress of financial risk management in the era of big data.
Author: Zhihao Shen
Institution: Shanxi University of Finance and Economics
Language: English
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4404867300