Internet Financial Risk Management in the Context of Big Data and Artificial Intelligence

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Abstract

In recent years, the emergence of big data and artificial intelligence technology has made Internet finance a brand new development model in the new era. As an emerging financial format, Internet finance plays an important role in providing people with convenient and efficient services. However, due to the late start in this regard and the imperfect related policies and regulations, China is currently still in the development stage, resulting in its risk management system not being mature and complete and lacking uniformity. There are also many regulatory deficiencies, which are not conducive to the healthy, stable, and continuous growth and progress of Internet finance. In the new situation, it is of great significance to strengthen the research on the security of China's Internet finance. Therefore, how to effectively manage Internet financial risks in the context of big data and artificial intelligence has become a topic of research. This study uses questionnaire analysis and data analysis to understand the distribution of risks and the importance of risk response measures through questionnaire surveys. According to the survey results, in the eyes of most interviewees, the ratios of operational risk, credit risk, platform operation risk, and lack of law and reputation risk in high-risk areas are 0.15, 0.3, 0.29, 0.51, and 0.1, respectively. The risks of these first-level indicators need to be particularly important and need to be effectively avoided to manage Internet financial risks. In addition, the most important risk response measures are the construction of information security, followed by the improvement of relevant laws and regulations. In their view, only from these aspects can we effectively control risks internally and externally.

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APA

Wang, N., & Wang, K. (2022). Internet Financial Risk Management in the Context of Big Data and Artificial Intelligence. Mathematical Problems in Engineering, 2022. https://doi.org/10.1155/2022/6219489

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