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

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.

Machine learning in internet financial risk management: A systematic literature review

“…Internet finance has rapidly developed due to its convenience, real-time nature, and no geographical limitations, resulting in the expansion of market size, number of participants, and services or products offered [2], However, it also faces significant risks, as evidenced by the large number of problems with P2P platforms in 2018. Compared with traditional financial services, internet finance has relatively low barriers to entry, smaller amounts, faster speeds, and more relaxed audits, which has led to higher requirements for credit risk control, fraud prediction, and other risk prevention measures in internet financial platforms [3,4]. Research related to risk identification, risk alert, and risk supervision based on big data [5][6][7][8], blockchain [9,10], artificial intelligence [4,11,12] and machine learning algorithms [1,2] is progressively unfolding.…”

“…Compared with traditional financial services, internet finance has relatively low barriers to entry, smaller amounts, faster speeds, and more relaxed audits, which has led to higher requirements for credit risk control, fraud prediction, and other risk prevention measures in internet financial platforms [3,4]. Research related to risk identification, risk alert, and risk supervision based on big data [5][6][7][8], blockchain [9,10], artificial intelligence [4,11,12] and machine learning algorithms [1,2] is progressively unfolding.…”

The Current State and Challenges of Financial Risk Management

“…Overly complex financial products, inadequate risk assessment, and a lack of transparency were key contributors. The crisis underscores the importance of effective oversight, transparency, and stress testing [11].…”

A Big Data Technique for Internet Financial Risk Control

“…After determining the risk analysis and predictive analysis, an early warning report is generated. Simultaneously, assess whether the early warning module meets actual needs, investigate the causes of forecast result deviations, improve related algorithms to improve the risk prediction function, close the gap between the two, as well as improve the accuracy and scientifically of the early warning module [19].…”