The Application of Artificial Intelligence and Big Data in Financial Risk Forecasting and Management

Abstract

In the past, financial risk management has always faced a changing market environment and while there were several traditional predictive models available for use, they have limited capabilities in addressing non-linear or high-dimensional risk factors. Therefore, enhancing the foresight in risk identification as well as the accuracy of decision-making within financial institutions will require further exploration into the application value of artificial intelligence and big data technology. Consequently, the goal of this paper is to conduct a comprehensive evaluation regarding the integration pathways and effectiveness of implementing these two technologies into financial risk predicting and managing practices. Findings from the research indicate that AI algorithms offer a deeper understanding of complex, hidden relationships among large amounts of multiple sources of information, while the availability of big data platforms provides opportunities for continuously monitoring risk in real-time. The combination of the two not only significantly improves the timeliness and accuracy of risk prediction, but also promotes the intelligent transformation of risk management models from passive response to active intervention.