Application and Practice of Big Data in Financial Risk Control

Abstract

The application of big data technology in financial risk control has significantly enhanced the efficiency and accuracy of risk management. By collecting multi-dimensional data, financial institutions can construct precise risk assessment models to achieve real-time monitoring and early warning of risks. This paper explores the specific application scenarios of big data in financial risk control, including credit
risk assessment, market risk prediction, operational risk prevention, and liquidity risk management, and analyzes its technical implementation
paths, such as data collection and integration, data mining and analysis, risk assessment and monitoring, as well as early warning and intervention. The application of big data technology provides financial institutions with powerful risk prevention and control measures, promoting
the steady development of the financial industry.