Financial fraud has shown a trend of complexity and concealment in recent years, and traditional risk management methods are no longer able to properly handle massive amounts of data and ever-changing fraud patterns. Through excellent data processing, storage, and analysis capabilities, big data technology has become a key tool for preventing fraud risks in the financial sector. Based on the unique characteristics of big data technology, this article elaborates on the architecture of big data storage and processing, data collection and preprocessing methods, and focuses on analyzing the application of this technology in financial fraud monitoring. By utilizing real-time transaction monitoring, fraud detection models, data fusion, and behavior pattern recognition technologies, the efficiency and accuracy of financial risk management have been significantly improved. At the same time, establishing a rapid response and decision support system has further strengthened the strategies and execution capabilities of financial institutions in combating fraudulent behavior.

Xuanrui Zhang. Exploration of the Application of Big Data Technology in Financial Fraud Monitoring. Socio-Economic Statistics Research (2026), Vol. 7, Issue 1: 19-26. https://doi.org/10.38007/SESR.2026.070103.

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