Research on the Construction of a Big Data-Driven Precision Prevention and Control System for Financial Risks
Abstract
cross-domain contagion, posing structural bottlenecks for traditional risk control models in terms of data dimensions, response speed, and
predictive accuracy. By integrating multi-source data and iterating intelligent algorithms, big data technology drives the transformation of
risk prevention and control from "post-event handling" to "pre-event warning." This paper elucidates the theoretical logic and technical architecture of big data risk control, analyzes practical challenges such as data silos, algorithmic black boxes, privacy compliance, and regulatory
coordination, and constructs a closed-loop prevention and control system from four dimensions data governance, intelligent decision-making,
prevention and control tools, and institutional safeguards to provide a practical reference for the modernization of financial risk governance.
Keywords
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DOI: http://dx.doi.org/10.70711/memf.v3i8.9719
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