In the financial sector of the United States, the deployment of big data technology has emerged as a pivotal strategy for financial institutions to bolster their competitiveness and mitigate risks; thus, the core objective of this article is to examine how big data technology can be harnessed to achieve comprehensive integration of internal and external data within financial institutions, thereby creating an efficient and reliable platform for the collection, storage, and analysis of vast amounts of data; recognizing that traditional risk management models are increasingly inadequate in addressing the complexities of the modern market, this article employs big data mining and real-time streaming data processing technologies to monitor, analyze, and generate alerts based on various business data, enabling more accurate identification of potential risks and timely intervention through the statistical analysis of historical data and precise mining of customer transaction behaviors and relationships; consequently, this article designs and implements a financial big data intelligent risk control platform that not only facilitates the effective integration, storage, and analysis of internal and external data of financial institutions but also provides intelligent visualization of customer characteristics and their relationships, alongside the intelligent supervision of diverse risk information.