Big Data Analytics for Financial Risk Management

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This thesis explores financial risk in supply chains, detailing the research context, objectives, and industry implications. It introduces the intersection of supply chain finance risks and Big Data, highlighting a significant disruption example. A comprehensive literature review identifies gaps in traditional and machine learning methods. The study presents advanced risk models, including ASCA-SVM and ASCALSMLP, with practical results. Finally, it discusses the Residual Conv-GRU model,...