Seeing the Dominoes Fall: A Causal Knowledge Platform for Cross-Market Financial Contagion Early Warning Using Global Public Data

Authors: [Yuan Man Lee] Corresponding Author: [ht3100z@outlook.com] Abstract Financial systemic risk increasingly propagates through hidden interconnections across markets, sectors, and borders. Traditional risk models—relying on static financial ratios or black-box machine learning—fail to provide early, explainable, and actionable warnings. We present NeuroSphere Pro, an enterprise-ready AI system that detects cross-market contagion using only publicly available data from China and global sources. By integrating corporate networks, bond defaults, macroeconomic indicators, and news sentiment into a dynamic causal knowledge graph, our platform identifies transmission pathways (e.g., “property sales slump → supplier cash crunch → trust product default”) and generates prescriptive mitigation strategies. Validated on real-world crises from 2020–2025—including the Evergrande collapse and U.S. regional bank stress—NeuroSphere Pro delivers warnings 7–21 days earlier than conventional approaches with 42% fewer false alarms. Critically, it requires no private transactional data, deploys in under six weeks, and complies with GDPR and China’s PIPL. This work demonstrates that public data, when structured causally, can power strategic risk intelligence.