The financial market has always been one of the most aggressive adopters of information technology. The recent adoption of big data technology in the financial market not only provides us with an ample amount of micro-level data but also creates more risk contagion channels for financial products. For instance, the financial risk could be transmitted via social media and the utilization of blockchain technology renders the prosperity of cryptocurrency.

Therefore, it is natural to investigate the impacts of this shifting landscape on the threads connecting fintech and financial risk analysis, which requires interdisciplinary efforts from scholars in financial economics, mathematics, computer science, complex systems, and econophysics. We must facilitate this interdisciplinary dialogue and collaboration in both academic and industrial communities.

The aim of this Special Issue is, therefore, to publish high-quality research and review articles addressing, by and large, the research questions recognized at the frontier of fintech and financial risk analysis in the era of Big Data. Being aware of their interdisciplinary nature, we aim to encourage methodological pluralism and welcome the attempt of multiple approaches, including, but not limited to, empirical studies, agent-based modeling, and human-subject experiments.

Potential topics include but are not limited to the following:

• Big data analytics for systemic risk
• Contagion and financial networks
• Cross-correlation analysis
• Default risk in bond
• Evolution of investors’ behavior
• Fraud detection with social media
• Machine learning in the financial market
• Pricing and risk of cryptocurrency
• Sentiment contagion and crash risk
• Social media coverage and market dynamics