Monitoring and assessing the risks in financial systems is critical to economic and social well-being. The financial crisis of 2007-2009 saw the breakdown of financial intermediation markets that led to many bank failures and a global credit crunch, drawing attention to the need for enhanced financial systemic risk analysis. Meeting systemic risk analysis challenges requires integration of a range of very large and complex data sources (e.g., financial contracts; counterparty reference data; financial position and transaction data; and market data) with a variety of systemic risk analysis techniques. Given this requirement, it makes sense to explore how new approaches to the analysis of large and complex data sources might be used to enhance financial systemic risk analytics capabilities. One such approach is Visual Analytics (VA). This interdisciplinary panel will explore the application of VA to financial systemic risk analysis, focusing on such questions as: what are the analytic tasks required for financial systemic risk analysis? What data are needed to support these tasks? How can interactive visualization support the provision of financial systemic risk capabilities such as the “situational awareness” and understanding interconnectedness in complex financial networks? How can visual analytics be combined with statistical analyses, semantics-based approaches, data mining, and high performance computing to enhance systemic risk analysis? And, what visual designs and interactions will best support visual analysis for financial systemic risk analysis, in particular under crisis conditions? The panel brings together perspectives from the systemic risk analysis “user communities”, i.e., financial regulators and market participants, with those of VA scientists and academic researchers to explore the capabilities and research challenges related to design, implementation and evaluation of a holistic financial systemic risk analysis framework with which to derive faster and better insights into the health of financial systems.