Work has now been completed on a SWIFT Institute research grant looking at the role of risk communication in macroprudential oversight and of visualization in risk communication.
Authored by Peter Sarlin, he concludes that two essential, yet rare, features for supporting the analysis of big data and communication of risks are analytical visualizations and interactive interfaces. Sarlin presented his initial findings at The Future of Financial Standards conference (March 2014, London). Now you can read his complete research paper, available for download here.
Macroprudential Oversight, Risk Communication and Visualization
Peter Sarlin – Goethe University Frankfurt; RiskLab Finland
This paper discusses the role of risk communication in macroprudential oversight and of visualization in risk communication. Beyond the soar in availability and precision of data, the transition from firm-centric to system-wide supervision imposes obvious data needs. More- over, broad and effective communication of timely information related to systemic risks is a key mandate of macroprudential supervisors, which further stresses the importance of simple rep- resentations of complex data. Risk communication comprises two tasks: internal and external dissemination of information about systemic risks. This paper focuses on the background and theory of information visualization and visual analytics, as well as techniques provided within these fields, as potential means for risk communication. We define the task of visualization in internal and external risk communication, and provide a discussion of the type of available macroprudential data and an overview of visualization techniques applied to systemic risk. We conclude that two essential, yet rare, features for supporting the analysis of big data and commu- nication of risks are analytical visualizations and interactive interfaces. This is illustrated with implementations of three analytical visualizations and five web-based interactive visualizations to systemic risk indicators and models.