Visualizing Financial Networks: new understanding of the financial system and implications for policy makers
Finance session
Ines Salpico (Soramäki Networks) — Kimmo Soramaki (Soramäki Networks)
Visualizing Financial Networks: new understanding of the financial system and implications for policy makers
Network Science has been so far regarded mostly as a tool of statistical analysis. However, it is growingly understood also as a methodological and conceptual approach to data processing, analysis and interpretation.
The social networking phenomena has had interesting and dramatic implications for network science namely because it made network representations widespread and better understood by the general audience. It also pushed the field’s boundaries while opening the door for a clear connection between the different disciplines that study and relate to it. At the same time new understanding of data has emerged: data is now understood as a mutating, ever updating and interconnected entity.
As a consequence of this change of paradigm in understanding data and of the developments in network science, institutions are growingly pushed to not only make data available but also to render it in a way that is both clear and “browsable”. Institutions (both public and private) have realized that visually exploring/representing the vast amounts of data internally available to them is of key importance for decision making and strategic planning.
In parallel the latest financial crisis made it clear that financial institutions must be regarded as nodes in a complex system in which interdependency and mutual influence are essential for its analysis. It illustrated the role of financial linkages as a channel for the propagation of shocks. It also forged the concept that institutions may be “too interconnected to fail”, in addition to the traditional concept of being “too big to fail”. Analyzing and understanding financial/economic phenomena and systemic risk therefore relies on the possibility of representing sets of (financial) data not in blunt tables but rather in appropriate and clear network layouts that can show the links between system’s agents.
In the aftermath of the crisis new regulatory authorities and powers have been set up. These include the European Banking Authority and the European Securities and Markets Authority in Europe and the Financial Stability Oversight Council and the Office of Financial Research in the USA, among others. The creation of these new regulatory agents will result in more granular data being made available. The policies determined by these new institutions will not only have an impact in the finance sector but also in the broader economy forcing other agents – commercial banks, businesses, etc. – to adapt to a changing environment. It will also push them to adopt new internal and external procedures and standards in data analysis and communication.
Financial Networks present specificities – different from those of social networks – that require new tools and models to make sense of them. In this paper we will look at how different data analysis and visualization tools are being developed and how they can be used and applied within financial institutions and risk analysis. Furthermore, a critical view will be drawn to how the introduction of these tools is affecting policy, decision making processes and institutional discourses.
The paper will have both a theoretical and a practical perspective, resulting from the background research and hands-on work undergone while developing the data and network analysis software FNA – Financial Network Analyzer – and implementing its use in different financial institutions.
