The Key to Understanding Systemic Risk: Data Driven Analytics

When addressing systemic risk, firms need to increase market transparency and accuracy of data while preserving anonymity and security.

If ever there was a time to start getting serious about systemic risk management it is now. The long running regulatory reform saga that has been playing out in the US and Europe is reaching the end of the beginning. Legal definitions and structures are here, now the hard work really starts. Between an industry that has been lobbying for limited change, and a set of politicians and regulators who want comprehensive reform there has been little constructive debate about the value to the industry and efficiency gains to be achieved from having better granular data on financial obligations. The key challenges are to increase the market transparency and accuracy of data relating to systemic risk while preserving anonymity and security.

In a global financial system that is characterized by a high degree of interdependency, systemic risk can be defined as the inherent risk of cascading failures that combine to significantly damage or even completely destroy the entire system. The rise of sophisticated financial instruments that 'package up' multiple risks in a relatively opaque way has increased systemic risk in the financial system in recent years. Systemic risk analytics aim to quantify risks relating to the broad-scope, long-term dynamics and dependencies of major markets and players, and are associated with significant shifts in market state. By contrast, market and credit risk have a narrower scope, make linear extrapolations from recent market trends, and assume localized shifts in aggregated market parameters.

Coming up with a mechanism for tracking the entire global financial system is daunting, but not impossible. The development of supercomputing techniques and advances in data storage and analytics make the creation of macro prudential tools and systems, a 'systemic risk utility", a viable proposition. The changes in the European regulatory landscape propose the creation of the European Systemic Risk Board. The recently passed Dodd-Frank Reform Bill in the US sees the creation of Supervisory Council of Regulators, and the Office of Financial Research. They will need tools to effectively carry out their mandates.

Access to Clean Data

In order to create a 'systemic risk utility', all parties need to agree on common models for collating and formatting their data. In the near future, it is likely that data standardization to enable systemic risk analysis will become a regulatory requirement. This will be a key focus of the newly formed Office of Financial Research. Of course, different challenges exist in Europe due to multiple national jurisdictions and data privacy laws so constructive dialogue is needed to assess how to collect the requisite information, initially leveraging existing reporting. Similarly, agreement will be needed on how to share this data and information globally.

Much work still needs to be done to create the most useful data in the most appropriate format so that multi-dimensional stress testing and other analysis can be done to assess the build-up of leverage and monitor the health of other aspects of the financial system. This work need not be the burden the industry fears. Understanding the broader role that existing industry owned utilities can play in this reforming ecosystem will drive the industry to create and adopt new standards, and can create economies of scale by reutilizing many forms of reporting that already occur.