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Enabling Data Analysis for Addressing Systemic Risk
January 2012
Eric Hughes, The MITRE Corporation
Arnie Rosenthal, The MITRE Corporation
Charles Worrell, The MITRE Corporation
ABSTRACT
Recently, the U.S. experienced an economic crisis that shook confidence in key
aspects of the financial system, and led to some calls for changes in the way the
government tracks economic information that might warn of such a crisis. Among those
changes was the creation of the Office of Financial Research (OFR), intended to collect
and provide information to "anticipate emerging threats to financial stability or assess
how shocks to one financial firm could impact the system as a whole" [OFR 2010]. These
functions have been termed systemic risk: the risk that a threat to a large, single
component of the financial system poses to the system as a whole, due to the interconnectedness
of the system and potential lack of consumer confidence in the system that
might be caused if one component failed. This paper considers the computational
approaches that may be needed in support of the mission of providing information about
systemic risk, and possible mitigations of that risk. We acknowledge that there are many
schools of thought for why the recent crisis occurred, the degree of systemic risk it posed,
and possible government actions to mitigate the risk. Our position is that an agency such
as the OFR with responsibility for monitoring systemic risk must be prepared to analyze
diverse, uncertain information about the financial system and threats to it. Such an
agency must be prepared to evaluate this information from multiple perspectives, and
assess possible future outcomes given a variety of assumptions and regulatory responses.
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