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Dartmouth Researchers Help to Create New Measurement of Banks “Too Big to Fail”

May 11, 2015

The 2008 financial crisis highlighted the risks of large, multinational, complex and interconnected banks that are “too big to fail” without severely damaging the global economy.

Since then, analysts have mostly focused on the size and interconnectedness of so-called “systemically important financial institutions” (SIFI), but Dartmouth researchers and their collaborators have created a novel mathematical formula that measures the internal complexity of individual firms. In a new study, the researchers show that this mathematical representation and various associated metrics provide a consistent way to compare the complexity of firms with often very different business models and as such may provide the foundation for determining a SIFI designation.

The study is available on the Social Science Research Network and will be presented June 4-5 at the International Conference on the Policy Implications of Systemic Risk Models and Measures. A PDF is available upon request.

“Our work quantifies the level of organizational complexity of a firm. We believe this may prove useful should firms need to reduce their complexity either in response to business or regulatory needs,” says co-author Dan Rockmore, a professor of mathematics and computer science at Dartmouth. “Using a data set containing the control hierarchies – or internal governance structures -- of many of the designated SIFIs, we find that in the past two years, these firms have decreased their complexity, perhaps in response to regulatory requirements.”

In November 2011, the Financial Stability Board, in collaboration with the International Monetary Fund, published a list of 29 SIFIs based on “their size, complexity, and systemic interconnectedness.” In their new study, the Dartmouth researchers and their collaborators use an individual firm’s management control hierarchy as a proxy for institutional complexity. The control hierarchy is a network representation of the institution and its subsidiaries.

“Ours is a novel approach that uses the innate network structure of the control hierarchy in considering intra-firm complexity,” Rockmore says. “In short, we quantify the industry and country heterogeneity in the hierarchy of business units. Greater diversity means greater supervisory challenges. This approach complements the more commonly studied inter-firm complexity (i.e., the interconnectedness across firms) that people usually think of when determining SIFI designations.”

By defining complexity as a function of the firm’s organizational tree, the researchers demonstrate that complexity and size are not synonymous and thus warrant distinct mention in the SIFI definition.

“Contrary to conventional wisdom, our results suggest that some of the SIFI-designated institutions may not pose greater supervisory challenge since their control hierarchy network may limit diversity in their business units,” Rockmore says. “Surprisingly, we find little difference in complexity between SIFIs and non-SIFI banks. However, the insurance companies in our sample are more complex according to these three criteria despite being smaller in size, having fewer subsidiaries and being less geographically or industry-diverse than the banks.”

Dartmouth Professor Dan Rockmore is available to comment at daniel.n.rockmore@dartmouth.edu.

The study included researchers from Dartmouth, American University, University of Washington, University of Oxford and Santa Fe Institute.

Last Updated: 9/9/15