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A Systems Accident Approach to Systemic Financial Risk

Journal 35: Zicklin-Capco Institute Paper Series in Applied Finance

Joseph Calandro, Jr.

This paper proposes a definition and assessment methodology for systemic financial risk that was inspired by systems accident research. Sociologist Charles Perrow found that industrial, aviation and marine systems are prone to failure if those systems are interactively complex and tightly coupled. Using that framework as a starting point, financial crisis research led to the definition of systemic financial risk as a function of financial complexity and excessive leverage. I present practical criteria for applying these parameters, and then profile the triggering mechanism of systemic financial risk – financial contagion – in a behavioral context consistent with my framework. A discussion of the current state of systemic financial risk is then offered. By practically defining systemic financial risk in the context of financial crisis case histories (with a focus on contemporary history) this paper facilitates a deeper and more practical understanding of this important, yet seemingly elusive phenomenon. And it does so in a manner readily assessable to a broad array of financial agents and researchers.

The popular definition of systemic financial risk is “risk that cannot be diversified” [Brealey and Myers (2000)]. Notwithstanding its popularity, this definition has little practical value, especially since the phenomenon of systemic financial risk has become more tangible following the 2007-2008 financial crisis. Systems-oriented research since that crisis led to the definition of “systemic financial risk” as the possibility of an economy-wide crash due to complex financial interactions that are fueled by excessive leverage. This definition was inspired by Perrow’s (1999) systems accident framework, which defines an accident-prone system as one that is both interactively complex and tightly coupled. Perrow’s framework was derived from detailed analyses of industrial, aviation and marine accidents. Leveraging this approach I analyzed financial crisis case histories to derive a framework to assess systemic financial risk, which is presented in the first two sections below. I then profile the triggering mechanism of systemic financial risk – financial contagion – from a behavioral perspective, and then I apply the framework to an overview of the current financial system.

Financial complexity

The first parameter of systemic financial risk based on my research is financial complexity. In general, a system is “complex … when there are strong interactions among its elements, so that current events heavily influence the probabilities of many kinds of later events” [Axelrod and Cohen (2000)]. Extending this definition, “financial complexity” can be defined as unfamiliar, unexpected and/or not immediately comprehensible financial interactions that are systemically significant. According to Tversky and Kahneman (1974), “Even when the likelihood of failure in each component [of a system] is slight, the probability of an overall failure can be high if many components are involved.” As defined here, financial complexity is a function of the components or criteria.

  • One financial agent observed that, “If you have got sixty, one hundred billion, or however many billions of something on your balance sheet, that is a ‘very’ big number… I don’t think you should ignore a big number, no matter what it is” [Tett (2010)].
  • “History is littered with examples of banks that collapsed because they misjudged default risk [i.e., counterparty creditworthiness] or had too much exposure to a single sector or lender. The savings and loan debacle of the late 1980s and early 1990s was one case in point” [Tett (2010)].
  • Before its 1998 failure, Long-Term Capital Management (LTCM) had a $1 trillion notional derivatives exposure [Lowenstein (2000)].
  • More than half of Fannie Mae’s and Freddie Mac’s delinquencies during the 2007-2008 financial crisis occurred in just four states: California, Arizona, Nevada, and Florida [Acharya et al. (2011)].

Derivatives-based concentrations generally continued to grow following LTCM’s failure; for example, consider the growth of credit default swaps (CDS) profiled in Figure 1. What makes this exhibit material from a systemic risk perspective is not just its “big numbers” but also the interconnected counterparty structure that was/is exposed to it. Significantly, this structure is the result of both governmental and non-governmental financial actions because, since the savings and loan crisis, government has facilitated the sale of troubled, as well as failed, financial institutions to more fiscally sound ones. The short-term objective of this policy, and its related easy-money policies (which are discussed below), was to rescue failed institutions without directly involving taxpayer funds, which generally seems to have been accomplished. Consider, for example, JP Morgan’s purchase of WaMu: According to Grind (2012), that “purchase meant that WaMu’s failure didn’t cost the deport insurance a dime.” However, one long-term consequence of the policy is increased levels of financial concentration risk.

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