Three areas in particular are discussed: •  Data and Communications: to allow a better understanding of network dynamics following a shock and thereby inform public communications. For example, learning from epidemiological experience in dealing with SARs, or from macroeconomic experience after the Great Depression, putting in place a system to map the global financial network and communicate to the public about its dynamics;  •  Regulation: to ensure appropriate control of the damaging network consequences of the failure of large, interconnected institutions. For example learning from experience in epidemiology by seeking actively to vaccinate the “super-spreaders” to avert financial contagion; and  •  Restructuring: to ensure the financial network is structured so as to reduce the chances of future systemic collapse. For example, learning from experience with engineering networks through more widespread implementation of central counterparties and intra-system netting arrangements, which reduce the financial network’s dimensionality and complexity. Networks and finance are not complete strangers. There has been growing interest among network theorists in applying their techniques to financial phenomena over the past few years. For example, network techniques have already been applied extensively to the  2  BIS Review 53/2009  dynamics of payment systems and inter-bank networks. 1 But the financial crisis of the past two years provides both a greater body of evidence, and a stronger incentive, to apply the lessons from other network disciplines to the pressing problems facing financial policymakers today.

In short, diversification strategies by individual firms generated a lack of diversity across the system as a whole. So what emerged during this century was a financial system exhibiting both greater complexity and less diversity. Up until 2007, many participants in financial markets would have viewed that network evolution as the inevitable by-product of technical progress in finance. Until then, complexity plus homogeneity equalled stability. But in just about every non-financial discipline – from ecologists to engineers, from geneticists to geologists – this evolution would have set alarm bells ringing. Based on their experience, complexity plus homogeneity did not spell stability; it spelt fragility. In understanding why, it is useful to explore some of the wider lessons from those disciplines, taking in turn the effects of complexity and diversity on stability. Complexity and stability Tropical rainforests are a complex adaptive system. In the immediate post-war period, these eco-systems were often used as a case-study when demonstrating why complex systems tended to exhibit greater stability. 3 In Elton’s (1958) words, this was because there are “always enough enemies and parasites available to turn on any species that starts being unusually numerous”. Complexity strengthened self-regulatory forces in systems, so improving robustness. This was the prevailing ecological wisdom up until the early 1970s. That conventional wisdom has since been turned on its head. From the 1970s onwards, orthodoxy was altered by a combination of enriched mathematical models and practical experience.