transfers that happened between thousands of US banks on a typical
day, they found that 75 per cent of the payments involved just 66
institutions.[83]
Illustration of assortative and disassortative networks
Adapted from Hao et al., 201 1The variability in links wasn’t the only problem. It was also how
these big banks fitted into the rest of the network. In 1989,
epidemiologist Sunetra Gupta led a study showing that the dynamics
of infections could depend on whether a network is what
mathematicians call ‘assortative’ or ‘disassortative’. In an assortative
network, highly connected individuals are linked mostly to other highly
connected people. This results in an outbreak that spreads quickly
through these clusters of high-risk individuals, but struggles to reach
the other, less connected, parts of the network. In contrast, a
disassortative network is when high-risk people are mostly linked to
low risk ones. This makes the infection spread slower at first, but
leads to a larger overall epidemic.[84]
The banking network, of course, turned out to be disassortative. A
major bank like Lehman Brothers could therefore spread contagion
widely; when Lehman failed, it had trading relationships with over one
million counter-parties.[85] ‘It was entangled in this mesh of
exposures – derivatives and cash – and no one had the faintest idea