If there is one certainty that emerged from the election result and the housing elements of the Queen’s speech, it is that the world of social housing will not get simpler over the next five years. The manner in which the sector as a whole, sub-sectors and individual organisations within it, adapts is only likely to lead (in the short to medium term) to more, and new kinds of, complexity.
And talking of complexity, in the New Scientist of 23rd May, there is a really good article that addresses the issue of systemic risk from a regulatory perspective. (Yes, that was New Scientist…). Despite the lurid tagline (“Capitalism’s hidden web of power”) the article addresses the mathematical model used in the understanding of risks associated with systemically important financial institutions, or SIFIs. A SIFI designation is based on three characteristics: size, interconnectedness and complexity. However, as the article points out much study has been made of the first two but less so on the third, complexity, for the probably obvious reason – it is very hard to define and measure.
Nonetheless the article describes the work of a team led by Robin Lumsdaine at the American University in Washington DC that has set out to address the deficit of understanding around complexity and risk, and their model, based on network theory, has produced some very interesting initial findings. Notably, “even small companies can be complex in a way that could threaten financial stability if they failed”. In other words, size matters, but it is not the only thing that matters when it comes to evaluating systemic risk.
For the learning of lessons of the model in social housing, post-Lehman brothers and Cosmopolitan, one can only hope that the New Scientist has a diverse readership amongst the non-executive directors of groups, chairs of audit committees, advisors on risk and, of course, the regulator.
In which context I will leave the last word to David Veredas of the Free University in Brussels (ULB) quoted in the New Scientist article as saying “It (the model) is very nice because it is very simple, and regulators like simple things”.