Taking Uncertainty Seriously: Simplicity versus Complexity in Financial Regulation

Distinguishing between risk and uncertainty, this paper draws on the psychological literature on heuristics to consider whether and when simpler approaches may out-perform more complex methods for modelling and regulating the financial system. We find that: (i) simple methods can sometimes dominate more complex modelling approaches for calculating banks’ capital requirements, especially if limited data are available for estimating models or the underlying risks are characterised by fat-tailed distributions; (ii) simple indicators often outperformed more complex metrics in predicting individual bank failure during the global financial crisis; (iii) when combining information from different indicators to predict bank failure, “fast-and-frugal” decision trees can perform comparably to standard, but more information-intensive, regression techniques, while being simpler and easier to communicate.