A perfect storm – why are some operational losses larger than others?

By Patrick McConnell

Abstract
In mid 2004, after a lengthy period of industry consultation, the Basel Committee finally released its definitive rules on capital charges for Operational Risk under Basel II. In its proposals for allowing banks to calculate regulatory capital using their own internal models, the Basel Committee specified very stringent ‘quantitative standards’ for modelling operational risk. This has led to much discussion in the industry as to the types of statistical tools that could be used to calculate operational risk capital, under the so-called Loss Distribution Approach (LDA). Advanced techniques, such as Extreme Value Theory (EVT), have been proposed to satisfy the new regulatory requirements.

However, LDA approaches make the assumptions that all loss events are drawn from the same underlying ‘model’, and can be grouped using the Basel II classification of ‘Loss Event Types’. The paper challenges these assumptions, specifically for the cases of the very largest losses, which have been shown to have a disproportionately high impact on quantitative measures resulting in inflated capital calculations. Using published examples, the paper argues that many of the very largest operational risk losses do not fit easily into the very broad ‘one size fits all’ Basel II event type classification, and, in fact, cut across many of the mandated categories. In statistical terms, these events should properly be considered as ‘outliers’ that should be removed from statistical analysis of the underlying distribution and addressed using other techniques.

Furthermore the paper argues that, for some of these large events, a measurement approach that attempts to measure risk to an unrealistic level of precision (e.g. to the 99.9th percentile demanded by Basel II) introduces ‘moral hazards’, encouraging managers to claim that risks have been fully mitigated to the (somewhat arbitrary) regulatory standard, rather than address the serious issues underlying these events. The illusory search for precision is no better illustrated than in the case of the real, but highly uncertain, potential for a Avian Flu Pandemic, where epidemiologists and medical experts are working within a six point scale for primary risks (death etc.) whereas banks are required to estimate capital to cover secondary impacts (i.e. monetary losses) to a precision of 1 in 1,000– clearly an unattainable task!

This paper recognises and argues that much more research is needed into the quantitative and qualitative standards proposed by Basel II and is a contribution to these debates. In particular, the paper argues for much more detailed and specific research into how best to manage risks that are real but difficult to measure under Basel II, in effect, arguing for expanding and strengthening Pillars 2 and 3 of Basel

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•Date: 30th June 2006 • Region: World • Type: Article •Topic: Operational risk
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