Exposure-based approaches

Rafael Cavestany and Emilio Lopez Cano

Previous chapters have introduced methodologies to build operational risk capital (ORC) models based on loss data and scenario analysis modelling. This chapter will presents exposure-based approaches that intend to address perceived weaknesses of loss and scenario modelling-based approaches.

Loss modelling is backward-looking by nature as it is based on historical data, and relies on the assumption that past loss experience has enough information to predict future losses. Moreover, loss data is dominated by high-frequency events, while the risk profile of financial institutions is most commonly dominated by low-frequency, high-severity events. Loss modelling addresses this issue by projecting the loss distribution tail by fitting a distribution function to the observed loss data. The extrapolation relies on the assumption that major losses can be derived from low losses. Although this can be true for many ORCs, it might not provide you with the complete set of possible operational risk events, and loss modelling requires being complemented with other information sources – such as scenario analysis and external loss data.

The main purpose of scenario analysis is to produce

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