Part II: General Framework for Operational Risk Capital Modelling

Rafael Cavestany

Operational risk modelling requires a robust determination of its inputs, as presented in Part I. This includes the definition of criteria for the collection of, and quality control for, internal losses, sourcing of external data, a strong process for the capture of scenario analysis and the incorporation of business environment and internal control factors (BEICFs) into the capital model.

Once quality inputs are available, they can be used in the appropriate modelling processes to obtain adequate capital estimations. Part II describes the modelling processes that permit a quality capital estimation and describes the circumstances in which these processes should be applied.

Most institutions calculate their operational risk capital requirements based on either a loss distribution approach (LDA) – mainly based on loss data – or a scenario-based approach (SBA). A more advanced approach is the hybrid model (HM), where loss data and scenario analysis are combined into a single model to compute capital using, in effect the four data elements requested in the Basel Committee on Banking Supervision “Operational Risk – Supervisory Guidelines for Advanced Measurement Approaches”

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