Achieving High-Performing, Simulation-Based Operational Risk Measurement with RevoScaleR
by Revolution Analytics on Jun 28, 2012
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Under the Basel II Accord, financial institutions are required for the first time to determine capital requirements for a new class of risk – operational risk. Large and internally active banks are ...
Under the Basel II Accord, financial institutions are required for the first time to determine capital requirements for a new class of risk – operational risk. Large and internally active banks are required to estimate operational risk exposure using the Advanced Measurement Approach (AMA), which relies on advanced empirical models. As banks continue to develop and enhance their own AMA models for operational risk measurement, they are increasingly utilizing R to perform various modeling tasks.
In this presentation, Northern Trust will discuss the use of R in the loss distribution approach (LDA), the most widely used empirical approach for the measurement of operational risk. In Northern Trust’s experience, R offers unparalleled access to various distributions that are most relevant for modeling the frequency and severity of operational loss events. Additionally, Northern Trust utilizes R to perform large scale Monte Carlo simulations within the context of the LDA. These simulations are computationally intense from a processing perspective, taking many hours and sometimes days to complete with the open source distribution but much less with Revolution R Enterprise.
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