Operational Risk Capital Models (2nd edition)
First published:
ISBN: 9781782724223
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Regulatory approval report
Regulatory approval report
Introduction
Challenges of operational risk advanced capital models
Part I: Capture and Determination of the Four Data Elements
Collection of operational loss data: ILD and ED
Scenario analysis framework and BEICFs integration
Part II: General Framework for Operational Risk Capital Modelling
Loss data modelling: ILD and ED
Distributions for modelling operational risk capital
Scenario analysis modelling
Exposure-based approaches
BEICFs modelling and integration into the capital model
Hybrid model construction: Integration of ILD, ED and SA
Derivation of the joint distribution and capitalisation of operational risk
Backtesting, stress testing and sensitivity analysis
Regulatory approval report
Evolving from a plain vanilla to a state-of-the-art model
Part III: Use Test, Integrating Capital Results into the Institution’s Day-to-day Risk Management
Strategic and operational business planning and monitoring
Risk/reward evaluation of mitigation and control effectiveness
Appendix 1: Credibility theory
Appendix 2: Mathematical optimisation methods required for operational risk modelling and other risk mitigation processes
Business risk quantification
Previous chapters have described different steps to build a state-of-the-art operational risk capital model with all the required elements. These elements permit the creation of a solid model for the determinations of capital estimates.
Banks and insurance companies may use these capital estimates for regulatory compliance, such as the Internal Capital Adequacy Assessment Process (ICAAP), regulatory stress-test exercises and others, as mentioned in previous chapters. Regulatory authorities request the validation of the models used for capital requirement purposes.
Model validation is submitted to regulatory authorities via a regulatory approval document. Regulators’ standard requirement on approval regulatory reporting is that such a report should allow the full replication of model results if the report is given to an independent analyst. This requires the documentation of all model assumptions, end-to-end starting with the selection of loss data and/or scenarios, to the Monte Carlo simulation parameters, passing through the details of the modelling assumptions and how all the different information elements have been merged into the model.
This chapter will present
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