Operational Risk Capital Models
First published:
ISBN: 9781782722014
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Loss Data Modelling: ILD and ED
Rafael Cavestany and Daniel Rodríguez
Loss Data Modelling: ILD and ED
Introduction
Collection of Operational Loss Data: ILD and ED
Scenario Analysis Framework and BEICFs Integration
Loss Data Modelling: ILD and ED
Scenario Analysis Modelling
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
Evolving from a Plain Vanilla to a State-of-the-Art Model
Strategic and Operational Business Planning and Monitoring
Risk–Reward Evaluation of Mitigation and Control Effectiveness
In this chapter, we examine the modelling of operational loss data, which can be applied in the modelling of internal loss data (ILD) and external data (ED). The use of ILD in the capital model permits us to incorporate relevant information on the specific characteristics of the risk profile of an institution, as reflected in its loss experience dominated by high frequency events. The use of ED permits us to complement the modelling with the experience of peer institutions, which is not reflected in the ILD, accompanying ILD with low frequency/high severity events.
Loss data is generally modelled by determining the frequency and severity distributions of the loss data of each operational risk category (ORC). The importance of using ILD in capital modelling is recognised by the Basel Committee on Banking Supervision in a 2011 document titled, “Operational Risk – Supervisory Guidelines for Advanced Measurement Approaches” (BCSG-AMA): “Supervisors expect ILD to be used in the operational risk measurement system (ORMS) to assist in the estimation of loss frequencies; to inform the severity distribution(s) to the extent possible.” In addition, the BCSG-AMA states, “Supervisors expect
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