Operational Risk Capital Models is a guide for the implementation of state of the art operational risk capital models suitable for regulatory approval.
For insurers, Solvency II implementation has created the need, in both highly developed and less developed markets, for the development of these models that help to better understand risks, safe capital and compliance. For the banking industry, regulators in many countries in Africa, Asia and Latin America (as well as Europe) are pressing their local banks to implement advanced operational risk capital models. Banks that have made early implementation are looking to improve their capital models with new advances to match the increasing regulatory requirements.
"I found the quantitative methods presented in “Operational Risk Capital Models” to be not only rigorous, but also understandable and actually useable and useful, which can be said of shockingly few books treating operational risk. Amidst a wasteland of operational risk management pie charts and unactionable and subjective heat maps, books like this are an oasis of practical, applied solutions for capital estimation and stress testing. If your objective is to directly and measurably mitigate and manage operational risk using scientifically defensible, objective methodology, as opposed to red-amber-green traffic ‘analyses,’ the methods herein are the kind you need."
J.D. Opdyke, author of multiple Journal of Operational Risk papers and winner of OR&R’s “Operational Risk Paper of the Year” Award in 2012 and 2015.
Operational Risk Capital Models enables you to model your operational risk capital to ensure the model meets regulatory standards. It describes the process end to end, from the capture of the required data to the modelling and VaR calculation, as well as the integration of capital results into your institution’s daily risk management.
• Modelling Challenges
• Regulatory Compliance and Supervision
• Operational Loss Modelling
• External Data Rescaling
• Scenario Analysis Framework and Modelling
• BEICFs Modelling and Integration into Capital Model
• Capital Results Integration into Business Planning and Risk Appetite
• Hybrid Model Construction: Integrating ILD, ED and SA
Operational Risk Capital Models is essential for the creation of op risk capital models for both regulatory compliance and improving risk management practices.The book addresses and resolves the challenges in the implementation of advanced operational risk capital models by presenting a highly detailed end-to-end process for the capital model construction, compliance and integration into management.
The first part of the book describes a robust framework for the definition and capture of the four data elements: Internal Loss Data, External Data, Scenario Analysis and Business Environment Internal Control Factors. This part includes topics such as the validation of scenario analysis and the use of business environment and internal control factors as inputs to the capital model. It provides insights for mitigating cognitive biases in scenario analysis and defines a common understanding for operational loss. It also presents state-of-the-art methods for expert judgment elicitation (Structured Expert Judgment) and their application into operational risk scenario analysis.
The second part presents the exhaustive modelling and integration of the four data elements to compute operational risk VaR, capital and depict the operational risk profile of the institution. This part addresses all standard and more advanced topics, such as the modelling of BEICFs and their use in capital allocation, correlation calculation and ex-post capital adjustment; modelling of scenario analysis including GoF, tail control and more; determination of the optimal modelling granularity and threshold (up to 8 different methods); fitting distributions with old and new loss data by the use of a decay factor; analysis of capital instability (the resampling and what-if methods); various methods for external data re-scaling; construction of a hybrid model using credibility theory; operational risk dependencies including frequency-severity dependence and the use of expert judgment in their elicitation; different methods for capital allocation (contribution to expected shortfall, Heuler allocation, incremental analysis and others); backtesting of severities, frequencies and total losses; stress testing under different approaches including the modified LDA, regression, historical analysis, scenario analysis based and more.
In the third part, the work turns into the integration of capital results into the day to day management: embedding of the operational risk profile into strategic and operational business planning process; operational risk appetite definition, cascading down, monitoring and adherence; and the risk/reward evaluation of the effectiveness of controls and mitigation plans (insurance, action plans, critical infrastructure protection, operational risk predictive models and the determination of the optimal mitigation strategy using adversarial risk analysis).
Finally, the book's appendices examine in detail the distributions used in operational risk modelling including truncated, shifted, mixtures, empirical and plain vanilla parametric distributions; different credibility theory models, optimization methods used in operational risk modelling and business risk modelling.
|Publication date||30 Apr 2015|
PART I - Capture and Determination of the Four Data Elements
1. Collection of Operational Loss Data: ILD and ED
2. Scenario Analysis Framework and BEIFCs Integration
Rafael Cavestany, Brenda Boultwood and Daniel Rodriguez
PART II - General Framework for Operational Risk Capital Modelling
3. Loss Data Modelling: ILD and ED
Rafael Cavestany and Daniel Rodriguez
4. Scenario Analysis Modelling
5. BEICFs Modelling and Integration into Capital Model
6. Hybrid Model Construction: Integration of ILD, ED and SA
Rafael Cavestany, Daniel Rodriguez and Fabrizio Ruggeri
7. Derivation of the Joint Distribution and Capitalisation of Operational Risk
8. Backtesting, Stress Testing and Sensitivity Analysis
Rafael Cavestany and Daniel Rodriguez
9. 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
10. Strategic and Operational Business Planning and Monitoring
Lutz Baumgarten, Rafael Cavestany and Brenda Boultwood
11. Risk/reward Evaluation of the Mitigation and Control Effectiveness
Rafael Cavestany and Javier Moguerza
Appendix I - Distributions for Modelling Operational Risk Capital
Appendix II - Credibility Theory
Appendix III – Mathematical Optimization Methods Required for Operational Risk Modelling and Other Risk Mitigation Processes
Appendix IV – Business Risk Quantification