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Quantifying Operational Risk in General Insurance Companies. Developed by a Giro Working Party

Published online by Cambridge University Press:  10 June 2011

Michael Howard Tripp ,
H. L. Bradley ,
R. Devitt ,
G. C. Orros ,
G. L. Overton ,
L. M. Pryor  and
R. A. Shaw
Michael Howard Tripp
Affiliation:
Watson Wyatt LLP, Watson House, London Road, Reigate, Surrey RH2 9PQ, U.K., Tel: +44 (0)1737-241144, Fax: +44 (0)1737-241496, Email: Michael.tripp@eu.watsonwyatt.com
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Abstract

The paper overviews the application of existing actuarial techniques to operational risk. It considers how, working in conjunction with other experts, actuaries can develop a new framework to monitor/review, establish context, identify, understand and decide what to do in terms of the management and mitigation of operational risk. It suggests categorisations of risk to help analyses and proposes how new risk indicators may be needed, in conjunction with more normal quantification approaches.

Using a case study, it explores the application of stress and scenario testing, statistical curve fitting (including the application of extreme value theory), causal (Bayesian) modelling and the extension of dynamic financial analysis to include operational risk. It suggests there is no one correct approach and that the choice of parameters and modelling assumptions is critical. It lists a number of other techniques for future consideration.

There is a section about how ‘soft issues’ including dominance risk, the impact of belief systems and culture, the focus of performance management systems and the psychology of organisations affect operational risk. An approach to rating the people aspects of risk in parallel with quantification may help give a better overall assessment of risk and improve the understanding for capital implications.

The paper concludes with a brief review of implications for reporting and considers what future work will help develop the actuarial contribution. It is hoped the paper will sow seeds for the development of best practice in dealing with operational risk and increase the interest of actuaries in this emerging new topic.

Keywords

Operational RiskEnterprise Risk ManagementRisk ManagementGeneral InsuranceQuantification of RiskFinancial ServicesCapital AssessmentCapital ManagementPeople Process and SystemsCurve FittingRisk ManagementRegulations and RiskCapital RegulationsRisk CategorisationRisk IndicatorsBank of International SettlementsExtreme Value TheoryStress TestsScenario AnalysisCausal ModelsBayesian TechniquesSoft IssuesMyers-BriggsBelbin Team RolesRisk ReportingProfessional Guidance
Type
Sessional meetings: papers and abstracts of discussions
Information
British Actuarial Journal , Volume 10 , Issue 5 , 01 December 2004 , pp. 919 - 1012
Copyright
Copyright © Institute and Faculty of Actuaries 2004

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References

BBA (1999). Operational risk management — the new frontier. The British Bankers Association.Google Scholar
BBA (2002). Operational risk management — the new frontier. British Bankers Association.Google Scholar
BBA, CA. Operational risk database loss categorisation. British Bankers Association. http://www.bba.org.uk/xl/45716.xlsGoogle Scholar
BCBS (2001). Working paper on the regulatory treatment of operational risk. Bank for International Settlements, Basel Committee on Banking Supervision.Google Scholar
BCBS (2003). Sound practices for the management and supervision of operational risk. Bank for International Settlements. Basel Committee Publications No 96.Google Scholar
Belbin, M.R. (1995). Team roles at work. Butterworth-Heinemann.Google Scholar
CAS (2001). Final report of the advisory committee on enterprise risk management. Casualty Actuarial Society.Google Scholar
CAS (2003). Overview of enterprise risk management. Enterprise Risk Management Committee, Casualty Actuarial Society. CAS various. www.casact.org/research/dfa/index.htmlGoogle Scholar
Charniak, E. (1991). Bayesian networks without tears. AI Magazine, 12(4), 50–63. http://www.aaai.org/Library/Magazine/Vol12/12-04/Papers/AIMag12-04-007.pdfGoogle Scholar
Converium Re. (2003). Dynamic financial analysis understanding risk and value creation in insurance. econwpa.wustl.edu/eps/ri/papers/0306/0306002.pdfGoogle Scholar
Doerig, H.-U. (2000). Operational risks in financial services: an old challenge in a new environment. Paper presented to Institut Internationale d'Etudes Bancaires, London. Available from http://www.risklab.ch/~kaufmann/RM.htmlGoogle Scholar
Embrechts, P., Klueppelberg, C. & Mikosch, T. (1997). Modelling of extremal events for insurance and finance. Springer.CrossRefGoogle Scholar
Fox, N.J. (2005). Capability maturity model (RM-CMM) for risk management. http://www.siliconrose.com.au/Articles/RiskCMM.htmGoogle Scholar
FSA (2002). Operational risk systems and controls. Financial Services Authority.Google Scholar
FSA (2003a). The firm risk assessment framework. Financial Services Authority.Google Scholar
FSA (2003b). Enhanced capital requirements and individual capital assessments for non-life insurers. Financial Services Authority.Google Scholar
FSA (2003c). Integrated prudential sourcebook — near-final text on prudential risks systems and controls. Financial Services Authority.Google Scholar
GIRO (2002). Report of the Operational Risks Working Party to GIRO 2002.Google Scholar
GIRO (2003). Operational risk: measurement or bust. Report of the working party to GIRO 2003.Google Scholar
Hall, D.C. (2002). Using a risk management maturity-level model. Software Risk Magazine, Vol. 2, No. 4.Google Scholar
Hallock, Micah, Heintz, & Kourtney, (2001). Measuring operational risk. Bank Accounting and Finance, Vol. 14, Issue 4.Google Scholar
Higgs, (1996). Comparison of Myers Briggs type indicator profiles and Belbin team roles. Henley Management College.Google Scholar
Hoffman, D. (2002). Managing operational risk: 20 firmwide best practice strategies. John Wiley & Sons.Google Scholar
Institute of Actuaries. Claims reserving manual.Google Scholar
IRM (2002). A risk management standard. The Institute of Risk Management, ALARM (The National Forum for Risk Management in the Public Sector) and AIRMIC (The Association of Insurance and Risk Managers).Google Scholar
King, J.L. (2001). Operational risk: measurement and modelling. Wiley Finance.Google Scholar
Laycock, et al. (1998). Operational risks and financial institutions. Risk Publications/Arthur Andersen.Google Scholar
MacKenzie, D. & Millo, Y. (2001). Negotiating a market, performing theory: the historical sociology of a financial derivatives exchange. Paper presented at European Association for Evolutionary Political Economy conference, Siena, November 8-11, 2001.CrossRefGoogle Scholar
McDonnell, W. (2002a). Managing risk: practical lessons from recent ‘failures’ of E.U. insurers.Google Scholar
McDonnell, W. (2002b). Financial Services Authority occasional paper, 20 December 2002.Google Scholar
Muermann, A. & Oktem, U. (2002). The near-miss management of operational risk. The Journal of Risk Finance.Google Scholar
Netica (1997). NeticaTM users guide, Norsys Software Corporation, http://www.norsys.comGoogle Scholar
Pearl, J. (1988). Probabilistic reasoning in intelligent systems. Morgan Kaufmann.Google Scholar
Pyle, D.H. (1997). Bank risk management: theory. Paper presented at the Conference on Risk Management and Regulation in Banking, Jerusalem, May 17-19, 1997.Google Scholar
Quenk, N.L. (1999). Essentials of Myers-Brigss type indicator assessment. John Wiley & Sons Inc.Google Scholar
Risksig (2002). Risk management maturity level development. Risk Management Specific Interest Group. http://www.risksig.com/projects/report.htmlGoogle Scholar
Simons, R. (1999). How risky is your company? Harvard Business Review.Google Scholar