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A Theoretical Framework for Operational Risk Management and Opportunity Realisation

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Advanced probability models are used to evaluate risks and to justify decisions where reliable data is available, e.g. reinsurance, money markets and nuclear energy. Operational risk management – the trade-offs made to run an efficient and effective organisation – has much less, and lower quality, data. In the first part of the paper, observations are made about the factors shaping operational risk management: the increasing shift of influence from tangible to intangible variables; the intuitive manner in which most operational risk is managed; the dynamic nature of the trade-offs balancing risk and reward; and in particular, that the critical factor in managing risk and opportunity is often how each choice feels rather than how a rational choice should be made. An economic framework is then used to examine the optimal relationship between operational risk and reward. Although operational risk management has many investment characteristics, players are bias towards minimising risks rather than maximising opportunities. This is because of uncertainty over the variables, and better knowledge of costs than rewards. The conclusion is that an overt, systematic approach to managing operational risk will be more effective and efficient than allowing an informal, intuitive process to operate. This requires that assumptions and the judgement process must be made explicit; that the value of intangibles should be appreciated; and that the knowledge gained by individuals in managing risk should be codified and retained by the host organisation.

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  • Adrian Sparrow, 2000. "A Theoretical Framework for Operational Risk Management and Opportunity Realisation," Treasury Working Paper Series 00/10, New Zealand Treasury.
  • Handle: RePEc:nzt:nztwps:00/10
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    File URL: https://treasury.govt.nz/sites/default/files/2007-10/twp00-10.pdf
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    Cited by:

    1. Yuqian Xu & Lingjiong Zhu & Michael Pinedo, 2020. "Operational Risk Management: A Stochastic Control Framework with Preventive and Corrective Controls," Operations Research, INFORMS, vol. 68(6), pages 1804-1825, November.

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