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Uncertainty Reduction in Operational Risk Management Process

Author

Listed:
  • Guy Burstein

    (Department of Industrial Engineering & Management, Ariel University, Ariel 40700, Israel)

  • Inon Zuckerman

    (Department of Industrial Engineering & Management, Ariel University, Ariel 40700, Israel)

Abstract

This paper proposes a new framework to reduce the variance and uncertainty in the risk assessment process. Today, this process is susceptible to background noise from sources of human factor biases and erroneous measurements. Our new framework consists of deconstructing the likelihood of failure function into its sub-factor and then reconstructing it in a formula that can reduce the variance and biases of a human auditor judgment. We tested our new framework on both a questionnaire study and a simulation of the risk assessment process, and the improvement in reducing the variance is significant.

Suggested Citation

  • Guy Burstein & Inon Zuckerman, 2024. "Uncertainty Reduction in Operational Risk Management Process," Risks, MDPI, vol. 12(5), pages 1-12, May.
    • Handle: RePEc:gam:jrisks:v:12:y:2024:i:5:p:77-:d:1392610
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    References listed on IDEAS

    as
    1. Michael Todorov Todinov, 2017. "Reducing Risk by Segmentation," International Journal of Risk and Contingency Management (IJRCM), IGI Global, vol. 6(3), pages 27-46, July.
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