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Assessing operational risk in the financial sector, using interdependency metrics

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  • Macaulay, Tyson

Abstract

Alternatives are needed to using intuition as the dominant approach for assessing critical infrastructure interdependencies. Since there is no single, measurable unit that accurately reflects interdependencies between critical infrastructure sectors, an interdependency metric must be a composite of measurable elements related to the dependency of one sector on another. This paper defines and applies quantitative and qualitative metrics, derived from the US financial sector, to assess its interdependencies with other sectors. The quantitative metric engages econometric data about the value of goods and services flowing between the financial sector and other critical infrastructure sectors. The qualitative data dependency metric is derived from financial sector executives’ opinions on the criticality of data and information flows between their companies and other sectors. The econometric and data dependency metrics are shown to possess strong correlations, and a composite interdependency metric is generated from the two metrics. The composite metric is then applied to understand the cascading impacts of disruptions in the financial sector.

Suggested Citation

  • Macaulay, Tyson, 2008. "Assessing operational risk in the financial sector, using interdependency metrics," International Journal of Critical Infrastructure Protection, Elsevier, vol. 1(C), pages 45-52.
  • Handle: RePEc:eee:ijocip:v:1:y:2008:i:c:p:45-52
    DOI: 10.1016/j.ijcip.2008.08.008
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    Cited by:

    1. Singh, Abhishek Narain & Gupta, M.P. & Ojha, Amitabh, 2014. "Identifying critical infrastructure sectors and their dependencies: An Indian scenario," International Journal of Critical Infrastructure Protection, Elsevier, vol. 7(2), pages 71-85.
    2. Laugé, Ana & Hernantes, Josune & Sarriegi, Jose M., 2015. "Critical infrastructure dependencies: A holistic, dynamic and quantitative approach," International Journal of Critical Infrastructure Protection, Elsevier, vol. 8(C), pages 16-23.
    3. Lo, Huai-Wei & Liou, James J.H. & Huang, Chun-Nen & Chuang, Yen-Ching & Tzeng, Gwo-Hshiung, 2020. "A new soft computing approach for analyzing the influential relationships of critical infrastructures," International Journal of Critical Infrastructure Protection, Elsevier, vol. 28(C).

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