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An analysis of operational risk events in US and European Banks 2008–2014

Published online by Cambridge University Press:  20 February 2017

Yifei Li ,
Neil Allan  and
John Evans
Yifei Li
Affiliation:
Sydney Business School, University of Wollongong, Level 9, 1 Macquarie Place, Sydney 2000, Australia
Neil Allan
Affiliation:
Systems Centre, Bristol University, 4 Bridge Yard, Bradford on Avon, BA15 1NX, UK
John Evans*
Affiliation:
Centre for Analysis of Complex Financial Systems, PO Box 363, Summer Hill, Australia
*
*Correspondence to: John Evans, Centre for Analysis of Complex Financial Systems, PO Box 363, Summer Hill, Australia. Tel: +614 1464 3658. E-mail: [email protected]
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Abstract

This paper explores the characteristics of 2,141 operational risk events amongst European (EU) and US banks over the period 2008–2014. We have analysed the operational risk events using a method originating in biology for the study of interrelatedness of characteristics in a complex adaptive system. The methodology, called cladistics, provides insights into the relationships between characteristics of operational risk events in banks that is not available from the traditional statistical analysis. We have used cladistics to explore if there are consistent patterns of operational risk characteristics across banks in single and different geographic zones. One significant pattern emerged which indicates there are key, stable characteristics across both geographic zones and across banks in each zone. The results identify the characteristics that could then be managed by the banks to reduce operational risk losses. We also have analysed separately the characteristics of operational risk events for “big” banks and extreme events and these results indicate that big banks and small banks have similar key operational risk characteristics, but the characteristics of extreme operational risk events are different to those for the non-extreme events.

Keywords

Operational riskRisk managementComplex adaptive systemCladistics analysis
Type
Papers
Information
Annals of Actuarial Science , Volume 11 , Issue 2 , September 2017 , pp. 315 - 342
Copyright
© Institute and Faculty of Actuaries 2017 

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