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Modernising operational risk management in financial institutions via data-driven causal factors analysis: A pre-registered report

Author

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  • Cornwell, Nikki
  • Bilson, Christopher
  • Gepp, Adrian
  • Stern, Steven
  • Vanstone, Bruce J.

Abstract

To enable more proactive management of the underlying sources of operational risks in financial institutions, this pre-registered study seeks to improve traditional qualitative approaches to causal factors analysis. A Bayesian network-based approach is used to leverage both incident and operations data to model the probability of operational loss events. The approach is applied and empirically tested in a case study on an Australian insurance company. The outputs from the model go beyond simply identifying key risk drivers to offer risk managers a deeper understanding of how causal factors influence risk. Insights into the collective effects of causal factors, their relative importance and critical thresholds strategically inform more efficient and effective mitigation decisions, ultimately enhancing firm performance and value.

Suggested Citation

  • Cornwell, Nikki & Bilson, Christopher & Gepp, Adrian & Stern, Steven & Vanstone, Bruce J., 2023. "Modernising operational risk management in financial institutions via data-driven causal factors analysis: A pre-registered report," Pacific-Basin Finance Journal, Elsevier, vol. 77(C).
  • Handle: RePEc:eee:pacfin:v:77:y:2023:i:c:s0927538x22002013
    DOI: 10.1016/j.pacfin.2022.101906
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    References listed on IDEAS

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    1. Robert W. Faff & Tom Smith, 2015. "A simple template for pitching research," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 55(2), pages 311-336, June.
    2. Robert S. Kaplan & Anette Mikes, 2016. "Risk Management—the Revealing Hand," Harvard Business School Working Papers 16-102, Harvard Business School.
    3. Georges Dionne, 2013. "Risk Management: History, Definition, and Critique," Risk Management and Insurance Review, American Risk and Insurance Association, vol. 16(2), pages 147-166, September.
    4. Chernobai, Anna & Jorion, Philippe & Yu, Fan, 2011. "The Determinants of Operational Risk in U.S. Financial Institutions," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 46(6), pages 1683-1725, December.
    5. Andrew Sanford & Imad Moosa, 2015. "Operational risk modelling and organizational learning in structured finance operations: a Bayesian network approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 66(1), pages 86-115, January.
    6. Chiungfeng Ko & Picheng Lee & Asokan Anandarajan, 2019. "The impact of operational risk incidents and moderating influence of corporate governance on credit risk and firm performance," International Journal of Accounting & Information Management, Emerald Group Publishing Limited, vol. 27(1), pages 96-110, March.
    7. Stefan Mittnik & Irina Starobinskaya, 2010. "Modeling Dependencies in Operational Risk with Hybrid Bayesian Networks," Methodology and Computing in Applied Probability, Springer, vol. 12(3), pages 379-390, September.
    8. Aven, Terje, 2016. "Risk assessment and risk management: Review of recent advances on their foundation," European Journal of Operational Research, Elsevier, vol. 253(1), pages 1-13.
    9. Timothy A Krause & Yiuman Tse, 2016. "Risk management and firm value: recent theory and evidence," International Journal of Accounting & Information Management, Emerald Group Publishing Limited, vol. 24(1), pages 56-81, March.
    10. Vincent T. Covello & Jeryl Mumpower, 1985. "Risk Analysis and Risk Management: An Historical Perspective," Risk Analysis, John Wiley & Sons, vol. 5(2), pages 103-120, June.
    11. Gerry Dickinson, 2001. "Enterprise Risk Management: Its Origins and Conceptual Foundation*," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 26(3), pages 360-366, July.
    12. Huang, Jinbo & Ding, Ashley & Li, Yong & Lu, Dong, 2020. "Increasing the risk management effectiveness from higher accuracy: A novel non-parametric method," Pacific-Basin Finance Journal, Elsevier, vol. 62(C).
    13. Martin Neil & Norman Fenton & Manesh Tailor, 2005. "Using Bayesian Networks to Model Expected and Unexpected Operational Losses," Risk Analysis, John Wiley & Sons, vol. 25(4), pages 963-972, August.
    14. repec:cup:jfinqa:v:46:y:2011:i:06:p:1683-1725_00 is not listed on IDEAS
    15. Alexander J. McNeil & Rüdiger Frey & Paul Embrechts, 2015. "Quantitative Risk Management: Concepts, Techniques and Tools Revised edition," Economics Books, Princeton University Press, edition 2, number 10496.
    16. Scutari, Marco, 2010. "Learning Bayesian Networks with the bnlearn R Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 35(i03).
    17. Robert S. Kaplan & Anette Mikes, 2016. "Risk Management—the Revealing Hand," Journal of Applied Corporate Finance, Morgan Stanley, vol. 28(1), pages 8-18, March.
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    Cited by:

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    3. Cornwell, Nikki & Bilson, Christopher & Gepp, Adrian & Stern, Steven & Vanstone, Bruce J., 2023. "Modernising operational risk management in financial institutions via data-driven causal factors analysis: A pre-registered study," Pacific-Basin Finance Journal, Elsevier, vol. 79(C).

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    More about this item

    Keywords

    Risk management; Operational risk; Data analytics; Firm value; Financial institutions; Insurance;
    All these keywords.

    JEL classification:

    • G20 - Financial Economics - - Financial Institutions and Services - - - General
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory

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