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Minimise model risk management oversight for cyber security solutions

Author

Listed:
  • Brotcke, Liming

    (Ally Financial, USA)

Abstract

Adoption of artificial intelligence (AI) and machine learning (ML)-powered cyber security tools and models by financial institutions has received considerable attention in the model risk management community. In parallel, developing trustworthy AI that is more explainable, fair, robust, private and transparent has also received considerable research and regulatory attention. Appropriate governing of cyber security models is inevitable. The prevailing thought at present is to have the model risk management function to oversee the development, implementation and use of such cyber security tools and models. This study first demonstrates two primary challenges of executing this oversight and then offers a few practical suggestions to ensure a reasonable application.

Suggested Citation

  • Brotcke, Liming, 2023. "Minimise model risk management oversight for cyber security solutions," Journal of AI, Robotics & Workplace Automation, Henry Stewart Publications, vol. 3(1), pages 55-63, September.
    • Handle: RePEc:aza:airwa0:y:2023:v:3:i:1:p:55-63
    as

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    More about this item

    Keywords

    cyber security; data science; model validation; machine learning;
    All these keywords.

    JEL classification:

    • M15 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - IT Management
    • G2 - Financial Economics - - Financial Institutions and Services

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