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Navigating the Decision-making Landscape of AI in Risk Finance: Techno-Accountability Unveiled

Author

Listed:
  • Helmi Issa

    (BSB - Burgundy School of Business (BSB) - ESC Dijon-Bourgogne, CEREN - Centre de Recherche sur les Entreprises - BSB - Burgundy School of Business (BSB) - ESC Dijon-Bourgogne)

  • Roy Dakroub
  • Hussein Lakkis
  • Jad Jaber

Abstract

The integration of AI systems has ushered in a profound transformation. This conversion is marked by revolutionary extrapolative capabilities, a shift towards data-centric decision-making processes, and the enhancement of tools for managing risks. However, the adoption of these AI innovations has sparked controversy due to their unpredictable and opaque disposition. This study employs the transactional stress model to empirically investigate how six technological stressors (techno-stressors) impact both techno-eustress (positive stress) and techno-distress (negative stress) experienced by finance professionals and experts. To collect data for this research, an e-survey was distributed to a diverse group of 251 participants from various sources. The findings, particularly the identification and development of techno-accountability as a significant factor, contributes to the risk analysis domain by improving the Failure Mode and Effect Analysis (FMEA) framework to better fit the rapidly evolving landscape of AI-driven innovations.

Suggested Citation

  • Helmi Issa & Roy Dakroub & Hussein Lakkis & Jad Jaber, 2025. "Navigating the Decision-making Landscape of AI in Risk Finance: Techno-Accountability Unveiled," Post-Print hal-05799088, HAL.
    • Handle: RePEc:hal:journl:hal-05799088
    DOI: 10.1111/risa.14336
    as

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