The Impact of Structural and Technical Factors on the Efficiency of AI-Based Risk Management
A Field Study on FinTech Companies in Iraq
DOI:
https://doi.org/10.61704/pr.553Keywords:
FinTech, Risk Management, , Artificial Intelligence (AI), Data Quality, Institutional Trust, IraqAbstract
This study aims to diagnose the impact of structural factors (Data Quality and Integration) and technical factors (Technical Efficiency, Explainability) on the efficiency of risk management in Iraqi financial institutions, while testing the mediating role of "Institutional Trust". The study adopted a descriptive-analytical approach, collecting data via a questionnaire distributed to a purposive sample of (120) experts, including risk and IT managers in banks and FinTech payment companies in (Baghdad, Erbil, and Basra). Data were analyzed using Structural Equation Modeling (SmartPLS v.4). The results concluded that "Data Quality" is the most influential factor on risk management efficiency, outweighing algorithm complexity. Furthermore, the study proved that "Explainability" plays a crucial role in enhancing institutional trust, which positively mediates the relationship between technology and decision efficiency. The study recommends adopting a "Data-First" strategy and ensuring data cleansing before expanding into smart systems.
References
حسن، أحمد عبد الله. (2022). حوكمة البيانات وأثرها في دعم اتخاذ القرار المالي في المصارف. مجلة العلوم الاقتصادية والإدارية، 15(1).
رسول، بلند خالد خليل، والحيالي، يونس غازي رجب، وحسين، مروج طاهر هذال. (2024). دور الذكاء الاصطناعي في تطوير التكنولوجيا المالية في المؤسسات المالية: دراسة حالة مصرف العراق الأول (FIB). مجلة وارث العلمية.
عبد الله، عبد الرزاق فاضل، وعباس، عمر عبد الواحد. (2025). دور تقنيات الذكاء المالي المدعومة بـ FinTech في تحسين فعالية التخطيط الاستراتيجي المستدام في القطاع المصرفي. مجلة الجامعة العراقية، 73(8).
عبد الرزاق، نور صباح، وقاسم، مريم حمزة. (2023). التكنولوجيا المالية ودورها في تعزيز كفاءة الأداء المصرفي. مجلة دراسات محاسبية ومالية، 18(2).
علي، علياء مهدي. (2023). تأثير الذكاء الاصطناعي في جودة التقارير المالية وانعكاسه على متخذي القرار (رسالة ماجستير غير منشورة). كلية الإدارة والاقتصاد، جامعة كربلاء، العراق.
Agarwal, M., Pandey, B. K., Sofia, R., & Kumar, S. (2024). AI-driven risk management in financial markets and FinTech. In Proceedings of the 2024 Second International Conference on Computational and Characterization Techniques in Engineering & Sciences (IC3TES) (pp. 1–6). IEEE.
Arner, D. W., Barberis, J., & Buckley, R. P. (2017). FinTech and RegTech in a nutshell, and the future in a sandbox. Northwestern Journal of International Law & Business, 35(2).
Bains, P., Conde, G., Ravikumar, R., & Iskender, E. S. (2025). AI projects in financial supervisory authorities: A toolkit for successful implementation (IMF Working Paper No. WP/25/199). International Monetary Fund.
Basel Committee on Banking Supervision. (2023). Principles for the sound management of operational risk. Bank for International Settlements.
Bholat, D., et al. (2021). Enhancing financial stability with artificial intelligence (Bank of England Staff Working Paper No. 924). Bank of England.
Deloitte. (2024). Explainable AI in financial risk management. Deloitte Insights.
European Central Bank. (2024). Artificial intelligence and risk management in financial institutions (Occasional Paper). European Central Bank.
Financial Stability Board. (2024, November 14). The financial stability implications of artificial intelligence. Financial Stability Board.
Fuster, A., Goldsmith-Pinkham, P., Ramadorai, T., & Walther, A. (2019). Predictably unequal? The effects of machine learning on credit markets. Journal of Finance, 74(5).
Giudici, P. (2018). FinTech risk management: A research challenge for artificial intelligence in finance. Frontiers in Artificial Intelligence, 1(1).
KPMG. (2024). AI, trust, and risk management in financial services. KPMG International.
McKinsey & Company. (2023). The role of AI in risk management and compliance. McKinsey Global Institute.
OECD. (2023). Artificial intelligence, data governance and financial stability. OECD Publishing.
Rolando, B., & Mulyono, H. (2024). Risk management in FinTech: Applications and challenges of AI-based risk. Economics and Business Journal (ECBS), 5(1).
Roy, J. K., & Vasa, L. (2024). Machine learning and artificial intelligence methods for FinTech credit scoring and risk management: A systematic literature review. International Journal of Business Analytics, 11(1).
Ryll, L., & Seewald, K. (2020). Artificial intelligence in credit risk management. Journal of Risk Management in Financial Institutions, 13(3).
World Economic Forum. (2025, January). Artificial intelligence in financial services (White paper, in collaboration with Accenture). World Economic Forum.
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Copyright (c) 2026 Saif G. Yassin
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Copyright © 2025 by the authors. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0). You may not alter or transform this work in any way without permission from the authors. Non-commercial use, distribution, and copying are permitted, provided that appropriate credit is given to the authors and Al-Hadba University.
