ISSN 2308-8559 e-ISSN 2415-8224
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https://doi.org/10.62763/ef/1.2026.08

Volume 16, No. 1, 2026

8-18

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    • Agentic Artificial Intelligence in financial and banking operations: A comprehensive review

    Laith Haleem Al-Hchemi

    Received 12.11.2025, Revised 19.02.2026, Accepted 26.03.2026 Published 01.04.2026

    Abstract

    The purpose of the study was to review of academic and industry literature, with the goal of clarifying the concept of agentic Artificial Intelligence, explaining its architectural workings, and exploring its applications in the financial and banking sectors. The rising use of Artificial Intelligence in the financial services sector had been pushing into a stage of financial automation that was not focused on rules but on systems able to reason, adapt, and act autonomously and goal-focused. This transition had led to what was currently referred to as agentic Artificial Intelligence – a category of intelligent systems that worked independently to a certain extent, which was missing in conventional Artificial Intelligence applications. The research was based on the systematic review methodology, which summarised the evidence related to the use of agentic Artificial Intelligence in autonomous trading, dynamic risk assessment, algorithmic underwriting, fraud detection, customised customer interaction, and regulatory compliance. As the analysis showed, it increased operational proactivity, situational awareness, and multi-step decision-making, allowing financial institutions to be more responsive to complex and fast-changing environments. In addition, the review outlined that there were persistent issues in regard to explainability, accountability, integration with legacy infrastructures, ethical protection, and preparedness to regulatory issues. Results suggested that agentic Artificial Intelligence had the potential ability to transform operational and strategic activities in the financial sector, but only by means of responsible governance and strict supervision, its advantages can become actual. The contribution of this review to the literature was an evidence-based integrated evaluation of the modern trends and an outline of the most prominent opportunities and limitations that will define the future of autonomous intelligent systems in the financial services

    Keywords:

    artificial agents; autonomous finance; digital banking; financial innovations; financial algorithm

    Suggested citation
    Al-Hchemi, L.H. (2026). Agentic Artificial Intelligence in financial and banking operations: A comprehensive review. Economic Forum, 16(1), 8-18. https://doi.org/10.62763/ef/1.2026.08
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    References

    1. Amin, M.S., Ayon, E.H., Ghosh, B.P., Chowdhury, M.S., Bhuiyan, M.S., Jewel, R.M., & Linkon, A.A. (2024). Harmonizing macro-financial factors and Twitter sentiment analysis in forecasting stock market trends. Journal of Computer Science and Technology Studies, 6(1), 58-67.‏ doi: 10.32996/jcsts.2024.6.1.7.
    2. Brohi, S., Mastoi, Q.-ul-ain, Jhanjhi, N.Z., & Pillai, T.R. (2025). A research landscape of agentic AI and large language models: Applications, challenges and future directions. Algorithms, 18(8), article number 499. doi: 10.3390/a18080499‏.
    3. Chitturi, N. (2025). Agentic Artificial Intelligence: Architectural paradigms and transformative impact of autonomous financial assistants across the mortgage lending lifecycle. Journal of Computer Science and Technology Studies, 7(8), 1155-1165. doi: 10.32996/jcsts.2025.7.8.131.
    4. CoinLaw. (n.d.). Retrieved from https://coinlaw.io/.
    5. Dodda, A. (2024). Integrating advanced and agentic AI in Fintech: Transforming payments and credit card transactions. European Advanced Journal for Emerging Technologies, 1(1). doi: 10.5281/zenodo.15962919.
    6. Dutta, C., Karpman, K., Basu, S., & Ravishanker, N. (2023). Review of statistical approaches for modeling high-frequency trading data. Sankhya B, 85, 1-48.‏ doi: 10.1007/s13571-022-00280-7.
    7. Elgendy, I.A., Helal, M.Y.I., Al-Sharafi, M.A., Albashrawi, M.A., Al-Ahmadi, M.S., Jeon, I.I., & Dwivedi, Y.K. (2025). Agentic systems as catalysts for innovation in FinTech: Exploring opportunities, challenges and a research agenda. Information Discovery and Delivery. doi: 10.1108/IDD-03-2025-0068.
    8. Gangavarapu, R. (2025). AI governance: Preparing for the rise of agentic AI. In Mastering AI governance (pp. 111-119). Cham: Springer.‏ doi: 10.1007/978-3-031-93681-4_12.
    9. Garg, V. (2025). Designing the mind: How agentic frameworks are shaping the future of AI behavior. Journal of Computer Science and Technology Studies, 7(5), 182-193.‏ doi: 10.32996/jcsts.2025.7.5.24.
    10. George, A.S. (2024). Finance 4.0: The transformation of financial services in the digital age. Partners Universal Innovative Research Publication, 2(3), 104-125.‏ doi: 10.5281/zenodo.11666694.
    11. Grand View Research. (n.d.). Home. Retrieved from https://www.grandviewresearch.com/.
    12. Huang, K. (Ed.) (2025). Agentic AI: Theories and practices (progress in IS). Cham: Springer.
    13. Huang, K., Wu, D., Ponnapalli, J., & Huang, G. (2025). AI agents in banking. In K. Huang (Ed.), Agentic AI (pp. 237-277). Cham: Springer. doi: 10.1007/978-3-031-90026-6_8.
    14. Hughes, L., Dwivedi, Y.K., Li, K., Appanderanda, M., Al-Bashrawi, M.A., & Chae, I. (2025). AI agents and agentic systems: Redefining global IT management. Journal of Global Information Technology Management, 28(3), 175-185. doi: 10.1080/1097198X.2025.2524286.
    15. Inala, R. (2023). AI-powered investment decision support systems: Building smart data products with embedded governance controls. Journal for ReAttach Therapy and Developmental Diversities, 6(10), 2251-2266. doi: 10.53555/jrtdd.v6i10s(2).3671.
    16. Inala, R., & Somu, B. (2025). Building trustworthy agentic AI systems for personalized banking experiences. Metallurgical and Materials Engineering, 31(5), 1336-1360. doi: 10.63278/mme.vi.1714.
    17. Jindal, G. (2024). The role of finance tech in revolutionizing traditional banking systems through data science and AI. Journal of Applied Sciences, 4(11), 10-21.‏ doi: 10.5281/zenodo.14057654.
    18. Jo, H., Bui, H., & Moreland, D. (2025). The role of AI in fraud detection: Are financial institutions using the most effective systems? Journal of Finance Issues, 23(2), 1-31. doi: 10.58886/jfi.v23i2.10086.
    19. Joshi, S. (2025). A comprehensive review of Gen AI agents: Applications and frameworks in finance, investments and risk domains. International Journal of Innovative Science and Research Technology, 10(5), 1339-1355. doi: 10.38124/ijisrt/25may964.
    20. Luqman, M., Gauba, H., Kumar, P., Desai, A.P., Yadav, A., Prajapati, R., & Yadav, P. (2025). Agentic AI in finance: A comprehensive overview. In Proceedings of the KDD 2025 workshop on agentic AI for enterprise: Emerging applications and real-world challenges. New York: ACM.
    21. Mucsková, M. (2024). Transforming banking with Artificial Intelligence: Applications, challenges, and implications. Trends Economics and Management, 42(1), 21-37. doi: 10.13164/trends.2024.42.21.
    22. Onabowale, O. (2025). The rise of AI and robo-advisors: Redefining financial strategies in the digital age. International Journal of Research Publication and Reviews, 6(1), 4832-4848.‏ doi: 10.55248/gengpi.6.0125.0640.
    23. OpenText. (n.d.). Secure information management for AI. Retrieved from https://www.opentext.com/.
    24. Paleti, S. (2022). Adaptive AI in banking compliance: Leveraging agentic AI for real-time KYC verification, anti-money laundering (AML) detection, and regulatory intelligence. Migration Letters, 19(6), 1253-1267.
    25. Pappil Kothandapani, H. (2025). AI-driven regulatory compliance: Transforming financial oversight through large language models and automation. Emerging Science Research, 3, 12-24.‏ doi: 10.6084/m9.figshare.28251608.v1.
    26. Quantified Strategies. (n.d.). Learn how to find, develop, and backtest trading strategies. Retrieved from https://www.quantifiedstrategies.com/.
    27. Sapkota, R., Roumeliotis, K.I., & Karkee, M. (2026). AI agents vs. agentic AI: A conceptual taxonomy, applications and challenges. Information Fusion, 126, article number 103599. doi: 10.1016/j.inffus.2025.103599.
    28. Somu, B. (2024). Agentic AI and financial compliance: Autonomous systems for regulatory monitoring in banking. European Data Science Journal, 2(1). doi: 10.5281/zenodo.15969238.
    29. Springs. (n.d.). Custom AI compliance solutions for enterprises. Retrieved from https://springsapps.com/.
    30. Sriram, H.K., & Somu, B. (2025). Beyond automation: Exploring the potential of agentic AI in risk management and fraud detection in banks. Eksplorium, 46(1), 192-220.
    31. Svetlova, E. (2022). AI ethics and systemic risks in finance. AI and Ethics, 2, 713-725.‏ doi: 10.1007/s43681-021-00129-1.
    32. Topraklı, A.Y. (2025). AI-driven valuation: A new era for real estate appraisal. Journal of European Real Estate Research, 18(1), 105-120.‏ doi: 10.1108/JERER-04-2024-0031.
    33. Vuković, D.B., Dekpo-Adza, S., & Matović, S. (2025). AI integration in financial services: A systematic review of trends and regulatory challenges. Humanities and Social Sciences Communications, 12, article number 562. doi: 10.1057/s41599-025-04850-8.
    34. Vyas, B. (2023). Java in action: AI for fraud detection and prevention. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 9(6), 58-69.‏ doi: 10.32628/CSEIT239063.
    35. Yordanova, Z., & Hristozov, Y. (2025). The evolution of financial analysis: From manual methods to AI and AI agents. Economics, 13(3), 219-239. doi: 10.2478/eoik-2025-0063.