Governing Autonomous Decision Authority: A Handoff-Threshold Framework for Agentic AI in Payment Infrastructure
Keywords:
agentic AI; payment infrastructure; autonomous CI/CD; real-time fraud decisioning; human-AI collaboration; AI governance; handoff threshold; NIST AI Risk Management Framework; bounded autonomy; escalation design; financial technology; responsible AI deploymentAbstract
Agentic AI systems now operate autonomously inside production payment infrastructure resolving CI/CD dependency conflicts, scoring transactions for fraud in real time, and managing the cadence of model deployment yet existing AI governance frameworks stop short of specifying a concrete, auditable mechanism for dividing decision authority between agent and human. This article addresses that gap directly. Drawing on practitioner experience operating agentic systems at global payment scale, we present a taxonomy of agentic deployment patterns in payment infrastructure, an architecture description of a layered real-time fraud-inference system, and a four-tier handoff-threshold governance framework full-autonomy, advisory-autonomy, confirm-before-act, and human-only mapped explicitly onto the NIST AI Risk Management Framework's Govern function and the human-oversight provisions of Article 14 of the EU AI Act. The framework turns what is otherwise an implicit, emergent boundary on agent authority into a documented control that risk and compliance functions can inspect and challenge.
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References
S. Russell and P. Norvig, Artificial Intelligence: A Modern Approach, 4th ed., Pearson, 2020.
M. Wooldridge, An Introduction to MultiAgent Systems, 2nd ed., John Wiley & Sons, 2009.
National Institute of Standards and Technology, Artificial Intelligence Risk Management Framework (AI RMF 1.0), U.S. Department of Commerce, 2023.
European Parliament and Council of the European Union, Regulation (EU) 2024/1689 (Artificial Intelligence Act), Article 14: Human Oversight, OJ L, 2024/1689, 12.7.2024.
U. Bhatt, A. Xiang, S. Sharma, et al., "Explainable machine learning in deployment," Proc. 2020 ACM Conf. on Fairness, Accountability, and Transparency (FAccT), pp. 648-657, 2020.
Financial Stability Board, The Financial Stability Implications of Artificial Intelligence, 2024.
International Organization of Securities Commissions (IOSCO), Artificial Intelligence in Capital Markets: Use Cases, Risks and Challenges, 2025.
U.S. Government Accountability Office, Artificial Intelligence: Use and Oversight in Financial Services, GAO-25-107197, 2025.
C. C. Nallapareddy, "Strategic Design with AI Agents, Predefined Workflows and Agentic AI," International Journal of Intelligent Systems and Applications in Engineering, vol. 13, no. 1, pp. 445-450, 2025.
T. B. Sheridan and W. L. Verplank, Human and Computer Control of Undersea Teleoperators, Man-Machine Systems Laboratory, MIT, 1978.
R. Parasuraman, T. B. Sheridan, and C. D. Wickens, "A model for types and levels of human interaction with automation," IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, vol. 30, no. 3, pp. 286-297, 2000.
SAE International, Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor Vehicles, J3016, 2021.
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