When AI Acts Alone: Managing Systemic Risk in Agentic FinTech

Abstract

The accelerating integration of artificial intelligence (AI) into financial technology (FinTech) ecosystems has transformed the global financial landscape, enabling unprecedented levels of automation, efficiency, and personalization. However, as AI systems evolve from assistive tools into autonomous, decision-making agents—so-called agentic AI—they introduce novel systemic risks that challenge traditional financial regulation and oversight mechanisms. This paper examines how autonomous AI-driven systems within FinTech can amplify financial fragility through algorithmic interdependence, data asymmetries, and emergent feedback loops. Drawing on recent research and empirical evidence, the study highlights the paradoxical duality of AI in finance: its potential to enhance risk management while simultaneously increasing the scale and speed of systemic contagion. It explores key domains such as algorithmic trading, digital credit scoring, decentralized finance (DeFi), and RegTech, emphasizing the pathways through which AI autonomy can produce “too-connected-to-fail” dynamics and endogenous complexity. The paper further proposes a multi-layered governance framework integrating ethical AI principles, real-time systemic risk monitoring, and adaptive regulatory oversight. Ultimately, managing systemic risk in agentic FinTech requires a paradigm shift from static compliance models toward dynamic co-evolution between human regulators and autonomous systems—ensuring resilience in a financial environment increasingly governed by machines that think and act independently.