Conceptual analysis uncovers emerging systemic financial risks in banking networks driven by autonomous AI agents, highlighting the need for complex-systems supervision frameworks.
Agentic artificial intelligence systems — models that plan, invoke tools, retain memory, and execute multi-step actions with limited human supervision — have moved from experimental pilots to production infrastructure inside major banks and trading firms during 2025-2026. This monograph argues that the systemic-risk consequences of this shift cannot be understood through financial regulation alone, nor through computer-science accounts of agent architecture alone: they require a complex-systems lens that treats interaction topology, cognitive opacity, and objective divergence among autonomous agents as structural properties of the financial network itself. [...] This is a conceptual and analytical work; it does not report new empirical estimation and should be read as a synthesis and framework-building exercise, not as a validated predictive model.
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Alfredo Merlet (2026) studied this question.
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