Real-Time Fraud on Real-Time Rails: An AI “Smart Circuit Breaker” for Securing Instant Payments
DOI:
https://doi.org/10.7190/fintaf.v3i1.503Keywords:
Artificial intelligence, AI-powered Banking, Fraud Prevention, Anomaly Detection, ISO 20022Abstract
The launch of instant payment rails (RTP, FedNow) introduces a new, fundamental business risk: irrevocability. In this T+0, 24/7 world, the legacy T+1 security architectures that are built on static rules and batch processing are architecturally mismatched to manage this risk. Fraudulent payment is no longer an operational issue to be "fixed"; it is an immediate, irreversible financial loss.
This paper proposes that Artificial Intelligence is a viable path forward and introduces an AI-driven "smart circuit breaker" as a native component of the core payment flow, not a simple "bolt-on."
This model becomes feasible through the rich, structured data of ISO 20022, enabling real-time contextual analysis and anomaly detection before settlement. This is not just a technical upgrade; it forces boardroom-level discussions on strategic trade-offs:
- Balancing customer friction from false positives.
- Justifying the ROI on new data infrastructure.
- Solving the "explainability" (XAI) hurdle for auditors.
The paper concludes that properly architected AI is not a cost center but a critical trust enabler—and a competitive advantage for secure, reliable instant payments.
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Copyright (c) 2026 Senthil Nathan
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