AI-Orchestrated Payment Intelligence Systems for Improving Transaction Efficiency and Reducing Operational Latency in FinTech Gateways
Keywords:
Transaction Efficiency, Operational Latency, AI Orchestration, Payment Intelligence, Real-Time Analytic, Digital Banking, Payment Systems, Intelligent Routing, Hybrid AIAbstract
This study proposes a robust AI-orchestrated payment intelligence system aimed at enhancing transaction efficiency and minimizing operational latency in FinTech gateways. The model integrates predictive analytics, real-time stream processing, and automated anomaly detection to dynamically adjust payment workflows based on system load, user behavior, and fraud probability. A hybrid architecture involving machine learning and rule-based engines is implemented to manage payment routing, currency conversion, and gateway selection. Experimental evaluation across simulated payment environments demonstrates a 38% improvement in throughput and a 47% reduction in processing latency, without compromising data security. This research highlights the importance of AI orchestration as the next frontier in digital financial operations.
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