AI-Driven Real-Time Transaction Monitoring and Automated Threat Response: Revolutionizing Payment Security
Year: 2025
Type: article
Abstract: The integration of AI and automation technologies is fundamentally transforming payment security in financial institutions worldwide. As transaction volumes grow and fraud techniques become more sophisticated, traditional rule-based systems and manual processes are being replaced by intelligent systems capable of real-time monitoring and automated threat response. These advanced systems operate through behavioral analysis, pattern recognition, contextual assessment, and anomaly detection to identify potential fraud with unprecedented accuracy while reducing false positives. Automated response mechanisms implement graduated interventions based on risk levels, balancing security with customer experience. Despite challenges in data quality, latency management, and regulatory explainability requirements, financial institutions are pioneering solutions through collaborative data sharing, edge computing architectures, and explainable AI frameworks. Emerging innovations including federated learning, quantum-resistant cryptography, and behavioral biometrics point to continued evolution in this critical domain, creating a security ecosystem that adapts and learns continuously to protect the global financial infrastructure.
Author: Sandeep Jarugula -
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4408884055