AI-Driven Real-Time Transaction Monitoring and Automated Threat Response: Revolutionizing Payment Security

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.

Authors

Publication Details

Journal
International Journal on Science and Technology
Published
2025-03-22
DOI
https://doi.org/10.71097/ijsat.v16.i1.2718
Primary Topic
Network Security and Intrusion Detection
Type
article
Field-Weighted Citation Impact
0.00
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article

AI-Driven Real-Time Transaction Monitoring and Automated Threat Response: Revolutionizing Payment Security

Sandeep Jarugula
International Journal on Science and Technology
Network Security and Intrusion Detection
article

AI-Driven Real-Time Transaction Monitoring and Automated Threat Response: Revolutionizing Payment Security

Sandeep Jarugula
article en

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.

International Journal on Science and TechnologyVol. 16(1)
Openalex Percentile: Top 95%
Network Security and Intrusion Detection
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AI-Driven Real-Time Transaction Monitoring and Automated Threat Response: Revolutionizing Payment Security — Sandeep Jarugula · International Journal on Science and Technology (2025) | TGRS Research Map | TGRS