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Comparative Study of Event-Driven Architectures in Financial Systems for Real-Time Risk Analysis and Mitigation

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  • Harsh Parnerkar

    (Software Engineer II, United States.)

Abstract

Event-driven architectures (EDAs) are now increasingly revolutionizing financial risk analytics through the substitution of batch-type systems with real-time monitoring. This article proposes comparative assessment of a Kafka–Flink pipeline and Temporal Risk Graphs (TRGs), Adaptive Model Orchestration (AMO), and Privacy-Preserving Stream Processing (P2SP). This reduces the latency in detecting by 85%–90% over batch processing, enhancing fraud detection accuracy and recall to 0.91 and 0.87, respectively. 40% less false positives, balanced accuracy and customer satisfaction. The system still maintains a throughput of 100,000 events per second, with under 200 ms p99 latency and 99.95% SLA adherence. The outcomes demonstrate that EDAs can retain speed, accuracy, and accountability, effectively managing persistent issues with micro-batch anomalies, model drift adaptability, and cross-domain integration in financial risk systems.

Suggested Citation

  • Harsh Parnerkar, 2025. "Comparative Study of Event-Driven Architectures in Financial Systems for Real-Time Risk Analysis and Mitigation," European Journal of Electrical Engineering and Computer Science, European Open Science, vol. 9(6), pages 46-54, November.
    • Handle: RePEc:epw:ejece0:v:9:y:2025:i:6:id:19761
    DOI: 10.24018/ejece.2025.9.6.761
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