AI-ENHANCED FRAUD DETECTION IN FINANCIAL WORKFLOWS: A HYBRID ML-LLM FRAMEWORK FOR RISK SCORING AND ANOMALY ANALYTICS
DOI:
https://doi.org/10.30890/2567-5273.2025-42-03-004Keywords:
fraud detection, risk scoring, financial workflows, machine learning (ML), large language models (LLM), real-time analytics, stream processing, semantic enrichment, explainable AI (XAI), latency and SLO, compliance, auditability.Abstract
The rapid expansion of cashless payments and instant transfers has intensified performance and transparency requirements for fraud detection. Decisions to block or approve transactions must be issued within milliseconds, without compromising accuracy, useReferences
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