Adaptive RegTech Architectures for Real-Time Compliance in Modernized Financial Transaction Systems
Keywords:
Adaptive Rule Engine, Anti-Money Laundering, Event-Driven Architecture, Financial Transaction Monitoring, Real-Time Compliance, RegTechAbstract
Regulatory compliance in financial transaction systems has historically depended on batch-processing architectures that accumulate transaction records over defined intervals before applying rule-based inspection. Adequate for an era of infrequent regulatory examination and slower-moving financial crime, this model has become misaligned with a regulatory environment that now mandates continuous monitoring, near-real-time reporting, and immediate corrective action capability. This article proposes the Adaptive RegTech Architecture (ARA), a principled framework for achieving genuine real-time compliance in institutions operating hybrid infrastructure — specifically, organizations whose transaction processing cores remain mainframe-resident while compliance obligations require modern event-driven capabilities. The ARA is organized around four design principles: compliance layer decoupling via event-driven interfaces, event primacy as the authoritative source for compliance evaluation, unified graph-based entity identity management, and adaptive machine learning-augmented rule engines. Implementation patterns are examined for hybrid mainframe environments, including Change Data Capture integration, synchronous pre-authorization screening, and federated cross-border deployment. Applications across Anti-Money Laundering (AML), Customer Due Diligence (CDD), and FATCA reporting domains are analyzed. The ARA is positioned as an architecture-level reference model — distinct from vendor-specific RegTech products and high-level regulatory guidance — addressing a demonstrable gap in compliance modernization literature for institutions with significant legacy infrastructure investment.
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