AI-Enhanced Early Warning Systems Under the EU Digital Markets Act: Automated Detection of Consumer-Reported Platform Violations
AI-Enhanced Early Warning Systems Under the EU Digital Markets Act: Automated Detection of Consumer-Reported Platform Violations

Author(s): Olusola Shedrack Agbebiyi
Subject(s): Social Sciences
Published by: Udruženje ekonomista i menadžera Balkana
Keywords: Digital Markets Act; Machine learning; Consumer intelligence; Platform regulation; Automated compliance
Summary/Abstract: This paper presents an AI enhanced early warning framework for monitoring compliance under the European Union’s Digital Markets Act (DMA). A fine tuned BERT model classifies consumer discussions into Article 6 violation types (self preferencing, bundling, discrimination, interoperability restriction) and combines results with community level statistical validation. On Reddit data (n = 82; 2020–2025), the classifier achieved 86.2% accuracy and macro F1 = 0.84; community validation averaged 0.86 with Z = 2.99 (p < 0.01). Projected operational costs decrease by ~90% relative to manual monitoring. The framework provides a reproducible, low cost pipeline for proactive DMA surveillance aligned with Articles 5, 6, 19, and 20 and supports prioritization of investigations through confidence weighted alerts.

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