Layered detection of tampered identity documents in electronic know-your-customer systems: A conceptual framework

Abstract

Identity fraud constitutes one of the most consequential threats confronting digital financial ecosystems, with sophisticated document falsification techniques undermining the foundational trust upon which regulatory compliance and consumer protection depend. This paper examines the effectiveness of electronic Know-Your-Customer (e-KYC) systems in detecting tampered identity documents and proposes an original conceptual framework designed to address persistent detection gaps. The inquiry proceeds through a structured, conceptual and analytical review of extant scholarship across information security, digital identity verification, and financial technology regulation, integrating insights from signal detection theory and risk-based authentication models to construct a theoretically grounded response to an underexplored problem. The proposed framework comprises four interacting layers: document authenticity verification, biometric integrity assessment, contextual risk scoring, and an adaptive decision engine. Three principal propositions are advanced. It is argued, first, that the integration of multimodal forensic analysis within e-KYC pipelines substantially reduces false-negative rates for tampered document detection. Second, that contextual risk signals, including behavioural biometrics, device intelligence, and geolocation anomalies, augment static document verification in a manner that individually neither modality can achieve. Third, that adaptive machine learning architectures capable of continuous recalibration offer a more durable defence against adversarial manipulation than rule-based heuristic systems. These findings carry significant implications for financial institutions navigating obligations under the Financial Action Task Force recommendations, Basel Committee guidance, and the European General Data Protection Regulation. By synthesising dispersed technical and regulatory literatures into a unified analytical model, this paper contributes to a nascent but critical area of scholarship at the intersection of cybersecurity, fintech governance, and digital trust architecture.