Hyper-Personalization in Digital Financial Services: Integrating Medallion Architecture, Generative AI, and Responsible Data Governance for Next-Generation Wealth Management

Abstract

Hyper-personalization has emerged as a defining paradigm in contemporary wealth management and digital financial services, driven by rapid advances in artificial intelligence, big data analytics, and scalable data architectures. Traditional personalization approaches, largely rule-based and segmentation-driven, are increasingly inadequate in addressing the growing complexity of client expectations, regulatory pressures, and real-time decision-making requirements. This research article develops a comprehensive theoretical and conceptual examination of hyper-personalization in wealth management ecosystems, grounded strictly in the existing scholarly literature on Medallion Architecture, generative artificial intelligence, Internet of Things-enabled data streams, explainable AI, dynamic pricing models, and data governance frameworks. Drawing upon prior research, the article elaborates how layered data architectures enable scalable, auditable, and compliant personalization, while generative AI and reinforcement learning extend personalization from reactive recommendation systems to proactive, context-aware financial advisory services. Particular attention is devoted to the regulatory and ethical dimensions of personalization, including data privacy, transparency, and accountability, with reference to GDPR-compliant AI-driven marketing and explainable recommendation systems. Using a qualitative, theory-building methodological approach, the study synthesizes insights across information systems, financial technology, and business intelligence research to articulate a unified model of hyper-personalized wealth management. The findings suggest that sustainable competitive advantage in financial services increasingly depends on the alignment of advanced analytics capabilities with responsible data practices and transparent decision-making mechanisms. The article contributes to academic discourse by bridging architectural, algorithmic, and governance perspectives, while offering strategic implications for financial institutions navigating the transition toward intelligent, client-centric digital ecosystems.