Financial institutions face an unprecedented imperative to transform their operational logic from product-centric models to data-driven architectures, yet existing digital transformation frameworks remain dominated by technology adoption perspectives that fail to theorize data as a core strategic production factor. This conceptual paper proposes a data-based view (DBV) framework—integrating the resource-based view, dynamic capabilities theory, and the DIKW hierarchy—to explain how financial institutions systematically transform data from a raw resource into strategic capital. The framework comprises four interconnected layers: Data Foundation (multi-source heterogeneous data acquisition and governance), Dynamic Capability (AI-powered analytical and algorithmic capabilities), Value Realization (the pathway from data assetization to data capitalization), and Organizational Wisdom (strategic decision-making at the apex of the DIKW pyramid). Regulatory compliance is theorized as a moderating variable that can exert both constraining (compliance drag) and catalyzing (compliance push) effects on the data-to-capital transformation process. We develop six testable propositions that specify the framework’s core relationships and provide directions for future empirical research. The DBV framework contributes to digital transformation scholarship by shifting analytical focus from technology adoption to data-driven strategic resource logic, while offering practical guidance for banking practitioners navigating digital transformation within tightly regulated environments.