Data-Based Intuition: Financial Decision-Making Under Risk and Uncertainty

This paper introduces data-based intuition, a framework for understanding how financial judgment develops through accumulated quantitative and qualitative analysis. It defines data-based intuition as the capacity to make context-sensitive financial judgments grounded in such analysis rather than instinct alone. The framework views financial decision-making as a recursive learning process: data inform analysis, analysis contributes to experience and judgment, and decisions and outcomes provide new information for subsequent assessment. Because financial relationships are contingent and may change, both analytical conclusions and intuitive judgments are fallible and open to revision. The paper develops this conceptual framework by connecting research on financial decision-making with work on expertise, intuition, and learning. Its central contribution is to explain how data-based intuition develops and operates in financial expertise, while clarifying the complementary roles of analysis, experience, and judgment. The framework also identifies conditions under which accumulated experience may support or weaken later judgments and offers a basis for future empirical research.