Artificial Intelligence as a Catalyst for Banker Knowledge Development: Econometric Evidence From South Asian Financial Markets And Economic Growth Dynamics

This study constitutes the first systematic econometric investigation into whether the deployment of artificial intelligence for banker knowledge enhancement exerts a statistically significant, causal influence on credit intermediation efficiency, financial inclusion depth, and aggregate economic growth across the eight sovereign economies of South Asia. Drawing exclusively on publicly disclosed macroeconomic, financial sector, and technology adoption data spanning the period 2000 to 2023, a novel composite index of AI-augmented banking knowledge intensity (AABKI) is constructed and embedded within a panel data framework comprising fixed-effects, random-effects, and dynamic Generalised Method of Moments (GMM) estimators. Three foundational hypotheses are advanced and empirically evaluated: first, that AI-mediated knowledge diffusion within banking institutions constitutes an autonomous, hitherto unrecognised driver of credit-to-GDP ratio growth, independent of conventional financial development determinants; second, that the marginal effect of AI banking knowledge intensity on financial inclusion is heterogeneous across income strata and geographic regions within South Asia, thereby generating a novel distributional channel through which technology shapes economic convergence; and third, that the interaction between regulatory institutional quality and AI banking knowledge adoption generates nonlinear threshold effects on long-run economic growth that existing theoretical frameworks have not articulated. Empirical results confirm all three hypotheses at conventional significance levels. The AABKI index is positively and robustly associated with domestic credit depth (beta = 0.347, p < 0.01), financial inclusion breadth (beta = 0.289, p < 0.01), and real GDP per capita growth (beta = 0.214, p < 0.05), with threshold nonlinearities identified at a regulatory quality score of 0.62 on the World Governance Indicators scale. These findings carry profound implications for central bank policy, SAARC-level financial integration strategy, and the design of AI governance frameworks for emerging market banking systems. JEL Classification: G21, O33, O53, C23, G28, F36, O16