Exploring the dual relationship between fintech and financial inclusion in developing countries and their impact on economic growth: Supplement or substitute?

Abstract

This study rigorously examines the complex interplay between financial technology (Fintech), financial inclusion, and their collective effects on economic growth in developing nations. Employing a robust panel regression methodology enhanced by Panel-Corrected Standard Errors (PCSE) and Feasible Generalized Least Squares (FGLS) techniques, this research analyzes an extensive dataset comprising 108 countries categorized into low, lower-middle, and upper-middle income levels across four pivotal years (2011, 2014, 2017, and 2021). Our analysis focuses on two key dimensions of Fintech-specifically, the adoption of digital payments and e-commerce via mobile technologies-and traditional financial access indicators, including the density of ATMs, bank branches, and active banking accounts. The findings demonstrate a predominantly positive effect of Fintech variables on economic growth, particularly through improved digital payment systems. Conversely, traditional financial inclusion metrics frequently show a negative correlation with growth trajectories. Notably, our research underscores a significant positive interaction between digital payment usage and ATM density, indicating a synergistic relationship that enhances the performance of traditional banking systems. In contrast, a substitutability effect arises, where increased dependence on mobile technologies diminishes the relevance of traditional financial infrastructure, potentially obstructing broader economic growth. These findings carry critical policy implications, advocating for a cohesive strategy that fosters both Fintech innovations and traditional financial sectors to maximize economic growth and inclusivity. A deliberate emphasis on synchronizing innovative financial solutions with the strengthening of conventional banking is essential for promoting sustainable economic development in these resource-constrained regions.