Financial stability with digital finance innovation: a BigQuery-based empirical investigation

Abstract

This study empirically explores how digital financial innovations (DFIs) drive financial stability with a BigQuery-based approach in measuring DFIs and a global analysis covering 74 countries in the 2002 – 2022 period. Specifically, this study measures DFIs by searching for patents related to DFIs, which are evaluated based on the abstract/title of the patent applications. The empirical result shows that DFIs are positively associated with financial stability. Furthermore, with the BigQuery-based approach, this study is also able to explore how different types of DFIs impact the stability of the financial system. Results show that DFIs in Payment, AI and Big Data, and Security and Regtech are significant and positively affect financial stability, while DFIs in Digital Banking and Blockchain technology lack statistical significance. Crucially, DFIs in AI and Big Data appear to have the most pronounced impact. The research findings are reinforced by multiple robustness checks, including endogeneity analysis with IV-2SLS, isolation of temporal shocks, non-linearities checks. Additionally, the heterogeneity analysis also shows that developing countries may benefit more from the stabilizing impacts of DFIs. From these findings, practically valuable implications can be drawn, shedding light on how to leverage DFIs to yield the highest effectiveness.