Disruptor or enabler? AI and financial system stability

Purpose The advent of artificial intelligence (AI) tools signifies a major advancement in technology, poised to significantly influence the financial system. From a conceptual standpoint, AI introduces both advantages and challenges to the financial landscape. Thus, this study aims to examine the dynamics between AI and financial system stability through several distinct approaches. Initially, the authors investigate potential nonlinearities in this relationship to assess the asymmetric reactions of financial system stability to the application of AI, both positive and negative. Design/methodology/approach Subsequently, to address intra-country variations, the authors incorporate a heterogeneous effect within the cross-sections by using a nonlinear panel autoregressive distributed lag model, which serves as a panel data adaptation of the Shin et al. (2014) framework and is comparable to the nonstationary heterogeneous panel data model. Findings The findings indicate that final system stability exhibits asymmetric responses to AI, with the latter displaying a more pronounced reaction. The results remain consistent across various AI proxies. Ultimately, the findings emanating from the study carry significant implications for financial system regulators. Originality/value This paper addresses gaps in the AI–financial stability literature by empirically examining the relationship internationally, where existing studies are limited. While some prior research (e.g. Daud et al., 2022; Li, 2021; Khan et al., 2023a) explores this globally, they do not fully account for nonlinearities and heterogeneity effects. To the best of the authors’ knowledge, this study is the first to use panel data to incorporate both aspects, offering a more comprehensive understanding of AI’s impact on financial stability. Doing so advances empirical knowledge beyond the largely theoretical, country-specific focus of earlier work (e.g. Darangwa, 2021; Chen and Du, 2016).