EFFECT OF ARTIFICIAL INTELLIGENCE ON BANKING STABILITY: EVIDENCE FROM DEVELOPING COUNTRIES

Abstract

The rapid adoption of artificial intelligence in the banking industry has generated critical concerns regarding its implications for banking stability, particularly in under-developed and institutionally constrained economies. This study examines the relationship between artificial intelligence adoption and banking stability, while incorporating the moderating influence of institutional quality and the potential risks associated with artificial intelligence implementation. The objective is to determine whether technological advancement strengthens financial resilience or introduces new vulnerabilities within fragile regulatory environments. A quantitative, cross-sectional research design was employed, and primary survey data were collected from 350 banking professionals operating in under-developed and lower-middle-income countries. The empirical findings reveal that artificial intelligence adoption is positively and significantly associated with banking stability. This suggests that advanced technological systems enhance banks’ risk management practices, improve operational efficiency, and strengthen resilience against financial shocks. By facilitating predictive analytics, automated monitoring, and more accurate credit evaluation processes, artificial intelligence appears to contribute to improved stability outcomes in banking institutions. Institutional quality also demonstrates a significant positive relationship with banking stability. Strong governance mechanisms, effective regulatory oversight, and transparent institutional frameworks contribute directly to financial system robustness. Furthermore, institutional quality is positively related to artificial intelligence adoption, indicating that supportive regulatory environments and governance structures play an essential role in enabling successful technological integration within banks. In contrast, risks associated with artificial intelligence do not show a statistically significant impact on banking stability in this study. Although concerns such as cybersecurity threats, algorithmic bias, and operational disruptions are recognized, their direct effect on stability appears limited within the observed sample. This may indicate that banks have implemented sufficient safeguards to mitigate these risks or that the stabilizing benefits of artificial intelligence outweigh its potential drawbacks.