FinTech, artificial intelligence, and European Union banks: A double-edged sword for performance?

作者
Marian Siminică,Daniel Cîrciumaru,Alina Georgiana Manta,Silviu Cârstina,Gabriela Badareu,Claudia Gherțescu
出处
期刊:Oeconomia Copernicana [Institute of Economic Research, Polish Economic Society Branch in Toruń, Faculty of Economic Sciences and Management at Nicolaus]
卷期号:16 (3): 1099-1176
标识
DOI:10.24136/oc.3798
摘要

Research background: The ongoing digital transformation within the European Union's banking sector, driven by the adoption of financial technologies (FinTech) and artificial intelli-gence (AI), has introduced substantial opportunities for enhancing operational efficiency, customer service personalization, and financial outreach. However, these innovations also generate strategic complexity, intensify competition from non-bank digital entrants, and create disparities in adaptation capacity across financial institutions. Despite a growing body of literature on this topic, empirical investigations remain limited regarding how these technologies differentially affect banks, based on their existing performance levels. Purpose of the article: This study examines the extent to which FinTech and AI integration influences financial performance across banks in all 27 EU member states. Specifically, it investigates whether these technological drivers yield uniform effects or whether their impact varies across banks depending on their baseline performance. The analysis is grounded in the premise that FinTech and AI are not inherently per-formance-enhancing and that their effects may depend on context, capacity, and strategy. Methods: Employing a panel quantile regression model, the analysis is based on a balanced panel dataset spanning the 2017–2023 period. To address both short- and long-term dynamics, the study complements its core estimation with a vector error correction model (VECM) and validates the robustness of findings through sys-tem-based regression techniques. The econometric framework incorporates bank-specific instruments and lagged performance metrics, with a particular focus on return on equity (ROE) as the dependent variable. Findings & value added: The results indicate that the adoption of FinTech and AI is associated with signif-icant improvements in performance metrics, particularly among well-capitalized or technologically agile banks. However, institutions with weaker fundamentals may experience limited or even adverse effects. These findings suggest that the performance implications of innovation are conditional, not universal. The paper contributes by offering a distribution-sensitive analysis that refines our under-standing of technological transformation in EU banking and provides actionable insights into strategic decision-making and regulatory oversight. Also, the results offer practical implications for bank executives considering strategic technology investments, as well as for regulators aiming to design supportive, risk-sensitive digital finance policies.
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