Purpose- FinTech represents all innovation related to how businesses seek to improve the process, delivery, and use of financial services and it is not a mere technological phenomenon. Considering that the various innovations in the financial and technological fields require the use of explanatory indices, the aim of this work is to propose an analysis of the factors that influence the degree of adoption of Fintech in the European countries.
Methodology- We use a correlation model in order to highlight the first results on the relationship between the degree of Fintech at a geographical level and some explanatory variables. The final sample consists of 28 European countries that have all variables requested in the analyisis. Specifically, the level of Fintech is measured by The Global Fintech Index developed by Findexable, while the factors that influence the Fintech come from dataset of International Monetary Fund (IMF): the number of ATMs, number of commercial bank branches, while the intensity of outstanding deposits with commercial banks and outstanding loans from commercial banks is lower
Findings- Regarding the analysis of the year 2021, our result indicates preliminarily that Fintech is negatively affected by the number of ATMs, number of commercial bank branches, while the intensity of outstanding deposits with commercial banks and outstanding loans from commercial banks is lower. This findings are consistent with this assumption: one of the driver of the Fintech is the digitalization.
Conclusion- The result of our model indicates that the degree of Fintech at a geographical leve seems to be linked to explanatory variables that are related to the banking world. This represents a useful information to academic, practitioners and policymakers. In fact, according to literature, Fintech has an effect on financial system and financial stability. Therefore the explanation of Fintech phenomenon and its measurement represent a crucial point. Future extensions of research could consider additional measures of Fintech and a focus on the most representative explanatory variables.
Primary Language | English |
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Subjects | Business Administration |
Journal Section | Articles |
Authors | |
Publication Date | January 15, 2024 |
Submission Date | November 15, 2023 |
Acceptance Date | January 15, 2024 |
Published in Issue | Year 2023 Volume: 18 Issue: 1 |
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