Factors linking upper-middle- and high-income countries in terms of banking ecosystem digitalization: Cluster analysis

Type of the article: Research Article AbstractThe banking and financial system of the countries of the world is constantly developing, but at different rates and ways, given their differences in the levels of economic, financial, and innovation development. The purpose of this article is to identify factors that link upper-middle- and high-income countries in terms of banking ecosystem digitalization, based on cluster analysis. The research sample includes 40 countries – 20 top-performing upper-middle-income and 20 high-income economies – based on the 2023 ICT Development Index. The analysis is based on 15 standardized indicators characterizing digitalization in the banking ecosystem, sourced from the International Monetary Fund, the World Bank, and the International Telecommunication Union. These indicators cover ICT development, AI readiness, cybersecurity, GovTech maturity, financial development, banking access, and digital transaction activity. Data standardization was performed in Stata (v19.5) using the built-in function to create new variables with a mean of 0 and a standard deviation of 1. Cluster analysis was conducted using the k-means method in Statgraphics (v19), with silhouette scores computed in Python to determine the optimal number of clusters. Cluster analysis revealed four distinct country groups, demonstrating that similarities in banking ecosystem digitalization transcend income levels. Key convergence factors include ICT development, GovTech maturity, mobile banking adoption, and AI readiness. Some upper-middle-income countries exhibit digitalization patterns comparable to high-income economies, highlighting the role of strategic investment and policy, rather than income, as primary drivers of digital financial advancement.