An Artificial Intelligence-Supported Sociological Analysis: The Relationship Between Financial Exclusion and Inequality in Access to Banking Services in Turkiye

This study examines the relationship between provincial-level financial infrastructure indicators—including the number of branches, ATMs, POS devices, and member businesses—and income inequality in Türkiye from a sociological perspective. Drawing on Pierre Bourdieu’s concepts of capital and field, the research utilises 81-province data provided by the Banks Association of Türkiye and the Turkish Statistical Institute (TBB) and the Turkish Statistical Institute (TUIK). Methodologically, the study employs random forest regression, K-means, and DBSCAN clustering methods, alongside SHAP values and visual analytics, to map regional disparities. The findings reveal a distinct spatial dimension to financial infrastructure concentration, which acts as a structural factor reflecting regional imbalances and social inequalities. Notably, SHAP analyses indicate that the number of bank branches and ATMs exerts the strongest impact on the Gini coefficient, with Istanbul emerging as an extreme outlier compared to the remaining 80 provinces. This strong correlation between physical/digital financial infrastructure and higher inequality underscores that financial concentration is a critical reflection of both economic and social disparities. Based on these correlational insights, the study outlines exploratory directions for policymakers, highlighting the potential value of data-driven, context-specific strategies that address both supply- and demand-side factors while explicitly acknowledging the inferential limitations inherent in cross-sectional data. Ultimately, implementing a macro-level interventional financial reform package could enhance regional infrastructure investments, improve digital financial literacy, and foster multi-dimensional financial inclusion.