This study examines the relationship between financial inclusion and economic development in the European Union by analyzing its macroeconomic determinants across 26 countries over the period of 2004–2023. Using a balanced panel dataset, the empirical analysis employs econometric techniques that account for heterogeneity, autocorrelation, and cross-sectional dependence, leading to the estimation of a Panel-Corrected Standard Errors (PCSE) model. Financial inclusion is proxied by the number of automated teller machines per 100,000 adults, while the explanatory variables include GDP per capita, personal remittances, inflation, years of schooling, unemployment, and foreign direct investment. The results show that GDP per capita, remittances, inflation, and unemployment have a positive and statistically significant effect on financial inclusion, whereas education and foreign direct investment exhibit a negative and significant relationship. These findings suggest that financial inclusion in the European Union is shaped by a complex interplay of economic development, labor market conditions, and external financial flows, rather than by structural factors alone. Notably, the results reveal counterintuitive relationships that challenge conventional assumptions about the roles of education and foreign investment in promoting financial access. This study contributes to the literature by providing updated panel evidence for advanced economies and by emphasizing the multidimensional nature of financial inclusion in a context of increasing digitalization and economic integration. The findings also offer relevant policy implications, suggesting that strategies to enhance financial inclusion should go beyond expanding financial infrastructure and instead focus on improving the effective use of financial services, strengthening financial capabilities, and reducing structural disparities across countries.

La presente investigación busca abordar la relación entre el endeudamiento y la rentabilidad financiera del Sector Automotriz de la provincia de Tungurahua en el periodo 2015-2020. Se utilizaron fuentes secundarias, por medio de la base de datos de la Superintendencia de Compañías, Valores y Seguros. De la misma manera, la metodología que se empleó fue Z de Altman y correlación de Pearson, que se utilizó para medir la relación entre las dos variables. Entre los principales resultados obtenidos se determina que a través de los años el endeudamiento ha ido disminuyendo considerablemente. Así mismo, la rentabilidad financiera se ha ido reduciendo, esto se debe a problemas externos que ocurrieron en el país. Finalmente, se analizaron las medias de los indicadores de rentabilidad y endeudamiento y se concluyó que en el 2016 y 2020 existe una correlación positiva media, es decir, se tiene que el rendimiento financiero por parte de las empresas fue logrado gracias al financiamiento con proveedores y entidades financieras.