Machine learning analysis of digital financial inclusion: Identifying determinants, barriers, and sustainability links

Digital financial inclusion is increasingly recognized as a catalyst for economic development and sustainability, yet significant adoption barriers persist, particularly in conflict-affected and developing contexts like Palestine. This study addressed the critical knowledge gap regarding the specific drivers and impediments to digital financial service uptake in this unique environment . This study is one of the first to apply machine learning to analyze the determinants of digital financial inclusion in the unique, under-researched context of Palestine. Utilizing primary survey data from 148 respondents in Jenin Governorate, West Bank, we employ L2-penalized (Ridge) logistic regression to overcome methodological challenges inherent in the data. The application of this technique proved effective by successfully managing model instability and multicollinearity, which hindered standard regression models, thereby robustly identifying key predictors of mobile banking adoption. The findings reveal a distinct digital divide, confirming that while basic account ownership is relatively high, factors such as reliable mobile internet access, pre-existing banking relationships, male gender, younger age, higher education, and higher income significantly enable mobile banking use. Conversely, older age, lower education, rural residency, female gender, and surprisingly, higher statement-based financial literacy present substantial barriers in the multivariate model suggesting a 'paradox of knowledge' where risk awareness may deter adoption. Notably, this paper contributes vital context-specific empirical evidence for Palestine and demonstrates the utility of machine learning for generating reliable insights in challenging research settings, and provides actionable, evidence-based policy recommendations focused on infrastructure enhancement, targeted literacy programs, and addressing geographic/demographic disparities to foster inclusive and sustainable financial development.