Exploring the Economic Impact of Banking Digitalization through Statistical and Computational Methods - Qarizada, Abdulkhaliq; Sazish, Baryali (Department of Informatics, Universitas Malikussaleh, 2026)
In the era of the Fourth Industrial Revolution, banking digitalization has emerged as a pivotal driver of economic development, fostering efficiency, financial inclusion, and technological innovation. The increasing adoption of mobile banking, online transactions, digital payment systems, and financial technologies (FinTech) has reshaped traditional financial systems and influenced macroeconomic outcomes such as GDP growth, investment, and employment. The purpose of this study is to systematically analyze the impact of banking digitalization on economic development, with a particular focus on the role of computational and machine learning techniques in assessing digital financial inclusion. A systematic literature review (SLR) methodology was employed, covering peer-reviewed studies published between 2020 and 2025. Relevant literature was retrieved from reputable databases including IEEE Xplore, ScienceDirect, Wiley Online Library, and MDPI, using keywords such as “banking digitalization,” “digital financial inclusion,” “economic development,” and “machine learning in banking.” The review process followed a transparent screening and selection protocol based on PRISMA guidelines, resulting in 21 studies that met the inclusion criteria. The selected studies employed a range of methodologies, including panel regression, Bayesian modeling, fuzzy multi-criteria decision-making (MCDM), artificial neural networks (ANN), and SEM–ANN hybrid approaches, allowing for comprehensive analysis of quantitative and computational perspectives. The results reveal that banking digitalization exerts a strong and positive influence on economic development. Digital financial inclusion significantly contributes to GDP growth, investment, and employment, particularly in emerging economies with supportive infrastructure and policies. Moreover, computational and machine learning techniques enhance the precision of evaluating digitalization impacts, enabling predictive insights into economic outcomes and labor market dynamics. In conclusion, banking digitalization serves as a transformative mechanism for promoting sustainable economic growth. Strategic investment in digital infrastructure, human capital development, and robust regulatory frameworks is essential to maximize the socioeconomic benefits of digital finance. The integration of advanced computational techniques further supports evidence-based decision-making, ensuring that digital banking contributes effectively to inclusive and resilient economic development.