Technology-Driven Finance and Inclusive Credit Assessment: Bibliometric Evidence and Insights from the Human Economic Forum

The increasing integration of digital technologies into financial and economic systems is reshaping the relationship between business performance, access to finance, and social impact. In line with recent critiques of value creation mechanisms in contemporary economies, this paper investigates how data-driven financial tools and technologically enabled evaluation frameworks may contribute to more inclusive and human-centered economic outcomes, with particular attention to small and medium-sized enterprises (SMEs). The study adopts a twofold methodological approach. First, a bibliometric analysis of academic literature indexed in major databases is conducted to map the evolution of research streams related to digital finance, financial inclusion, social impact, and alternative credit assessment models. The results highlight a growing yet fragmented body of research addressing the integration of social value into financial decision-making, while revealing a significant gap in the systematic exploration of social credit mechanisms as instruments of inclusive finance. Second, the paper develops a qualitative case study focused on the Human Economic Forum (HEF), interpreted as a conceptual and institutional laboratory promoting economic models grounded in human-centered and service-oriented logics. Within this framework, the study examines the concept of social credits as a complementary tool to traditional credit scoring systems. Social credits are analyzed as mechanisms capable of incorporating behavioral, social, and community-based indicators into financial evaluations, thereby reducing informational asymmetries and enhancing access to finance. The findings suggest that when technological innovation is combined with agile organizational frameworks and human-centered evaluation criteria, financial systems can evolve beyond efficiency-driven paradigms toward more socially responsible and inclusive models. By integrating bibliometric evidence with an applied case study, this paper contributes to the ongoing debate on digital finance and social impact, offering relevant implications for financial institutions, policymakers, and ecosystem actors.