Advancing Financial Inclusion for Small and Medium Enterprises through Generative AI Frameworks in the United States

Aim: This study examines the role of generative AI in enhancing financial inclusion among Small and Medium Enterprises (SMEs) in the United States. It explores the potential of AI- driven frameworks in mitigating financial constraints, improving credit accessibility, and streamlining financial processes for SMEs.

Study Design: A systematic review of literature published between 2019 and 2024 was conducted to assess the impact of generative AI technologies on financial services for SMEs. The study specifically focuses on digital lending innovations, AI-driven credit assessment strategies, and their role in advancing financial inclusion.

Methodology: The study employed a systematic literature review approach, sourcing peer- reviewed journal articles and reports from Google Scholar, Scopus, IEEE Xplore, and SSRN. Articles were selected based on their direct relevance to generative AI applications in financial inclusion and SME development in the United States. Only studies that explicitly addressed AI-driven financial solutions for SMEs were included in the review.

Results: The findings reveal that generative AI has significantly contributed to reducing financial exclusion among SMEs. Key applications such as automated credit scoring, fraud detection, and AI-powered financial advisory services have shown high potential in improving credit access, operational efficiency, and risk management. However, the adoption of these technologies faces critical challenges, including data privacy concerns, ethical issues, and high implementation costs.

Conclusions: Generative AI has the potential to drive financial inclusion for SMEs in the United States by expanding access to financial services and improving credit assessment methodologies. However, addressing barriers to adoption requires collaborative efforts among policymakers, financial institutions, and technology developers to ensure equitable access, ethical implementation, and long-term sustainability of AI-driven financial solutions.