Fintech Start-up Innovation: Thematic and Bibliometric Analysis of Embedded Finance and AI Trends Using VosViewer

Abstract

Objective: This study aims to identify and map the main trends in FinTech literature from 2015 to 2025, particularly those related to embedded finance and artificial intelligence (AI).
Research Design & Methods: Adopting an exploratory qualitative approach, this study focuses on literature and bibliometric analysis. Data was collected from the Scopus database, with additional literature from Google Scholar as a supplementary source, covering publications from 2015 to 2025 using the keywords fintech, AI, embedded finance, and trust.
Findings: VOSviewer analysis places fintech as a central node with major clusters covering AI & risk management, embedded finance, user trust, regulation, financial inclusion, and blockchain. Since 2019, publications on “Fintech AI” have surged significantly, while “Embedded Finance AI” shows a declining trend due to its integration into general FinTech. AI drives efficiency and risk mitigation, embedded finance simplifies financial services, and trust and adaptive regulation issues remain key focuses.
Implications & Recommendations: These findings highlight the importance of redefining digital trust, responsible AI governance, and collaboration between startups and banks. Regulators need to adopt a principle-based adaptive approach.
Contribution & Value Added: This research offers data-driven strategic references for academics, startups, and regulators, and serves as a foundation for further empirical studies using innovative combined methodological approaches.