Mapping the Research Landscape of Artificial Intelligence and Machine Learning in Finance: A Bibliometric Analysis
DOI:
https://doi.org/10.53032/tvcr/2026.v8n2.19Keywords:
Artificial intelligence; Machine learning; Finance; Bibliometric analysis; Digital financeAbstract
The rapid advancements in Artificial Intelligence (AI) and Machine Learning (ML) technologies have profoundly impacted the financial sector, offering significant improvements in areas such as risk management, algorithmic trading, fraud detection, credit scoring, and customer service. Using Scopus, this study conducts a bibliometric review of research on artificial intelligence and machine learning in finance. A BibTeX dataset of 103 English articles and reviews (1996–2026) from Economics/ Econometrics/ Finance and Business/ Management/ Accounting was analysed to map growth, impact, and collaboration. Output remained sparse until 2017, then expanded rapidly, peaking in 2024–2025. The literature is highly collaborative and influential. Dominant themes include digital finance, risk management, and sustainability-oriented finance.
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