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Artificial intelligence and machine learning in finance: A bibliometric review

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Cited by:

  1. Goodell, John W. & Oriani, Marco Ercole & Paltrinieri, Andrea & Patel, Ritesh, 2023. "The importance of ABS 2 journals in finance scholarship: Evidence from a bibliometric case study," Finance Research Letters, Elsevier, vol. 55(PA).
  2. Awijen, Haithem & Ben Zaied, Younes & Ben Lahouel, Béchir & Khlifi, Foued, 2023. "Machine learning for US cross-industry return predictability under information uncertainty," Research in International Business and Finance, Elsevier, vol. 64(C).
  3. Minghao Zhou & Wenhao Lai, 2023. "Coal gangue recognition based on spectral imaging combined with XGBoost," PLOS ONE, Public Library of Science, vol. 18(1), pages 1-15, January.
  4. Darko B. Vuković & Senanu Dekpo-Adza & Stefana Matović, 2025. "AI integration in financial services: a systematic review of trends and regulatory challenges," Palgrave Communications, Palgrave Macmillan, vol. 12(1), pages 1-29, December.
  5. Anica-Popa Liana-Elena & Vrîncianu Marinela & Petrică Papuc Iuliana-Mădălina, 2023. "AI – powered Business Services in the Hyperautomation Era," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 17(1), pages 1036-1050, July.
  6. Ren, Yi-Shuai & Ma, Chao-Qun & Kong, Xiao-Lin & Baltas, Konstantinos & Zureigat, Qasim, 2022. "Past, present, and future of the application of machine learning in cryptocurrency research," Research in International Business and Finance, Elsevier, vol. 63(C).
  7. Oliveira, Alexandre Silva de & Ceretta, Paulo Sergio & Albrecht, Peter, 2023. "Performance comparison of multifractal techniques and artificial neural networks in the construction of investment portfolios," Finance Research Letters, Elsevier, vol. 55(PA).
  8. Alena Vagaská & Miroslav Gombár & Antonín Korauš, 2022. "Mathematical Modeling and Nonlinear Optimization in Determining the Minimum Risk of Legalization of Income from Criminal Activities in the Context of EU Member Countries," Mathematics, MDPI, vol. 10(24), pages 1-25, December.
  9. Gupta, Somya & Ghardallou, Wafa & Pandey, Dharen Kumar & Sahu, Ganesh P., 2022. "Artificial intelligence adoption in the insurance industry: Evidence using the technology–organization–environment framework," Research in International Business and Finance, Elsevier, vol. 63(C).
  10. Chen, Dangxing & Ye, Jiahui & Ye, Weicheng, 2023. "Interpretable selective learning in credit risk," Research in International Business and Finance, Elsevier, vol. 65(C).
  11. Paul Handro & Bogdan Dima, 2024. "Analyzing Financial Markets Efficiency: Insights from a Bibliometric and Content Review," Journal of Financial Studies, Institute of Financial Studies, vol. 16(9), pages 119-175, May.
  12. Jewel Kumar Roy & László Vasa, 2024. "Machine Learning and Artificial Intelligence Method for FinTech Credit Scoring and Risk Management: A Systematic Literature Review," International Journal of Business Analytics (IJBAN), IGI Global, vol. 11(1), pages 1-23, January.
  13. Li Xian Liu & Zhiyue Sun & Kunpeng Xu & Chao Chen, 2024. "AI-Driven Financial Analysis: Exploring ChatGPT’s Capabilities and Challenges," IJFS, MDPI, vol. 12(3), pages 1-35, June.
  14. Costola, Michele & Hinz, Oliver & Nofer, Michael & Pelizzon, Loriana, 2023. "Machine learning sentiment analysis, COVID-19 news and stock market reactions," Research in International Business and Finance, Elsevier, vol. 64(C).
  15. Ayed Alwadain & Rao Faizan Ali & Amgad Muneer, 2023. "Estimating Financial Fraud through Transaction-Level Features and Machine Learning," Mathematics, MDPI, vol. 11(5), pages 1-15, February.
  16. Wang, Liang & Li, Munan, 2024. "An exploration method for technology forecasting that combines link prediction with graph embedding: A case study on blockchain," Technological Forecasting and Social Change, Elsevier, vol. 208(C).
  17. P. V. Thayyib & Rajesh Mamilla & Mohsin Khan & Humaira Fatima & Mohd Asim & Imran Anwar & M. K. Shamsudheen & Mohd Asif Khan, 2023. "State-of-the-Art of Artificial Intelligence and Big Data Analytics Reviews in Five Different Domains: A Bibliometric Summary," Sustainability, MDPI, vol. 15(5), pages 1-38, February.
  18. Evangelos Liaras & Michail Nerantzidis & Antonios Alexandridis, 2024. "Machine learning in accounting and finance research: a literature review," Review of Quantitative Finance and Accounting, Springer, vol. 63(4), pages 1431-1471, November.
  19. HUO, Peng & WANG, Luxin, 2022. "Digital economy and business investment efficiency: Inhibiting or facilitating?," Research in International Business and Finance, Elsevier, vol. 63(C).
  20. Wang, Dan & Chen, Zhi & Florescu, Ionuţ & Wen, Bingyang, 2023. "A sparsity algorithm for finding optimal counterfactual explanations: Application to corporate credit rating," Research in International Business and Finance, Elsevier, vol. 64(C).
  21. González, Marta Ramos & Ureña, Antonio Partal & Fernández-Aguado, Pilar Gómez, 2023. "Forecasting for regulatory credit loss derived from the COVID-19 pandemic: A machine learning approach," Research in International Business and Finance, Elsevier, vol. 64(C).
  22. Yasmeen Ansari & Mansour Saleh Albarrak & Noorjahan Sherfudeen & Arfia Aman, 2022. "A Study of Financial Literacy of Investors—A Bibliometric Analysis," IJFS, MDPI, vol. 10(2), pages 1-16, May.
  23. Gang Kou & Yang Lu, 2025. "FinTech: a literature review of emerging financial technologies and applications," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-34, December.
  24. Antonio Carlos Alcázar-Blanco & José Francisco Rangel-Preciado & Fiama Portillo-Santos, 2024. "Incorporating Artificial Intelligence into Finance: A Bibliometric Analysis," JRFM, MDPI, vol. 17(12), pages 1-14, December.
  25. Pavlos I. Zitis & Stelios M. Potirakis & Alex Alexandridis, 2024. "Forecasting Forex Market Volatility Using Deep Learning Models and Complexity Measures," JRFM, MDPI, vol. 17(12), pages 1-22, December.
  26. Robert Kudelić & Tamara Šmaguc & Sherry Robinson, 2025. "Artificial intelligence in the service of entrepreneurial finance: knowledge structure and the foundational algorithmic paradigm," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-43, December.
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