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Analysis of Machine Learning and Artificial Intelligence in Finance: Growth and New Trends

In: Advances in Quantitative Methods for Economics and Business

Author

Listed:
  • Muhammad Amin

    (NED University of Engineering & Technology)

  • Farhan Ahmed

    (NED University of Engineering & Technology)

  • Mirza Mehmood Baig

    (NED University of Engineering & Technology)

Abstract

The review paper exhibits the application and usefulness of machine learning (ML) and artificial intelligence (AI) state of art in the field of applied finance. Using the large volume of data, bibliometric review has been done. The published articles (in number 540) within the domain of economics and finance from the year 2010 to 2022 have been extracted from the core collection of Web of Science (WOS). VOSViewer—data visualization application has been operated for extracting; the trends in machine learning and/or artificial intelligence in finance, the most influential authors, the most influential documents, the most influential sources/journals, the most influential countries, the most influential organizations based on citations and the four research streams have also been developed for future research. The trend exhibits an inclination toward scholarly publications in the domain of bankruptcy, block chain, portfolio management, and anti-money laundering (AML). The top three countries contributors to the main research are the United States, China, and the United Kingdom. Our finding provides real-world guidance for the overall financial system (financial instruments, markets, institutions and central banks) on how to use AI and ML in decision-making for managing international finance.

Suggested Citation

  • Muhammad Amin & Farhan Ahmed & Mirza Mehmood Baig, 2025. "Analysis of Machine Learning and Artificial Intelligence in Finance: Growth and New Trends," Springer Books, in: Salvador Cruz Rambaud & Juan Evangelista Trinidad Segovia & Catalina B. García-García (ed.), Advances in Quantitative Methods for Economics and Business, chapter 0, pages 225-236, Springer.
    • Handle: RePEc:spr:sprchp:978-3-031-84782-0_11
    DOI: 10.1007/978-3-031-84782-0_11
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