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Artificial Intelligence & Machine Learning in Finance: A literature review

Author

Listed:
  • Wassima Lakhchini

    (Université Hassan 1er [Settat], ENCGS - Ecole Nationale de Commerce et de Gestion de SETTAT)

  • Rachid Wahabi

    (Université Hassan 1er [Settat])

  • Mounime El Kabbouri

    (Université Hassan 1er [Settat])

Abstract

In the 2020s, Artificial Intelligence (AI) has been increasingly becoming a dominant technology, and thanks to new computer technologies, Machine Learning (ML) has also experienced remarkable growth in recent years; however, Artificial Intelligence (AI) needs notable data scientist and engineers' innovation to evolve. Hence, in this paper, we aim to infer the intellectual development of AI and ML in finance research, adopting a scoping review combined with an embedded review to pursue and scrutinize the services of these concepts. For a technical literature review, we goose-step the five stages of the scoping review methodology along with Donthu et al.'s (2021) bibliometric review method. This article highlights the trends in AI and ML applications (from 1989 to 2022) in the financial field of both developed and emerging countries. The main purpose is to emphasize the minutiae of several types of research that elucidate the employment of AI and ML in finance. The findings of our study are summarized and developed into seven fields: (1) Portfolio Management and Robo-Advisory, (2) Risk Management and Financial Distress (3), Financial Fraud Detection and Anti-money laundering, (4) Sentiment Analysis and Investor Behaviour, (5) Algorithmic Stock Market Prediction and High-frequency Trading, (6) Data Protection and Cybersecurity, (7) Big Data Analytics, Blockchain, FinTech. Further, we demonstrate in each field, how research in AI and ML enhances the current financial sector, as well as their contribution in terms of possibilities and solutions for myriad financial institutions and organizations. We conclude with a global map review of 110 documents per the seven fields of AI and ML application.

Suggested Citation

  • Wassima Lakhchini & Rachid Wahabi & Mounime El Kabbouri, 2022. "Artificial Intelligence & Machine Learning in Finance: A literature review," Post-Print hal-03916744, HAL.
    • Handle: RePEc:hal:journl:hal-03916744
    DOI: 10.5281/zenodo.7454232
    Note: View the original document on HAL open archive server: https://hal.science/hal-03916744
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    References listed on IDEAS

    as
    1. Donthu, Naveen & Kumar, Satish & Mukherjee, Debmalya & Pandey, Nitesh & Lim, Weng Marc, 2021. "How to conduct a bibliometric analysis: An overview and guidelines," Journal of Business Research, Elsevier, vol. 133(C), pages 285-296.
    2. Antoncic, Madelyn, 2020. "A paradigm shift in the board room: Incorporating sustainability into corporate governance and strategic decision-making using big data and artificial intelligence," Journal of Risk Management in Financial Institutions, Henry Stewart Publications, vol. 13(4), pages 290-294, September.
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    Keywords

    Artificial Intelligence; Machine Learning; Finance; Scoping review;
    All these keywords.

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