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Considerations Related To The Application Of Deep Learning And Neural Networks In Finance And Banking. A Bibliometric Approach

Author

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  • Daniela Iulia Maria Carbune

    (University of Craiova ”Eugeniu Carada” Doctoral School of Economic Sciences, Romania)

Abstract

The aim of this paper is to examine the impact and applications of Deep Learning (DL) and Neural Networks (NN) in financial markets and especially on banking markets, using a bibliometric analysis based on 970 articles published between 2015-2024. The study highlights key trends, collaboration networks and influential contributions using data extracted from the Web of Science database and analyzed with VOSviewer software. Findings illustrate the widespread integration of those two AI applications in financial approaches such as credit evaluation, stock market forecasting and risk modeling. The study highlights the prominence of areas such as computer science and business economics while pointing out the need for hybrid models and explainable AI, essential for meeting regulatory compliance. Additionally, it emphasizes the interdisciplinary nature of this field, connecting AI with big data and financial systems.

Suggested Citation

  • Daniela Iulia Maria Carbune, 2024. "Considerations Related To The Application Of Deep Learning And Neural Networks In Finance And Banking. A Bibliometric Approach," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(2), pages 480-488, December.
    • Handle: RePEc:ovi:oviste:v:xxiv:y:2024:i:2:p:480-488
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    More about this item

    Keywords

    deep learning; neural networks; banking; bibliometric analysis; VOSviewer;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G20 - Financial Economics - - Financial Institutions and Services - - - General
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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