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Deep learning in finance and banking: A literature review and classification

Author

Listed:
  • Jian Huang

    (The Hong Kong University of Science and Technology)

  • Junyi Chai

    (BNU-HKBU United International College)

  • Stella Cho

    (BNU-HKBU United International College)

Abstract

Deep learning has been widely applied in computer vision, natural language processing, and audio-visual recognition. The overwhelming success of deep learning as a data processing technique has sparked the interest of the research community. Given the proliferation of Fintech in recent years, the use of deep learning in finance and banking services has become prevalent. However, a detailed survey of the applications of deep learning in finance and banking is lacking in the existing literature. This study surveys and analyzes the literature on the application of deep learning models in the key finance and banking domains to provide a systematic evaluation of the model preprocessing, input data, and model evaluation. Finally, we discuss three aspects that could affect the outcomes of financial deep learning models. This study provides academics and practitioners with insight and direction on the state-of-the-art of the application of deep learning models in finance and banking.

Suggested Citation

  • Jian Huang & Junyi Chai & Stella Cho, 2020. "Deep learning in finance and banking: A literature review and classification," Frontiers of Business Research in China, Springer, vol. 14(1), pages 1-24, December.
    • Handle: RePEc:spr:fobric:v:14:y:2020:i:1:d:10.1186_s11782-020-00082-6
    DOI: 10.1186/s11782-020-00082-6
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    References listed on IDEAS

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    6. Pedro M. Mirete-Ferrer & Alberto Garcia-Garcia & Juan Samuel Baixauli-Soler & Maria A. Prats, 2022. "A Review on Machine Learning for Asset Management," Risks, MDPI, vol. 10(4), pages 1-46, April.
    7. Jaydip Sen & Rajdeep Sen & Abhishek Dutta, 2021. "Machine Learning in Finance-Emerging Trends and Challenges," Papers 2110.11999, arXiv.org.
    8. Heyam H. Al-Baity, 2023. "The Artificial Intelligence Revolution in Digital Finance in Saudi Arabia: A Comprehensive Review and Proposed Framework," Sustainability, MDPI, vol. 15(18), pages 1-16, September.
    9. Ajitha Kumari Vijayappan Nair Biju & Ann Susan Thomas & J Thasneem, 2024. "Examining the research taxonomy of artificial intelligence, deep learning & machine learning in the financial sphere—a bibliometric analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 58(1), pages 849-878, February.
    10. Brahmana, Rayenda Khresna, 2022. "Do Machine Learning Approaches Have the Same Accuracy in Forecasting Cryptocurrencies Volatilities?," MPRA Paper 119598, University Library of Munich, Germany.
    11. Mahsa Tavakoli & Rohitash Chandra & Fengrui Tian & Cristi'an Bravo, 2023. "Multi-Modal Deep Learning for Credit Rating Prediction Using Text and Numerical Data Streams," Papers 2304.10740, arXiv.org, revised Sep 2023.
    12. Kanzari, Dalel & Nakhli, Mohamed Sahbi & Gaies, Brahim & Sahut, Jean-Michel, 2023. "Predicting macro-financial instability – How relevant is sentiment? Evidence from long short-term memory networks," Research in International Business and Finance, Elsevier, vol. 65(C).
    13. Valentina ZOZULYA & Evgeny SOKOLOV & Evgeny KOSTYRIN & Sergey KOROLEV, 2021. "The effectiveness of applying beta-coefficient modifications when calculating returns on shares in Russian companies," Eastern Journal of European Studies, Centre for European Studies, Alexandru Ioan Cuza University, vol. 12, pages 31-52, June.
    14. Ni Zhan, 2021. "Where does the Stimulus go? Deep Generative Model for Commercial Banking Deposits," Papers 2101.09230, arXiv.org.
    15. Jianian Wang & Sheng Zhang & Yanghua Xiao & Rui Song, 2021. "A Review on Graph Neural Network Methods in Financial Applications," Papers 2111.15367, arXiv.org, revised Apr 2022.
    16. Ricardo Cuervo, 2023. "Predictive AI for SME and Large Enterprise Financial Performance Management," Papers 2311.05840, arXiv.org.
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    18. Thierry Warin & Aleksandar Stojkov, 2021. "Machine Learning in Finance: A Metadata-Based Systematic Review of the Literature," JRFM, MDPI, vol. 14(7), pages 1-31, July.

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