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Deep Learning and Implementations in Banking

Author

Listed:
  • Hossein Hassani

    (University of Tehran)

  • Xu Huang

    (De Montfort University)

  • Emmanuel Silva

    (University of the Arts London)

  • Mansi Ghodsi

    (University of Tehran)

Abstract

Data-driven technologies have been changing every aspect of human life and the fast-developing banking sector with its data-rich nature has become the implementation field of these fast-evolving technologies. Deep learning, as one of the emerging technologies in recent years, has also been inevitably adopted for various improvements in banking. To the best of our knowledge, there is no comprehensive literature review, which focuses on specifically deep learning and its implementations in banking. Therefore, this paper investigates the deep learning technology in-depth and summarizes the relevant applications in banking so to contribute to the existing literature. Moreover, by providing a reliable and up-to-date review, it is also aimed to serve as the one-stop repository for banks and researchers who are interested in embracing deep learning, whilst bringing insights for the directions of future research and implementation.

Suggested Citation

  • Hossein Hassani & Xu Huang & Emmanuel Silva & Mansi Ghodsi, 2020. "Deep Learning and Implementations in Banking," Annals of Data Science, Springer, vol. 7(3), pages 433-446, September.
    • Handle: RePEc:spr:aodasc:v:7:y:2020:i:3:d:10.1007_s40745-020-00300-1
    DOI: 10.1007/s40745-020-00300-1
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    References listed on IDEAS

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