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Big Data Applications the Banking Sector: A Bibliometric Analysis Approach

Author

Listed:
  • Haitham Nobanee
  • Mehroz Nida Dilshad
  • Mona Al Dhanhani
  • Maitha Al Neyadi
  • Sultan Al Qubaisi
  • Saeed Al Shamsi

Abstract

This study aims to review the existing literature on big data applications in banking using a bibliometric analysis approach. This approach describes citation rates, research outputs, and their implementations, along with current streams in the field and future research agenda. The articles were selected from 2012 to 2020 and sorted by the citation rate in results and analysis. We have discovered 60 papers related to big data in banking, although the applications of big data in the banking sector are growing rapidly, the number of research output in this field is limited. Several themes are extracted from the studies that are reviewed, analyzed, and presented in this report. This review covered the themes that include investment, profit, competition, credit risk analysis, banking crime, and fintech. This report also signifies the importance, use of big data, and its function in the banking and financial sector. This study has also discussed the future research scope in the banking industry’s big data analytics.

Suggested Citation

  • Haitham Nobanee & Mehroz Nida Dilshad & Mona Al Dhanhani & Maitha Al Neyadi & Sultan Al Qubaisi & Saeed Al Shamsi, 2021. "Big Data Applications the Banking Sector: A Bibliometric Analysis Approach," SAGE Open, , vol. 11(4), pages 21582440211, December.
    • Handle: RePEc:sae:sagope:v:11:y:2021:i:4:p:21582440211067234
    DOI: 10.1177/21582440211067234
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    References listed on IDEAS

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    1. Carson Duan, 2024. "Analyses of Scientific Collaboration Networks among Authors, Institutions, and Countries in FinTech Studies: A Bibliometric Review," FinTech, MDPI, vol. 3(2), pages 1-25, April.
    2. Al-Omoush, Khaled Saleh & Garcia-Monleon, Fernando & Mas Iglesias, José Manuel, 2024. "Exploring the interaction between big data analytics, frugal innovation, and competitive agility: The mediating role of organizational learning," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    3. Mustafa Raza Rabbani & Abu Bashar & Iqbal Thonse Hawaldar & Muneer Shaik & Mohammed Selim, 2022. "What Do We Know about Crowdfunding and P2P Lending Research? A Bibliometric Review and Meta-Analysis," JRFM, MDPI, vol. 15(10), pages 1-23, October.
    4. Sim Jia Jin & Abdul Halim Abdullah & Mahani Mokhtar & Umar Haiyat Abdul Kohar, 2022. "The Potential of Big Data Application in Mathematics Education in Malaysia," Sustainability, MDPI, vol. 14(21), pages 1-23, October.
    5. Zhu, Haiyang & Chen, Zhen & Xia, Dongrui & Nassani, Abdelmohsen A. & Hameed, Waseem Ul, 2024. "Integrating fintech in natural resource management: Assessing the EKC hypothesis for sustainable development in E7 countries," Resources Policy, Elsevier, vol. 93(C).
    6. Morshadul Hasan & Ariful Hoque & Thi Le, 2023. "Big Data-Driven Banking Operations: Opportunities, Challenges, and Data Security Perspectives," FinTech, MDPI, vol. 2(3), pages 1-26, July.
    7. Damianos P. Sakas & Ioannis Dimitrios G. Kamperos & Dimitrios P. Reklitis & Nikolaos T. Giannakopoulos & Dimitrios K. Nasiopoulos & Marina C. Terzi & Nikos Kanellos, 2022. "The Effectiveness of Centralized Payment Network Advertisements on Digital Branding during the COVID-19 Crisis," Sustainability, MDPI, vol. 14(6), pages 1-23, March.
    8. Nejla Ellili & Haitham Nobanee & Ahmad Yuosef Alodat & Mehroz Nida Dilshad & Sabiha Nuzhat, 2024. "Mapping marine insurance: a bibliometric review: a taxonomical study using bibliometric visualization and systematic analysis," Journal of Financial Services Marketing, Palgrave Macmillan, vol. 29(3), pages 745-762, September.

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