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Big Data in the Banking Sector from a Transactional Cost Theory (TCT) Perspective—The Case of Top Lebanese Banks

In: ICT for an Inclusive World

Author

Listed:
  • Charbel Chedrawi

    (Saint Joseph University)

  • Yara Atallah

    (Saint Joseph University)

  • Souheir Osta

    (Saint Joseph University)

Abstract

The Voluminous data are being exchanged during banking transactions internally and externally. In the current information era, big data can help firms reveal hidden information and achieve competitive advantages, translating into higher productivity, lower operating costs, and a greater supply curve shift. In fact, the integration of big data analytics in the banking operations in England and Singapore enhanced customer services’ efficiency, reduced transaction costs, increased number of users, and boosted demand. This article discusses challenges and role of Big Data in the banking sector through the transaction cost theory approach of Williamson [1]. Following a qualitative approach, this paper reveals the actions currently undertaken by the two leading banks in the Lebanese market in order to optimize big data integration in their internal and external transactions.

Suggested Citation

  • Charbel Chedrawi & Yara Atallah & Souheir Osta, 2020. "Big Data in the Banking Sector from a Transactional Cost Theory (TCT) Perspective—The Case of Top Lebanese Banks," Lecture Notes in Information Systems and Organization, in: Youcef Baghdadi & Antoine Harfouche & Marta Musso (ed.), ICT for an Inclusive World, pages 391-405, Springer.
    • Handle: RePEc:spr:lnichp:978-3-030-34269-2_27
    DOI: 10.1007/978-3-030-34269-2_27
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    Cited by:

    1. 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.

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