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Artificial Intelligence as an Enabling Tool for the Development of Dynamic Capabilities in the Banking Industry

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  • Cristina Gallego-Gomez

    (International University of La Rioja (UNIR), Spain)

  • Carmen De-Pablos-Heredero

    (ESIC Business and Marketing School, Spain & Rey Juan Carlos University, Spain)

Abstract

Banks are investing in artificial intelligence (AI) to develop more innovative business models in order to face competition. The main objective of this paper consists in analyzing bank experiences when they introduce AI from the theory of dynamic capabilities and the resource-based view approach. Documentary research enables the description of experiences in three companies from the financial industry. It has been considered of interest to include different international experiences. For that reason, a firm providing debit and credit card services has been included, MasterCard, along with international banks such as Royal Bank of Scotland and Caixa Bank. Results show that AI enables firms to promote new relationships with customers, detect their needs or experiences, and adapt the service given by firms to be more competitive. AI also allows them to speed up responses to customers answers and doubts through its value chain. This research also shows that the proper implementation of AI permits a reconfiguration of traditional banking scenario. Detection, absorption, integration, and innovation are capabilities that allow these firms to build the managerial skills oriented to save costs, increase efficiency, and be more competitive.

Suggested Citation

  • Cristina Gallego-Gomez & Carmen De-Pablos-Heredero, 2020. "Artificial Intelligence as an Enabling Tool for the Development of Dynamic Capabilities in the Banking Industry," International Journal of Enterprise Information Systems (IJEIS), IGI Global, vol. 16(3), pages 20-33, July.
    • Handle: RePEc:igg:jeis00:v:16:y:2020:i:3:p:20-33
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    Cited by:

    1. Chotia, Varun & Cheng, Yue & Agarwal, Reeti & Vishnoi, Sushant Kumar, 2024. "AI-enabled Green Business Strategy: Path to carbon neutrality via environmental performance and green process innovation," Technological Forecasting and Social Change, Elsevier, vol. 202(C).
    2. Omar H. Fares & Irfan Butt & Seung Hwan Mark Lee, 2023. "Utilization of artificial intelligence in the banking sector: a systematic literature review," Journal of Financial Services Marketing, Palgrave Macmillan, vol. 28(4), pages 835-852, December.
    3. Fotis Kitsios & Maria Kamariotou, 2021. "Artificial Intelligence and Business Strategy towards Digital Transformation: A Research Agenda," Sustainability, MDPI, vol. 13(4), pages 1-14, February.
    4. Sánchez, Marisa A., 2022. "A multi-level perspective on financial technology transitions," Technological Forecasting and Social Change, Elsevier, vol. 181(C).
    5. Mariani, Marcello M. & Machado, Isa & Magrelli, Vittoria & Dwivedi, Yogesh K., 2023. "Artificial intelligence in innovation research: A systematic review, conceptual framework, and future research directions," Technovation, Elsevier, vol. 122(C).

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