IDEAS home Printed from https://ideas.repec.org/a/cbu/jrnlec/y2024v6ip204-212.html
   My bibliography  Save this article

An Overview Over The Impact Of Artificial Intelligence Technologies In The Banking Industry – A Bibliometric Analysis

Author

Listed:
  • CARBUNE DANIELA IULIA MARIA

    (UNIVERSITY OF CRAIOVA, EUGENIU CARADA DOCTORAL SCHOOL OF ECONOMIC SCIENCES)

Abstract

The banking industry is experiencing a significantly transformation fueled by the adoption of artificial intelligence (AI) technologies, which are reshaping essential operations, improving service quality and encouraging innovation across the sector. This paper conducts a bibliometric analysis to assess the impact of artificial intelligence technologies within financial institutions, applying VOSviewer software to identify and visualize the trends and patterns in the academic literature extracted from the Web of Science database. Present study highlights the development of research themes, key collaboration networks and finds out the interconnections through various AI applications within the baking sector. The findings of the study underscore the fact that artificial intelligence plays as a protagonist in increasing operational efficiency, enhancing customer experiences and streamlining decision-making workflows. By highlighting the current applications of artificial intelligence and identifying areas where it has demonstrated its effectiveness, this information significantly contributes to a deeper and more comprehensive understanding of the role of AI in reshaping banking processes and services. At the same time, the research article offers promising directions for future research, such as exploring the ethical implications of AI, addressing possible biases in algorithmic models and investigating ways to optimally integrate with existing systems. Advancing research in these directions will be essential for fully exploiting the potential of AI and managing the challenges inherent in its adoption, thus contributing to a continuous, responsible and sustainable innovation of the banking industry in the face of technological change.

Suggested Citation

  • Carbune Daniela Iulia Maria, 2024. "An Overview Over The Impact Of Artificial Intelligence Technologies In The Banking Industry – A Bibliometric Analysis," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 6, pages 204-212, December.
    • Handle: RePEc:cbu:jrnlec:y:2024:v:6i:p:204-212
    as

    Download full text from publisher

    File URL: https://www.utgjiu.ro/revista/ec/pdf/2024-06,%20Volumul%20I/24_Carbune.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Tzeremes, Nickolaos G., 2015. "Efficiency dynamics in Indian banking: A conditional directional distance approach," European Journal of Operational Research, Elsevier, vol. 240(3), pages 807-818.
    2. Constantin Zopounidis & Emilios C. C Galariotis & Michael Doumpos & Stavroula Sarri & Kostas Andriosopoulos, 2015. "Multiple criteria decision aiding for finance: An updated bibliographic survey," Post-Print hal-02879842, HAL.
    3. Doumpos, Michalis & Zopounidis, Constantin & Gounopoulos, Dimitrios & Platanakis, Emmanouil & Zhang, Wenke, 2023. "Operational research and artificial intelligence methods in banking," European Journal of Operational Research, Elsevier, vol. 306(1), pages 1-16.
    4. 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.
    5. Farrukh Rafiq & Nikhil Dogra & Mohd Adil & Jei-Zheng Wu, 2022. "Examining Consumer’s Intention to Adopt AI-Chatbots in Tourism Using Partial Least Squares Structural Equation Modeling Method," Mathematics, MDPI, vol. 10(13), pages 1-15, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Doumpos, Michalis & Zopounidis, Constantin & Gounopoulos, Dimitrios & Platanakis, Emmanouil & Zhang, Wenke, 2023. "Operational research and artificial intelligence methods in banking," European Journal of Operational Research, Elsevier, vol. 306(1), pages 1-16.
    2. Degl’Innocenti, Marta & Matousek, Roman & Sevic, Zeljko & Tzeremes, Nickolaos G., 2017. "Bank efficiency and financial centres: Does geographical location matter?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 46(C), pages 188-198.
    3. Jang Ho Kim & Yongjae Lee & Woo Chang Kim & Frank J. Fabozzi, 2022. "Goal-based investing based on multi-stage robust portfolio optimization," Annals of Operations Research, Springer, vol. 313(2), pages 1141-1158, June.
    4. Tsionas, Mike G., 2019. "Multi-objective optimization using statistical models," European Journal of Operational Research, Elsevier, vol. 276(1), pages 364-378.
    5. Carlin C. F. Chu & Simon S. W. Li, 2024. "A multiobjective optimization approach for threshold determination in extreme value analysis for financial time series," Computational Management Science, Springer, vol. 21(1), pages 1-14, June.
    6. Pätäri, Eero & Karell, Ville & Luukka, Pasi & Yeomans, Julian S, 2018. "Comparison of the multicriteria decision-making methods for equity portfolio selection: The U.S. evidence," European Journal of Operational Research, Elsevier, vol. 265(2), pages 655-672.
    7. Worthington, Andrew C. & Zelenyuk, Valentin, 2018. "Data envelopment analysis, truncated regression and double-bootstrap for panel data with application to Chinese bankingAuthor-Name: Du, Kai," European Journal of Operational Research, Elsevier, vol. 265(2), pages 748-764.
    8. Maria Elisabete Duarte Neves & Maria Do Castelo Gouveia & Catarina Alexandra Neves Proença, 2020. "European Bank’s Performance and Efficiency," JRFM, MDPI, vol. 13(4), pages 1-17, April.
    9. Carayannis, Elias G. & Ferreira, Fernando A.F. & Bento, Paulo & Ferreira, João J.M. & Jalali, Marjan S. & Fernandes, Bernardo M.Q., 2018. "Developing a socio-technical evaluation index for tourist destination competitiveness using cognitive mapping and MCDA," Technological Forecasting and Social Change, Elsevier, vol. 131(C), pages 147-158.
    10. Gulati, Rachita & Kumar, Sunil, 2016. "Assessing the impact of the global financial crisis on the profit efficiency of Indian banks," Economic Modelling, Elsevier, vol. 58(C), pages 167-181.
    11. Qi, Yue & Liao, Kezhi & Liu, Tongyang & Zhang, Yu, 2022. "Originating multiple-objective portfolio selection by counter-COVID measures and analytically instigating robust optimization by mean-parameterized nondominated paths," Operations Research Perspectives, Elsevier, vol. 9(C).
    12. Max Berre, 2022. "Which Factors Matter Most? Can Startup Valuation be Micro-Targeted?," Post-Print hal-03829877, HAL.
    13. Amin Aminimehr & Ali Raoofi & Akbar Aminimehr & Amirhossein Aminimehr, 2022. "A Comprehensive Study of Market Prediction from Efficient Market Hypothesis up to Late Intelligent Market Prediction Approaches," Computational Economics, Springer;Society for Computational Economics, vol. 60(2), pages 781-815, August.
    14. Julio Cezar Soares Silva & Diogo Ferreira de Lima Silva & Luciano Ferreira & Adiel Teixeira de Almeida-Filho, 2022. "A dominance-based rough set approach applied to evaluate the credit risk of sovereign bonds," 4OR, Springer, vol. 20(1), pages 139-164, March.
    15. Kallio, Markku & Halme, Merja & Dehghan Hardoroudi, Nasim & Aspara, Jaakko, 2022. "Transparent structured products for retail investors," European Journal of Operational Research, Elsevier, vol. 302(2), pages 752-767.
    16. Shahzad, Muhammad Farrukh & Xu, Shuo & An, Xin & Javed, Iqra, 2024. "Assessing the impact of AI-chatbot service quality on user e-brand loyalty through chatbot user trust, experience and electronic word of mouth," Journal of Retailing and Consumer Services, Elsevier, vol. 79(C).
    17. 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 Nov 2024.
    18. Cinzia Daraio & Léopold Simar & Paul W. Wilson, 2020. "Fast and efficient computation of directional distance estimators," Annals of Operations Research, Springer, vol. 288(2), pages 805-835, May.
    19. Righi, Marcelo Brutti & Borenstein, Denis, 2018. "A simulation comparison of risk measures for portfolio optimization," Finance Research Letters, Elsevier, vol. 24(C), pages 105-112.
    20. Minviel, Jean Joseph & De Witte, Kristof, 2017. "The influence of public subsidies on farm technical efficiency: A robust conditional nonparametric approach," European Journal of Operational Research, Elsevier, vol. 259(3), pages 1112-1120.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cbu:jrnlec:y:2024:v:6i:p:204-212. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Ecobici Nicolae The email address of this maintainer does not seem to be valid anymore. Please ask Ecobici Nicolae to update the entry or send us the correct address (email available below). General contact details of provider: https://edirc.repec.org/data/fetgjro.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.