IDEAS home Printed from https://ideas.repec.org/a/gam/jrisks/v13y2025i6p106-d1667690.html
   My bibliography  Save this article

The Impact of Fintech on the Stability of Middle Eastern and North African (MENA) Banks

Author

Listed:
  • Aisha Mohammad Afzal

    (Accounting and Finance Department, College of Business, University of Doha for Science and Technology, Doha 24449, Qatar)

  • Bashar Abu Khalaf

    (Accounting and Finance Department, College of Business, University of Doha for Science and Technology, Doha 24449, Qatar)

  • Maryam Saad Al-Naimi

    (Accounting and Finance Department, College of Business, University of Doha for Science and Technology, Doha 24449, Qatar)

  • Enas Samara

    (Finance Department, Graduate School of Business, The National University of Malaysia, Bangi 43600, Malaysia)

Abstract

This study investigates the impact of financial technology (Fintech) on bank stability in the Middle East and North Africa (MENA). Utilizing panel data from 94 banks in 10 countries over a 13-year period from 2011 to 2023, this research employs panel GMM regression to examine the relationship between the level of Fintech adoption, as measured by the Fintech index, and a bank’s stability. This paper controls for bank characteristics (efficiency, profitability, size, liquidity risk, and dividend payout ratio) and macroeconomic variables (GDP growth and inflation). The Fintech index is calculated using data text mining from the banks’ annual reports. This research contributes to the existing literature by providing empirical evidence of the positive effects of Fintech adoption in the MENA banking sector. The positive findings underscore the transformative impact of Fintech on banking stability, highlighting the importance of technological integration in MENA’s financial institutions for growth, stability, and effective strategies. The robustness of the results regression confirmed that our findings hold.

Suggested Citation

  • Aisha Mohammad Afzal & Bashar Abu Khalaf & Maryam Saad Al-Naimi & Enas Samara, 2025. "The Impact of Fintech on the Stability of Middle Eastern and North African (MENA) Banks," Risks, MDPI, vol. 13(6), pages 1-22, May.
    • Handle: RePEc:gam:jrisks:v:13:y:2025:i:6:p:106-:d:1667690
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-9091/13/6/106/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-9091/13/6/106/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mild, Andreas & Waitz, Martin & Wöckl, Jürgen, 2015. "How low can you go? — Overcoming the inability of lenders to set proper interest rates on unsecured peer-to-peer lending markets," Journal of Business Research, Elsevier, vol. 68(6), pages 1291-1305.
    2. Finlay, Steven, 2011. "Multiple classifier architectures and their application to credit risk assessment," European Journal of Operational Research, Elsevier, vol. 210(2), pages 368-378, April.
    3. Peterson K. Ozili, 2019. "Non-performing loans and financial development: new evidence," Journal of Risk Finance, Emerald Group Publishing Limited, vol. 20(1), pages 59-81, January.
    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. Yufei Xia & Lingyun He & Yinguo Li & Nana Liu & Yanlin Ding, 2020. "Predicting loan default in peer‐to‐peer lending using narrative data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 260-280, March.
    2. Dangxing Chen & Weicheng Ye & Jiahui Ye, 2022. "Interpretable Selective Learning in Credit Risk," Papers 2209.10127, arXiv.org.
    3. Peterson K. Ozili, 2019. "Impact of IAS 39 reclassification on income smoothing by European banks," Journal of Financial Reporting and Accounting, Emerald Group Publishing Limited, vol. 17(3), pages 537-553, September.
    4. Cao Son Tran & Dan Nicolau & Richi Nayak & Peter Verhoeven, 2021. "Modeling Credit Risk: A Category Theory Perspective," JRFM, MDPI, vol. 14(7), pages 1-21, July.
    5. Doumpos, Michalis & Andriosopoulos, Kostas & Galariotis, Emilios & Makridou, Georgia & Zopounidis, Constantin, 2017. "Corporate failure prediction in the European energy sector: A multicriteria approach and the effect of country characteristics," European Journal of Operational Research, Elsevier, vol. 262(1), pages 347-360.
    6. Wang, Qian & Su, Zhongnan & Chen, Xinyang, 2021. "Information disclosure and the default risk of online peer-to-peer lending platform," Finance Research Letters, Elsevier, vol. 38(C).
    7. Elekdag, Selim & Emrullahu, Drilona & Ben Naceur, Sami, 2025. "Does FinTech Increase Bank Risk-taking?," Journal of Financial Stability, Elsevier, vol. 76(C).
    8. Cang, Shuang & Yu, Hongnian, 2014. "A combination selection algorithm on forecasting," European Journal of Operational Research, Elsevier, vol. 234(1), pages 127-139.
    9. Dumitrescu, Elena & Hué, Sullivan & Hurlin, Christophe & Tokpavi, Sessi, 2022. "Machine learning for credit scoring: Improving logistic regression with non-linear decision-tree effects," European Journal of Operational Research, Elsevier, vol. 297(3), pages 1178-1192.
    10. Guotai Chi & Zhipeng Zhang, 2017. "Multi Criteria Credit Rating Model for Small Enterprise Using a Nonparametric Method," Sustainability, MDPI, vol. 9(10), pages 1-23, October.
    11. Aamir Aijaz Syed & Assad Ullah & Muhammad Abdul Kamal, 2024. "Does economic policy uncertainty impedes financial inclusion in BRICS economies: the mediating role of quality of governance," Economic Change and Restructuring, Springer, vol. 57(1), pages 1-24, February.
    12. Qizhi Tao & Yizhe Dong & Ziming Lin, 2017. "Who can get money? Evidence from the Chinese peer-to-peer lending platform," Information Systems Frontiers, Springer, vol. 19(3), pages 425-441, June.
    13. Wang, Liang & Li, Yuxuan & Liang, Meiqi & Wang, Yuanfei, 2023. "Research on P2P product portfolio strategy based on term structure under risk reserve system," International Review of Economics & Finance, Elsevier, vol. 83(C), pages 124-138.
    14. Candida Ferreira, 2023. "The Influence of Bank Performance, Market Condition and Economic Growth on Non-Performing Loansa," World Journal of Applied Economics, WERI-World Economic Research Institute, vol. 9(1), pages 77-98, June.
    15. Lessmann, Stefan & Baesens, Bart & Seow, Hsin-Vonn & Thomas, Lyn C., 2015. "Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research," European Journal of Operational Research, Elsevier, vol. 247(1), pages 124-136.
    16. Parimal Kumar Giri & Sagar S. De & Sachidananda Dehuri & Sung‐Bae Cho, 2021. "Biogeography based optimization for mining rules to assess credit risk," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 28(1), pages 35-51, January.
    17. Emmanuel Flachaire & Sullivan Hué & Sébastien Laurent & Gilles Hacheme, 2024. "Interpretable Machine Learning Using Partial Linear Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 86(3), pages 519-540, June.
    18. Su, Chi-Wei & Mirza, Nawazish & Umar, Muhammad & Chang, Tsangyao & Albu, Lucian Liviu, 2022. "Resource extraction, greenhouse emissions, and banking performance," Resources Policy, Elsevier, vol. 79(C).
    19. Li, Zhiyong & Li, Aimin & Bellotti, Anthony & Yao, Xiao, 2023. "The profitability of online loans: A competing risks analysis on default and prepayment," European Journal of Operational Research, Elsevier, vol. 306(2), pages 968-985.
    20. Hai Long Pham & Kevin James Daly, 2020. "The Impact of BASEL Accords on the Management of Vietnamese Commercial Banks," JRFM, MDPI, vol. 13(10), pages 1-13, September.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:gam:jrisks:v:13:y:2025:i:6:p:106-:d:1667690. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.