Araştırma Makalesi

ARTIFICIAL INTELLIGENCE IN BANKING: A BIBLIOMETRIC REVIEW

Cilt: 35 17 Haziran 2026
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ARTIFICIAL INTELLIGENCE IN BANKING: A BIBLIOMETRIC REVIEW

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This study examines the existing scientific foundations on the connection between artificial intelligence (AI) and the banking sector. It reviews 218 peer-reviewed articles published between 2010 and2024 and indexed in the Web of Science Core Collection. The literature is discussed in three dimensions, namely, intellectual structure, thematic structure and geographical distribution. With VOSviewer, the co-occurrence networks of key words, authors collaboration patterns, citation structures, and development of thematics are mapped to help to see the pre-existing research areas and the emergent trends. The results reveal that discipline has a solid foundation on technological base, especially machine learning, big data, and blockchain. Nonetheless, some more recent research has started to explore behavioral and more ethical concerns of AI, such as trust, explainability, and user acceptance. Although the thematic scope of the field has expanded, international and institutional collaboration remains limited. There are distinct research gaps that can be identified, especially in explainable AI in banking, green finance and cross-national comparative research. These results demonstrate the relevance of interdisciplinary cooperation in facilitating the responsible application of AI in the banking industry. In order to add to the co-occurrence analysis, Latent Dirichlet Allocation (LDA) topic modeling was applied on 216 article abstracts (k = 5) to reduce potential bias in keyword-based analyses. The findings indicate that there are five recurring latent themes, namely credit risk and fraud detection; Know Your Customer (KYC) and Anti-Money Laundering (AML); trust and explainability in AI systems; AI applications in digital banking services; and Environmental, Social, and Governance (ESG) considerations. An important contribution of the research is the fact that the findings have been related to the theory of technology adoption, especially the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT). The results also have a policy implication in that they go in line with developments in AI governance systems today. Altogether, this paper summarizes the existing research on AI in the banking sector and outlines directions for future research.

Anahtar Kelimeler

Kaynakça

  1. Aldboush, H. H., & Ferdous, M. (2023). Building trust in fintech: an analysis of ethical and privacy considerations in the intersection of big data, AI, and customer trust. International Journal of Financial Studies, 11(3), 90. https://doi.org/10.3390/ijfs11030090
  2. Ashta, A., & Herrmann, H. (2021). Artificial intelligence and fintech: An overview of opportunities and risks for banking, investments, and microfinance. Strategic Change, 30(3), 211-222. https://doi.org/10.1002/jsc.2404
  3. Atwal, G., & Mulca, D. (2021). Antecedents of intention to adopt artificial intelligence services by consumers in personal financial investing. Strategic Change, 30(3), 293-298. https://doi.org/10.1002/jsc.2412
  4. Bhatnagr, P., & Rajesh, A. (2024). Artificial intelligence features and expectation confirmation theory in digital banking apps: Gen Y and Z perspective. Management Decision. https://doi.org/10.1108/MD-07-2023-1145
  5. Bhatnagr, P., Rajesh, A., & Misra, R. (2024). Continuous intention usage of artificial intelligence enabled digital banks: a review of expectation confirmation model. Journal of Enterprise Information Management, 37(6), 1763-1787. https://doi.org/10.1108/JEIM-11-2023-0617
  6. Blei, David M., Andrew Y. Ng, and Michael I. Jordan. Latent dirichlet allocation. Journal of Machine Learning Research 3.Jan (2003): 993-1022.
  7. Boot, A., Hoffmann, P., Laeven, L., & Ratnovski, L. (2021). Fintech: what’s old, what’s new?. Journal of Financial Stability, 53, 100836. https://doi.org/10.1016/j.jfs.2020.100836
  8. Boustani, N. M. (2022). Artificial intelligence impact on banks clients and employees in an Asian developing country. Journal of Asia Business Studies, 16(2), 267-278. https://doi.org/10.1108/JABS-09-2020-0376

Ayrıntılar

Birincil Dil

İngilizce

Konular

Ekonometri (Diğer)

Bölüm

Araştırma Makalesi

Yayımlanma Tarihi

17 Haziran 2026

Gönderilme Tarihi

1 Mayıs 2025

Kabul Tarihi

5 Aralık 2025

Yayımlandığı Sayı

Yıl 2026 Cilt: 35

Kaynak Göster

APA
Dayan, V. (2026). ARTIFICIAL INTELLIGENCE IN BANKING: A BIBLIOMETRIC REVIEW. Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 35. https://doi.org/10.35379/cusosbil.1688968
AMA
1.Dayan V. ARTIFICIAL INTELLIGENCE IN BANKING: A BIBLIOMETRIC REVIEW. Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi. 2026;35. doi:10.35379/cusosbil.1688968
Chicago
Dayan, Volkan. 2026. “ARTIFICIAL INTELLIGENCE IN BANKING: A BIBLIOMETRIC REVIEW”. Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi 35 (Haziran). https://doi.org/10.35379/cusosbil.1688968.
EndNote
Dayan V (01 Haziran 2026) ARTIFICIAL INTELLIGENCE IN BANKING: A BIBLIOMETRIC REVIEW. Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi 35
IEEE
[1]V. Dayan, “ARTIFICIAL INTELLIGENCE IN BANKING: A BIBLIOMETRIC REVIEW”, Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, c. 35, Haz. 2026, doi: 10.35379/cusosbil.1688968.
ISNAD
Dayan, Volkan. “ARTIFICIAL INTELLIGENCE IN BANKING: A BIBLIOMETRIC REVIEW”. Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi 35 (01 Haziran 2026). https://doi.org/10.35379/cusosbil.1688968.
JAMA
1.Dayan V. ARTIFICIAL INTELLIGENCE IN BANKING: A BIBLIOMETRIC REVIEW. Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi. 2026;35. doi:10.35379/cusosbil.1688968.
MLA
Dayan, Volkan. “ARTIFICIAL INTELLIGENCE IN BANKING: A BIBLIOMETRIC REVIEW”. Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, c. 35, Haziran 2026, doi:10.35379/cusosbil.1688968.
Vancouver
1.Volkan Dayan. ARTIFICIAL INTELLIGENCE IN BANKING: A BIBLIOMETRIC REVIEW. Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi. 01 Haziran 2026;35. doi:10.35379/cusosbil.1688968