Merkez Bankalarında Yapay Zeka Kullanımı

Öz

Yapay zekâ insanlık tarihinde önemli değişikliklere yol açmaktadır. Yapay zekâya ilişkin ilk çalışmalar 1950’li yıllarda Turing’in bir makine nasıl insan gibi düşünebilir sorusuyla başlamıştır. Günümüzde de yapay zekâ çalışmaları hızla devam etmektedir. Yapay zekânın uzun geçmişine rağmen tartışmalı ve gelişime açık yanları bulunmaktadır. Yapay zekâ kullanımı pek çok sektörde ve kurumda giderek yaygınlaşmaktadır. Çalışmanın ana amacı merkez bankalarının yapay zekâ kullanım potansiyelini değerlendirmektir. Merkez bankalarının yapay zekâdan yararlanma potansiyelinin giderek artmasına karşın, yazında bu alandaki çalışmalar henüz oldukça kısıtlıdır. Bu çalışma, merkez bankalarının geleneksel görevleri üzerinden, yapay zekâ kullanımını çok boyutlu bir yaklaşımla inceleyerek literatüre katkı vermeyi hedeflemektedir.Yapay zekânın örgüt bünyesine alınabilmesi, örgütlerin olgunluk seviyeleriyle de oldukça ilişkilidir. Bu nedenle makalede BIS üyesi merkez bankaları incelenmiştir. Çalışmanın temel bulgusunu yapay zekâ algoritmalarının siyah kutu olarak adlandırılan kapalı yanlarının merkez bankası hesap verebilirliği ile örtüşmemesi oluşturmaktadır. Bu bulguya ek olarak merkez bankalarının yapay zekâ kullanımına ilişkin önemli bir potansiyeli bulunmasına rağmen bu potansiyeli örgütsel yapılanmalarına yaymada eksiklikleri ve kısıtları bulunduğu görülmüştür.

Anahtar Kelimeler

• Yapay Zeka ve Merkez Bankaları
• Büyük Veri ve Merkez Bankaları
• Merkez Bankaları ve Siyah Kutu Algoritmalar

Artificial Intelligence Use in Central Banks

Öz

Artificial intelligence is leading to significant changes in human history. Early studies on artificial intelligence began in the 1950s with Turing's question of how a machine could think like a human. Today, artificial intelligence studies are developing rapidly. Despite its long history, artificial intelligence still has controversial aspects and areas open to further development. The use of artificial intelligence is becoming increasingly widespread across many sectors and institutions. The primary objective of this study is to evaluate the potential of AI integration within central banks. While there is a growing potential for central banks to use AI, existing literature on this subject remains limited. This study aims to contribute to the literature by examining AI usage through a multi-dimensional approach, focusing on the traditional mandates of central banks. Integrating artificial intelligence into an organization is highly correlated with the organization's capabilities. Therefore, this study examines central banks that are members of the BIS (Bank for International Settlements). The core finding of the research is that the "black box" nature of AI algorithms, referring to their lack of transparency, is inconsistent with the principle of central bank accountability. In addition to this finding, it was observed that although central banks possess significant potential for AI utilization, they face deficiencies and constraints in diffusing this potential across their organizational structures.

Anahtar Kelimeler

• Artificial Intelligence and Central Banks
• Big Data and Central Banks
• Central Banks and Black Box Algorithms

Kaynakça

1. Akın, E., & Şahin, M. E. (2024). Derin öğrenme ve yapay sinir ağı modelleri üzerine bir inceleme. EMO Bilimsel Dergi, 14(1), 27-38.
2. Aldasoro, I., Doerr, S., Gambacorta, L., Notra, S., Oliviero, T., & Whyte, D. (2024). Generative artificial intelligence and cyber security in central banking. Journal of Financial Regulation, 11(1), 119-128.
3. Araujo, D., Bruno, G., Marcucci, J., Schmidt, R., & Tissot, B. (2022). Machine learning applications in central banking, IFC Bulletin, no 57.
4. Araujo, D., Bruno, G., Marcucci, J., Schmidt, R., & Tissot, B. (2023). Data science in central banking: applications and tools. IFC Bulletin, 59.
5. Araujo, D., Doerr, S., Gambacorta, L., & Tissot, B. (2024). Artificial intelligence in central banking. BIS Bulletin, 84.
6. Banca d’Italia (2025). Banca d'Italia promotes artificial intelligence project in the Italian financial sector. https://www.bancaditalia.it/ media/notizia/banca-d-italia-promotes-artificial-intelligence-project-in-the-italian-financial-sector/ , 03.05.2025.
7. Benford, J. (2024). Trusted AI: Ethical, safe, and effective application of artificial intellegence at the Bank Of England, https://www.bankofengland.co.uk/speech/2024/september/james-benford-speech-at-the-central-bank-ai-inaugural-conference, 08.05.2025.
8. Beşe, E. (2007). Finansal sistem stres testi uygulamaları ve Türkiye örneği. Türkiye Cumhuriyet Merkez Bankası Uzmanlık Yeterlilik Tezi. Ankara.

9. BIS (2025). IFC survey on central banks’ use of AI and ML.
10. Bholat, D., & Susskind, D. (2021). The assessment: artificial intelligence and financial services. Oxford Review of Economic Policy, 37(3), 417-434.
11. Bholat, D. (2015). Big data and central banks. Big Data & Society, 2(1), https://doi.org/10.1177/2053951715579469 .
12. BoE (2024). Artificial Intellegence in UK Financial Services. https://www.bankofengland.co.uk/report/2024/artificial-intelligence-in-uk-financial-services-2024 , 30.04.2025.
13. Bowman, M. W. (2024). Artificial Intelligence in the Financial System: A speech at the 27th Annual Symposium on Building the Financial System of the 21st Century: An Agenda for Japan and the United States, Washington, DC, November 22, 2024. Board of Governors of the Federal Reserve System (US).
14. Breeden, S. (2024). Banks’ use of AI could be included in stress tests, says Bank of England deputy governor. Banks’ use of AI could be included in stress tests, says Bank of England deputy governor. 13.05.2025.
15. Bundesbank (2025). Monetary Policy Communication According to Artificial Intellegence.
16. Casillas, J. (2024). Bias and discrimination in machine decision-making systems. Ethics of Artificial Intelligence, 13-38.
17. Chirra, B. R. (2024). Revolutionizing Cybersecurity: The Role of AI in Advanced Threat Detection Systems. International Journal of Advanced Engineering Technologies and Innovations, 1(4), 480-504.
18. Challoumis, C. (2024). AI And The Economy-How Technology Is Redefining Employment And Income Distribution, https://mpra.ub.uni-muenchen.de/122722/1/MPRA_paper_122722.pdf, 16.03.2025.
19. Chansang, P (2019). Data management in the data evolution era at Bank of Thailand, IFC Bulletin, no 53.
20. Cipollone, P. (2024). Artificial intelligence: A Central Bank’s View, https://www.ecb.europa.eu/press/key/date/2024/html/ ecb.sp240704_1~e348c05894.en.html , 03.05.2025.
21. Cornelli, G., Doerr, S., Gambacorta, L., & Tissot, B. (2022). Big data in Asian central banks. Asian Economic Policy Review, 17(2), 255-269.
22. Das, Hindistan Merkez Bankası Başkanı, Yapay Zekânın Artan Kullanımı Kaynaklanan Finansal İstikrar Riskleri Konusunda Uyardı. https://ticaret.gov.tr/blog/sektor-haberleri/hindistan-merkez-bankasi-baskani-yapay-zekânin-artan-kullanimindan-kaynaklanan-finansal-istikrar-riskleri-konusunda-uyardi , 16.10.2024.
23. De Galhau, F. (2024). Innovation by central banks: the sooner the better, https://www.banque-france.fr/en/governors-interventions/innovation-central-banks-sooner-better , 08.05.2025.
24. Decker, M. C., Wegner, L., & Leicht-Scholten, C. (2025). Procedural fairness in algorithmic decision-making: the role of public engagement. Ethics and Information Technology, 27(1), 1.
25. Devys, E., & von Kalckreuth, U. (2021). The use of AI for company data gathering-Finding and monitoring fintechs in Germany and France. IFC-Bank of Italy Workshop on “Machine learning in central banking”
26. DFKI (2024), Cybermapping with AI – Deutsche Bundesbank and DFKI establish collaborative research lab. https://www.dfki.de/en/web/news/cybermapping-and-ai 03.05.2025.
27. Dincer, N., Eichengreen, B., & Martinez, J. J. (2024). Central Bank Independence: Views from History and Machine Learning. Annual Review of Economics, 16(1), 393-428.
28. DNB, Data Science Hub, https://www.dnb.nl/en/research/data-science-hub/ , 03.05.2025.
29. Doerr, S., Leonardo G., & Jose M. S. (2021). Big data and machine learning in central banking. BIS Working Paper, No. 930.
30. Dörfler, V. (2023). Yöneticiler İçin Yapay Zekâ, Türkiye İş Bankası Yayınları, İstanbul.
31. Duijm, P., & van Lelyveld, I. (2025). Data Science for central banks and supervisors: How to make it work, actually. Harvard Data Science Review, 7(1).
32. Dwork, C. (2006). Differential privacy. In 33rd International Colloquium on Automata, Languages and Programming (ICALP) (ss.. 1–12).
33. EU (2025). EU AI Act: first regulation on artificial intellegence, https://www.europarl.europa.eu/topics/en/article/20230601STO93804/ eu-ai-act-first-regulation-on-artificial-intelligence , 02.05.2025.
34. EU, Artificial Intelligence Act (Regulation (EU) 2024/1689), Official Journal version of 13 June 2024, https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=OJ:L_202401689 , 30.03.2025.
35. Farič, A., & Bratko, I. (2024). Machine Bias: A Survey of Issues. Informatica, 48(2), 205-215.
36. Financial Times (2025), Bundesbank enlists AI to prove ECB’s dovish bias, https://www.ft.com/content/bd9392a2-f7a9-4fa8-bf8d-175a48e3c6fc, 03.05.2025.
37. Fingscheidt, T., Blumenberg, P., & Möller, B. (2026). Engineering of Hallucination in Generative AI: It's not a Bug, it's a Feature. arXiv preprint arXiv:2601.07046.
38. Giuffrida, A (2025). “Italian newspaper says it has published world’s first AI-generated edition”, https://www.theguardian.com/ technology/2025/mar/18/italian-newspaper-says-it-has-published-worlds-first-ai-generated-edition , 31.03.2025.
39. Global Times (2025). Çin Merkez Bankası, yapay zekâ büyük dil modellerinin uygulamalarını teşvik etme sözü verdi, https://www.globaltimes.cn/page/202503/1330294.shtml , 03.05.2025.
40. Guerra, P., & Castelli, M. (2021). Machine learning applied to banking supervision a literature review. Risks, 9(7), 136.
41. Gümüş, E. (2024). Yapay sinir ağları ve derin öğrenme modeli kullanılarak usd/try döviz kurunun tahmin edilmesi. Anadolu Üniversitesi Sosyal Bilimler Dergisi, 24(2), 703-726.
42. Harker, P. T.(2024). Fintech, AI, and the Changing Financial Landscape , https://www.philadelphiafed.org/the-economy/banking-and-financial-markets/241112-fintech-ai-and-the-changing-financial-landscape, 30.04.2025.
43. Hern, A. (2015). Computers now better than humans at recognising and sorting images, https://www.theguardian.com/global/2015/may/13/ baidu-minwa-supercomputer-better-than-humans-recognising-images, 31.03.2025.
44. IBM. What is explainable AI?, https://www.ibm.com/think/topics/explainable-ai , 2.4.2025.
45. IIF - Institute of International Finance (2019). Machine Learning Recommendations for Policymakers.
46. Juliussen, B. A., Rui, J. P., & Johansen, D. (2023). Algorithms that forget: Machine unlearning and the right to erasure. Computer Law & Security Review, 51, 105885.
47. Kalmykov, V. L., & Kalmykov, L. V. (2024). A white box solution to the black box problem of AI. arXiv preprint arXiv:2401.03093.
48. Kerdsri, J., & Treeratpituk, P. (2022): “Using deep learning technique to automate banknote defect classification” in “Machine learning in central banking”, IFC Bulletin, no 57, November, presentation given at an Irving Fisher Committee on Central Bank Statistics and Bank of Italy workshop, 19–22 October 2021, www.bis.org/ifc/publ/ifcb57_34.pdf.
49. Kruhse-Lehtonen, U., & Hofmann, D. (2020). How to Define and Execute Your Data and AI Strategy. Harvard Data Science Review, 2(3).
50. Kurnaz, İ. (2016). Siber güvenlik ve ilintili kavramsal çerçeve. Siber Politikalar Dergisi, 1, (1).
51. Kutlu I. (2023). Yapay zekâ teknolojileri ve zaman serileri analizi ile ekonominin banknot talebinin tahmini: türkiye geneli ve eskişehir şubesi reeskont bölgesinin karşılaştırılması, Uzmanlık Tezi.
52. Lagarde, C. (2017). Central Banking and Fintech—A Brave New World?, https://www.imf.org/en/News/Articles/2017/09/28/ sp092917-central-banking-and-fintech-a-brave-new-world , 01.05.2025.
53. McCarthy, J. (2007). From here to human-level AI. Artificial Intelligence, 171(18), 1174-1182.
54. Nicolazzo, S., & Nocera, A. (2025). How Secure is Forgetting? Linking Machine Unlearning to Machine Learning Attacks. arXiv preprint arXiv:2503.20257.
55. Njoroge, L. (2024). Role of Artificial Intelligence (AI) in. https://www.comesa.int/wp-content/uploads/2020/09/Special-Report-AI-and-Big-Data-Implication-for-Central-Banking-in-COMESA-region.pdf , 28.04.2025.
56. Perez-Cruz, F., & Shin, H. S. (2024). Testing the cognitive limits of large language models, BIS Bulletin, no 83.
57. Perkowski, P., & Marsal, A. (2024). Generative AI at work: Survey evidence from three Central Banks. Available at SSRN.
58. Popowicz, J. E. (2024). European Commission opens consultation on AI in finance, https://www.centralbanking.com/fintech/7961503/european-commission-opens-consultation-on-ai-in-finance , 02.05.2025.
59. Raza, S., Ghuge, S., Ding, C., Dolatabadi, E., & Pandya, D. (2024). FAIR Enough: Develop and Assess a FAIR-Compliant Dataset for Large Language Model Training?. Data Intelligence, 6(2), 559-585.
60. Richardson, A., van Florenstein Mulder, T., & Vehbi, T. (2021). Nowcasting GDP using machine-learning algorithms: A real-time assessment. International journal of forecasting, 37(2), 941-948.
61. Rosenblatt, F. (1958). The perceptron: A probabilistic model for information storage and organization in the brain. Psychological Review, 65(6), 386–408
62. Santos, O., & Radanliev, P. (2024). Beyond the Algorithm: AI, Security, Privacy, and Ethics. Addison-Wesley Professional, https://learning.oreilly.com/ , 27.03.2025.
63. Sun, Z., Sandoval, L., Crystal-Ornelas, R., Mousavi, S. M., Wang, J., Lin, C., ... & John, A. (2022). A review of earth artificial intelligence. Computers & Geosciences, 159, 105034.
64. Takan, D. E., Bozkurt, U. A., Bingöl, B., Baskın, Ş., Temur, Ş., & Takan, S. (2023). Gerbner’in Yetiştirme Teorisi Perspektifinden Yapay Zekâ’da Yanlılık Problemi. Veri Bilimi, 6(2), 41-55.
65. Thareja (2024), Artificial Intellegence Beyond Classical AI, Pearson., https://learning.oreilly.com/ , 27.03.2025.
66. TRT Haber (2024). Avrupa Merkez Bankası Başkanı Lagarde'dan yapay zekâ uyarısı, https://www.trthaber.com/haber/dunya/ avrupa-merkez-bankasi-baskani-lagardedan-yapay-zekâ-uyarisi-879526.html , 01.05.2025.
67. Türk Dil Kurumu (t.y.) Güncel Türkçe Sözlük. 12 Mart 2026 tarihinde, https://sozluk.gov.tr/ adresinden alındı.
68. Vegesna, V. V. (2023). Privacy-Preserving Techniques in AI-Powered Cyber Security: Challenges and Opportunities. International Journal of Machine Learning for Sustainable Development, 5(4), 1-8.
69. Vučinić, M., & Luburić, R. (2024). Artificial intelligence, fintech and challenges to central banks. Journal of Central Banking Theory and Practice, 13(3), 5-42.
70. Xu, Y., Liu, X., Cao, X., Huang, C., Liu, E., Qian, S., ... & Zhang, J. (2021). Artificial intelligence: A powerful paradigm for scientific research. The Innovation, 2(4).