Knowledge Economy Studies

A Feasibility Study on the Application of Artificial Intelligence in Central Bank Monetary Policies: Money Creation and Liquidity Management in Focus

Document Type : Original Article

Authors

Ebrahim Abdipour Fard 1
Sedigheh Gharloghi 2

1 Professor, Department of Private Law, Faculty of Law, University of Qom, Qom, Iran.

2 Ph.D. Student in Public Law, University of Qom, Qom, Iran.

https://doi.org/10.22034/kes.2025.2057018.1054
Abstract
In the contemporary economic landscape, the implementation of monetary policies constitutes one of the primary responsibilities of central banks, aimed at objectives such as money creation, liquidity management, inflation containment, and recession prevention. With the emergence of advanced technologies, Artificial Intelligence (AI) has gradually evolved into a powerful instrument for enhancing the efficiency and effectiveness of these policies. The adoption of intelligent data processing and analytical techniques enables central banks to monitor liquidity flows, calibrate money supply levels, and forecast economic behaviors more accurately. This study, employing a descriptive-analytical methodology and grounded in legal and economic sources, seeks to address a central question: To what extent can AI contribute to improving the processes of money creation and liquidity control within central banks, and what challenges and considerations are involved in its implementation? The findings suggested that strategic integration of AI into monetary policymaking—particularly in the domain of money creation—can lead to more informed decision-making, mitigation of financial risks, and increased policy effectiveness, thereby fostering greater public confidence in central banking institutions. Nevertheless, such integration necessitates adherence to specific prerequisites and regulatory frameworks, as the application of AI in the field of economics still requires consistent human oversight due to the limited specialized expertise at the intersection of economics and technology.

Keywords

Artificial Intelligence (AI)
Central Bank
Liquidity Management
Monetary Policy
Money Creation

Subjects

Akbari, M., Hashemi Far, S. M., Karimi Vardanjani, R., & Simiari, M. R. (2020). Economic-jurisprudential dimensions of money creation from the perspective of Islamic banking. Biannual Interdisciplinary Journal of Jurisprudential Research, 8 (2), 136.
Angwin, J., Larson, J., Mattu, S., & Kirchner, L. (2016, May 23). Machine bias. ProPublica. https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing. 
Arabi, S. H., & Meysami, H. (2019). Money and banking with an Islamic approach (3rd ed.). Qom: Research Institute for Islamic Culture and Thought.
Bank of England & Financial Conduct Authority. (2024, November 21). Artificial intelligence in UK financial services – 2024. https://www.bankofengland.co.uk/report/2024/artificial-intelligence-in-uk-financial-services-2024.
Begenau, J., & Landvoigt, T. (2015). Financial regulation in a quantitative model of the modern banking system. Unpublished manuscript, Harvard University and University of Texas at Austin.
Bierman, H. Jr., & Hass, J. E. (1963). An introduction to managerial finance. London: Pitman Publishing Ltd.
Chakraborty, C., & Joseph, A. (2017). Machine learning at central banks (Bank of England Working Paper No. 674). Bank of England. 
Cipollone, P. (2024, July). Artificial intelligence: a central bank’s view. In Keynote speech at the National Conference of Statistics on official statistics at the time of artificial intelligence. Rome (Vol. 4).
Crisanto, J. C., Leuterio, C. B., Prenio, J., & Yong, J. (2024). Regulating AI in the financial sector: recent developments and main challenges. Fonte: BIS: https://www. bis. org/fsi/publ/insights63. pdf.
Danielsson, J., & Uthemann, A. (2024). On the use of artificial intelligence in financial regulations and the impact on financial stability (First version September 2023). Systemic Risk Centre, London School of Economics. 
Deutsche Bundesbank. (2025). Monetary policy communication according to artificial intelligence. Monthly Report – March 2025.
Dignum, V. (2019). Responsible artificial intelligence: how to develop and use AI in a responsible way (Vol. 2156). Cham: Springer.
Efuntade, A. O., & Efuntade, O. O. (2024). Linking artificial intelligence into management of liquidity by central bank: An exploratory review of Nigerian financial system. International Journal of Business and Finance Research, 10 (8), 91–99. https://doi.org/10.56201/ijbfr.v10.no8.2024.pg91.99.
European Central Bank. (2007). Understanding financial market liquidity. European Central Bank. https://www.ecb.europa.eu.
Hashemi Dizej, A. (2010). Money, currency, and banking (3rd ed.). Ardabil: Hafez Andisheh Publications.
Hernández de Cos, P. (2024, April 17). Managing AI in banking: Are we ready to cooperate? [Keynote speech]. Institute of International Finance Global Outlook Forum, Washington, DC. 
Holm-Hadulla, F., Mazelis, F., & Rast, S. (2023). Bank and non-bank balance sheet responses to monetary policy shocks. Economics Letters, 222, 110918. https://doi.org/10.1016/j.econlet.2023.110918. 
Ingham, G., Coutts, K., & Konzelmann, S. (2016). Introduction: "Cranks" and "brave heretics": Rethinking money and banking after the Great Financial Crisis. Cambridge Journal of Economics, 40 (5), 1247–1257. https://doi.org/10.1093/cje/bew040. 
Jafarzadeh, B., & Akbari Fard, H. (2013). Economics of money and banking (2nd ed.). Noor-e Elm Publications [In Persian]. 
Kahyaoğlu, H. (2021). The Impact of Artificial Intelligence on Central Banking and Monetary Policies. The Impact of Artificial Intelligence on Governance, Economics and Finance, Volume I, 83-98.
Kolb, B. A. (1983). Principles of financial management. Texas: Business Publications Inc.
Lin, T. C. (2019). Artificial intelligence, finance, and the law. Fordham Law Review, 88(2), 531. 
Lopez-Corleone, M., Begum, S., & Sixuan Li, G. (2022). Artificial intelligence (AI) from a regulator’s perspective: The future of AI in central banking and financial services. Journal of AI, Robotics & Workplace Automation, 2(1), 7-16.
McLeay, M., Radia, A., & Thomas, R. (2014). Money creation in the modern economy. Bank of England Quarterly Bulletin, 14–27. https://www.bankofengland.co.uk/quarterly-bulletin/2014/q1/money-creation-in-the-modern-economy. 
Milana, C., & Ashta, A. (2021). Artificial intelligence techniques in finance and financial markets: A survey of the literature. Strategic Change, 30 (3), 189–209. https://doi.org/10.1002/jsc.2399. 
Moenjak, T. (2021). Central banking, monetary and financial stability: Theory and practice (A. Azizi & F. Nourbakhsh, Trans.; 2nd ed.). Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran.
Njoroge, L. (2024). Role of artificial intelligence (AI) in central banking: Implications for COMESA member central banks. COMESA Monetary Institute.
Ozili, P. K. (2020). Does competence of central bank governors influence financial stability? Future Business Journal, 6 (1), 24–34. https://doi.org/10.1186/s43093-020-00022-z. 
Ozili, P. K. (2024). Artificial intelligence in central banking: benefits and risks of AI for central banks. In Industrial Applications of Big Data, AI, and Blockchain (pp. 70-82). IGI Global.
Qian, Y. (2019). Central Bank Digital Currency: optimization of the currency system and its issuance design. China Economic Journal, 12(1), 1-15.
Shabsigh, M. G., & Boukherouaa, E. B. (2023). Generative artificial intelligence in finance: Risk considerations. International Monetary Fund.
Shim, J. K., & Constas, M. (2009). Encyclopedia of international finance and banking (A. Mojtahed et al., Trans.; 1st ed.). Tehran, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran.
Shirzad, A., & Rahmani, A. (2024). Smart Treasury: Leveraging Artificial Intelligence and Robotic Process Automation for Financial Excellence. Knowledge Economy Studies, 1(1), 65-86.
Veloso, M., Balch, T., Borrajo, D., Reddy, P., & Shah, S. (2021). Artificial intelligence research in finance:  discussion and examples.  Oxford Review of Economic Policy, 37(3), 564-584.
Wirtz, B. W., Weyerer, J. C., & Sturm, B. J. (2020). The darksides of artificial intelligence: An integrated AI governance framework for public administration. International Journal of Public Administration, 43 (9), 818–829. https://doi.org/10.1080/01900692.2020.1749851.
Knowledge Economy Studies
Volume 2, Issue 1
April 2025
Pages 79-97

Home

Submit Manuscript

Contact Us