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<p>Artificial Intelligence (AI) is transforming the regulatory framework of central banks, particularly by reshaping supervisory, compliance, and risk management mechanisms. This paper presents a comprehensive review of leveraging AI in central banking, focusing on regulatory systems, technological adaptation, and research trends in emerging economies. Following the PRISMA criteria, 235 peer-reviewed articles were sourced from the Scopus and Web of Science databases from 1999 to 2024. Bibliometric analysis of the data was conducted using R Studio and VOS viewer, revealing temporal drifts, source networks, spatial networks, and lexical networks. The findings show that the impact of AI on central banking has been growing, with a significant increase from 2016 and a sharp uplift between 2016 and 2020. The top contributing countries are the United States and the United Kingdom in the developed nations, while China, India, and Malaysia are the leading contributors among emerging countries. Key research topics on AI in central banking are financial resilience, central bank digital currencies, and regulatory responses to technological disruption, as well as AI’s strong capabilities in real-time data analysis, fraud detection, and risk management. Through a comprehensive review of AI’s transformative implications for central banking, this study identifies ethical and operational challenges facing the industry and offers crucial directions for future research.</p>

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Leveraging artificial intelligence for enhanced central banking regulation in emerging economies: A bibliometric analysis

  • 期刊论文

  • 发表日期：

    2025年12月1日

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  • Mohammad Sahabuddin,
  • Ferdowsy Begum,
  • Md. Abu Hamjalal Bubu,
  • Md. Shemul Sheikh,
  • Yasmin Jamadar

摘要

Artificial Intelligence (AI) is transforming the regulatory framework of central banks, particularly by reshaping supervisory, compliance, and risk management mechanisms. This paper presents a comprehensive review of leveraging AI in central banking, focusing on regulatory systems, technological adaptation, and research trends in emerging economies. Following the PRISMA criteria, 235 peer-reviewed articles were sourced from the Scopus and Web of Science databases from 1999 to 2024. Bibliometric analysis of the data was conducted using R Studio and VOS viewer, revealing temporal drifts, source networks, spatial networks, and lexical networks. The findings show that the impact of AI on central banking has been growing, with a significant increase from 2016 and a sharp uplift between 2016 and 2020. The top contributing countries are the United States and the United Kingdom in the developed nations, while China, India, and Malaysia are the leading contributors among emerging countries. Key research topics on AI in central banking are financial resilience, central bank digital currencies, and regulatory responses to technological disruption, as well as AI’s strong capabilities in real-time data analysis, fraud detection, and risk management. Through a comprehensive review of AI’s transformative implications for central banking, this study identifies ethical and operational challenges facing the industry and offers crucial directions for future research.