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El Bachir Boukherouaa, Khaled AlAjmi, Jose Deodoro, Aquiles Farias, and Rangachary Ravikumar

This paper discusses the impact of the rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector. It highlights the benefits these technologies bring in terms of financial deepening and efficiency, while raising concerns about its potential in widening the digital divide between advanced and developing economies. The paper advances the discussion on the impact of this technology by distilling and categorizing the unique risks that it could pose to the integrity and stability of the financial system, policy challenges, and potential regulatory approaches. The evolving nature of this technology and its application in finance means that the full extent of its strengths and weaknesses is yet to be fully understood. Given the risk of unexpected pitfalls, countries will need to strengthen prudential oversight.

Mr. Itai Agur, Jose Deodoro, Xavier Lavayssière, Soledad Martinez Peria, Mr. Damiano Sandri, Hervé Tourpe, and Mr. German Villegas Bauer
Whether in crypto assets or in CBDCs, design choices can make an important difference to the energy consumption of digital currencies. This paper establishes the main components and technological options that determine the energy profile of digital currencies. It draws on academic and industry estimates to compare digital currencies to each other and to existing payment systems and derives implications for the design of environmentally friendly CBDCs. For distributed ledger technologies, the key factors affecting energy consumption are the ability to control participation and the consensus algorithm. While crypto assets like Bitcoin are wasteful in terms of resources, other designs could be more energy efficient than existing payment systems.
Mr. Itai Agur, Jose Deodoro, Xavier Lavayssière, Soledad Martinez Peria, Mr. Damiano Sandri, Hervé Tourpe, and Mr. German Villegas Bauer

Whether in crypto assets or in CBDCs, design choices can make an important difference to the energy consumption of digital currencies. This paper establishes the main components and technological options that determine the energy profile of digital currencies. It draws on academic and industry estimates to compare digital currencies to each other and to existing payment systems and derives implications for the design of environmentally friendly CBDCs. For distributed ledger technologies, the key factors affecting energy consumption are the ability to control participation and the consensus algorithm. While crypto assets like Bitcoin are wasteful in terms of resources, other designs could be more energy efficient than existing payment systems.

Mr. Itai Agur, Jose Deodoro, Xavier Lavayssière, Soledad Martinez Peria, Mr. Damiano Sandri, Hervé Tourpe, and Mr. German Villegas Bauer
El Bachir Boukherouaa, Mr. Ghiath Shabsigh, Khaled AlAjmi, Jose Deodoro, Aquiles Farias, Ebru S Iskender, Mr. Alin T Mirestean, and Rangachary Ravikumar
This paper discusses the impact of the rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector. It highlights the benefits these technologies bring in terms of financial deepening and efficiency, while raising concerns about its potential in widening the digital divide between advanced and developing economies. The paper advances the discussion on the impact of this technology by distilling and categorizing the unique risks that it could pose to the integrity and stability of the financial system, policy challenges, and potential regulatory approaches. The evolving nature of this technology and its application in finance means that the full extent of its strengths and weaknesses is yet to be fully understood. Given the risk of unexpected pitfalls, countries will need to strengthen prudential oversight.