Powering the Digital Economy: Opportunities and Risks of Artificial Intelligence in Finance

Departmental Papers, October 22, 2021

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Canonical URL: Powering the Digital Economy: Opportunities and Risks of Artificial Intelligence in Finance

Authors: El Bachir Boukherouaa, Ghiath Shabsigh, Khaled AlAjmi, Jose Deodoro, Aquiles Farias, Ebru S Iskender, Alin T Mirestean, Rangachary Ravikumar
Published: October 22, 2021
Series: Departmental Papers
DOI: https://doi.org/10.5089/9781589063952.087

Rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector brings benefits in financial deepening and efficiency.
AI/ML adoption raises concerns about widening the digital divide between advanced and developing economies.
The paper distills and categorizes unique risks to the integrity and stability of the financial system posed by AI/ML.
The evolving nature of AI/ML and its application in finance means the full extent of strengths and weaknesses is yet to be fully understood.
Given the risk of unexpected pitfalls, countries will need to strengthen prudential oversight.

Potential to widen the digital divide between advanced and developing economies.
Risks to the integrity of the financial system.
Risks to the stability of the financial system.
Policy challenges stemming from evolving technology and applications.
Need for regulatory approaches tailored to AI/ML-specific risks.

Strengthen prudential oversight to address unexpected pitfalls associated with AI/ML deployment.
Advance discussion on policy challenges and potential regulatory approaches that account for the evolving nature of AI/ML in finance.
Categorize and target regulatory responses to the unique risks AI/ML poses to integrity and stability.

Subjects: Anti-money laundering and combating the financing of terrorism (AML/CFT), Artificial intelligence, Crime, Cyber risk, Economic sectors, Financial sector, Financial sector policy and analysis, Financial sector stability, Financial services, Fintech, Machine learning, Technology
Keywords: Anti-money laundering and combating the financing of terrorism (AML/CFT), Artificial intelligence, Artificial Intelligence, Cyber risk, Cybersecurity, Data Privacy, Embedded Bias, Financial Regulation, Financial sector, Financial sector stability, Financial Stability, Fintech, Global, IMF Library, Machine learning, Machine Learning, machine learning algorithm, machine learning capability, ML deployment, ML in finance, ML system, Risk Management, strategy landscape