Powering the Digital Economy: Opportunities and Risks of Artificial Intelligence in Finance
Departmental paper by El Bachir Boukherouaa, Ghiath Shabsigh, Khaled AlAjmi, Jose Deodoro, Aquiles Farias, Ebru S. Iskender, Alin T. Mirestean, Rangachary Ravikumar, published by the International Monetary Fund. A staff paper is its authors’ text. Dated 2021-10-22.
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- Powering the Digital Economy: Opportunities and Risks of Artificial Intelligence in Finance International Monetary Fund · published 2021-10-22 · Retrieved for the candidate pack on 2026-11-02 (SHA-256 90973ad87869f334410b993b16c30df44e9a78e1107954eab82e0609a67d0651). Retrieved again at admission on 2026-11-06 (SHA-256 a3c72bc30e04773a36b586abd840bde6c17e39978674f8bf8c2aeb134847b19f; web pages are served with new markup on each request). IMF eLibrary HTML full text of Departmental Paper No. 2021/024 as served on 2026-11-02 (the eLibrary PDF download returned HTTP 202 with no body; imf.org refused, HTTP 403)
- Powering the Digital Economy: Opportunities and Risks of Artificial Intelligence in Finance (DP/2021/024, PDF) International Monetary Fund · published 2021-10-22 · Retrieved for the candidate pack on 2026-11-04 (SHA-256 1c331597155263949e804d936735ca13bfc0ca1f69b32c75b806eac70349dc71). Retrieved again at admission on 2026-11-06 (same file). PDF as served on 2026-11-04 to plain curl with its default user agent (`tools.mjs fetch`, with a browser user agent, receives HTTP 403; the cache entry was made by hand); the same SHA-256 as the copy a second check by a model of another family read
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- AI and money: what central banks and financial authorities have said, 1997–2026 →6 records on this document
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- AI raises financial-stability risks through correlated behaviourIn the IMF Departmental Paper of 22 October 2021, IMF staff authors El Bachir Boukherouaa, Khaled AlAjmi, Jose Deodoro, Aquiles Farias and Rangachary Ravikumar write that concentration of third-party AI/ML algorithm providers could drive greater homogeneity in risk assessments and credit decisions, with a risk of uniformity (herding), and that widespread AI/ML use could increase procyclicality.2021-10-22 · publication · Stated in source · Supported Inspect claim & evidence ↗AI raises financial-stability risks through correlated behaviour: propositions page →
- Reliance on a few AI providers creates concentration riskIn the IMF Departmental Paper of 22 October 2021, Boukherouaa, AlAjmi, Deodoro, Farias and Ravikumar write that AI/ML service providers could become systemically important participants in financial market infrastructure, increasing vulnerability to single points of failure.2021-10-22 · publication · Stated in source · Supported Inspect claim & evidence ↗Reliance on a few AI providers creates concentration risk: propositions page →
- AI increases cyber, fraud and operational risks in financeIn the IMF Departmental Paper of 22 October 2021, Boukherouaa, AlAjmi, Deodoro, Farias and Ravikumar write that AI/ML adoption increases the scope for cyber threats and brings new cyber risks, and that the cybersecurity regulatory perimeter could be expanded to cover AI/ML-specific threats.2021-10-22 · publication · Stated in source · Supported Inspect claim & evidence ↗AI increases cyber, fraud and operational risks in finance: propositions page →
- AI can improve nowcasting and policy analysisIn the IMF Departmental Paper of 22 October 2021, Boukherouaa, AlAjmi, Deodoro, Farias and Ravikumar write that AI/ML systems could help central banks improve their understanding of economic and financial developments and support better-tuned monetary and macroprudential policies, and that central bank experiments have focused on near-term forecasting and market sentiment.2021-10-22 · publication · Stated in source · Supported Inspect claim & evidence ↗AI can improve nowcasting and policy analysis: propositions page →
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- Central banks need to build their own AI capacityIn the IMF Departmental Paper of 22 October 2021, Boukherouaa, AlAjmi, Deodoro, Farias and Ravikumar write that central banks have been slow to adopt AI/ML, attributing this in part to a lack of adequate capacity, and that risks would be amplified if a central bank lacks the resources and skills to operate AI/ML safely.2021-10-22 · publication · Stated in source · Supported Inspect claim & evidence ↗Central banks need to build their own AI capacity: propositions page →
- Existing financial rules broadly cover AIIn the IMF Departmental Paper of 22 October 2021, Boukherouaa and Shabsigh, with AlAjmi, Deodoro, Farias, Iskender, Mirestean and Ravikumar, write that regulatory gaps could affect financial stability if technological advances outpace existing regulations, and that an adequate policy response requires clear minimum standards and guidelines for the sector; they report that some jurisdictions have concluded existing regulations are sufficient.2021-10-22 · publication · Stated in source · Supported Inspect claim & evidence ↗Existing financial rules broadly cover AI: propositions page →
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