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In 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. Copy claim link
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Date 2021-10-22 · publication Records dated 2021 → Role Articulation Register (kind of text) Nonfiction Scope and limits A statement of what the text says, not evidence that the risk has materialised or that any authority has adopted a policy. A staff paper attributed to its authors.
The evidence 03 primary source Supports the claim
Powering the Digital Economy: Opportunities and Risks of Artificial Intelligence in Finance ↗ International Monetary Fund · 2021-10-22
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Source excerpt “The concentration of third-party AI/ML algorithm providers could drive greater homogeneity in risk assessments and credit decisions in the financial sector, which, coupled with rising interconnectedness, could create the conditions for a buildup of systemic risks.” Location in source Chapter 3, section F “Impact on Financial Stability”, second bullet (HTML)
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Machine-checked · 2026-11-06
Source details and check notes Authors El Bachir Boukherouaa; Ghiath Shabsigh; Khaled AlAjmi; Jose Deodoro; Aquiles Farias; Ebru S. Iskender; Alin T. Mirestean; Rangachary Ravikumar Version 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) Canonical address Open the canonical source ↗ Accessed 2026-11-06 Language English (en) Attribution El Bachir Boukherouaa, Ghiath Shabsigh, Khaled AlAjmi, Jose Deodoro, Aquiles Farias, Ebru S. Iskender, Alin T. Mirestean, Rangachary Ravikumar, “Powering the Digital Economy: Opportunities and Risks of Artificial Intelligence in Finance”, 2021-10-22. Reuse No open redistribution licence asserted. Bibliographic metadata, editorial paraphrases and short attributed quotations (at most 50 words each). Recheck terms before wider redistribution. Check notes Candidate pack passage, AI and money (research/ai-money). The quotation (36 words) matched a fresh retrieval of 2026-11-06. Matching ignored differences of whitespace, case, quotation marks, dashes, line-break hyphens and Unicode compatibility forms. No human editorial review. primary source Supports the claim
Powering the Digital Economy: Opportunities and Risks of Artificial Intelligence in Finance ↗ International Monetary Fund · 2021-10-22
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Source excerpt “The widespread use of AI/ML could potentially increase procyclicality of financial conditions.” Location in source Chapter 3, section F, third bullet (HTML)
How it was read Retrieved directly from the publisher
Machine-checked · 2026-11-06
Source details and check notes Authors El Bachir Boukherouaa; Ghiath Shabsigh; Khaled AlAjmi; Jose Deodoro; Aquiles Farias; Ebru S. Iskender; Alin T. Mirestean; Rangachary Ravikumar Version 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) Canonical address Open the canonical source ↗ Accessed 2026-11-06 Language English (en) Attribution El Bachir Boukherouaa, Ghiath Shabsigh, Khaled AlAjmi, Jose Deodoro, Aquiles Farias, Ebru S. Iskender, Alin T. Mirestean, Rangachary Ravikumar, “Powering the Digital Economy: Opportunities and Risks of Artificial Intelligence in Finance”, 2021-10-22. Reuse No open redistribution licence asserted. Bibliographic metadata, editorial paraphrases and short attributed quotations (at most 50 words each). Recheck terms before wider redistribution. Check notes Candidate pack passage, AI and money (research/ai-money). The quotation (12 words) matched a fresh retrieval of 2026-11-06. Matching ignored differences of whitespace, case, quotation marks, dashes, line-break hyphens and Unicode compatibility forms. No human editorial review. primary source Context only
Powering the Digital Economy: Opportunities and Risks of Artificial Intelligence in Finance (DP/2021/024, PDF) ↗ International Monetary Fund · 2021-10-22
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Source excerpt “The views expressed in this paper are those of the author(s) and do not necessarily represent the views of the IMF, its Executive Board, or IMF management.” Location in source PDF p. 3, series note
How it was read Retrieved directly from the publisher
Machine-checked · 2026-11-06
Source details and check notes Authors El Bachir Boukherouaa; Ghiath Shabsigh; Khaled AlAjmi; Jose Deodoro; Aquiles Farias; Ebru S. Iskender; Alin T. Mirestean; Rangachary Ravikumar Version 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 Canonical address Open the canonical source ↗ Accessed 2026-11-06 Language English (en) Attribution El Bachir Boukherouaa, Ghiath Shabsigh, Khaled AlAjmi, Jose Deodoro, Aquiles Farias, Ebru S. Iskender, Alin T. Mirestean, Rangachary Ravikumar, “Powering the Digital Economy: Opportunities and Risks of Artificial Intelligence in Finance (DP/2021/024, PDF)”, 2021-10-22. Reuse No open redistribution licence asserted. Bibliographic metadata, editorial paraphrases and short attributed quotations (at most 50 words each). Recheck terms before wider redistribution. Check notes Candidate pack passage, AI and money (research/ai-money). The text’s own statement of whose views it gives, shown beside the record; it is context, not support. The quotation matched a fresh retrieval of 2026-11-06. No human editorial review. Status and meaning Editorial status. Machine-checked . Machines found this record and checked it against its sources; no person accepted it individually. Each evidence record above shows how it was checked.
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Record ID am-u01-imf-2021-dp-ai-finance