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The FSB report of 1 November 2017 on artificial intelligence and machine learning in financial services states that if many market participants use similar AI and machine-learning programmes, the resulting correlated risks may entail financial stability risks and, as with any herding behaviour, could amplify financial shocks. Copy claim link
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Supporting evidence: primary · 1 source
Date 2017-11-01 · publication Records dated 2017 → 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. The report states that there was no evidence of this occurring at the time and frames it as a possibility with greater adoption; its analysis is described as preliminary.
The evidence 03 primary source Supports the claim
Artificial intelligence and machine learning in financial services: Market developments and financial stability implications ↗ Financial Stability Board · 2017-11-01
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Source excerpt “if many market participants come to use similar AI and machine learning programmes in areas such as credit scoring or financial market activities, the consequent correlated risks may entail financial stability risks.” Location in source Section 4.1, PDF p. 29 (printed p. 25)
How it was read Retrieved directly from the publisher
Machine-checked · 2026-11-06
Source details and check notes Authors Financial Stability Board Version Retrieved for the candidate pack on 2026-11-02 (SHA-256 25c70dafbd365900355dc39968f5c0be52117f52e246d29bb91c395d82701e93). Retrieved again at admission on 2026-11-06 (same file). PDF dated 1 November 2017 as served by fsb.org on 2026-11-02 (requested at the wp-content address, redirected to /uploads/P011117.pdf) Canonical address Open the canonical source ↗ Accessed 2026-11-06 Language English (en) Attribution Financial Stability Board, “Artificial intelligence and machine learning in financial services: Market developments and financial stability implications”, 2017-11-01. 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 (32 words) matched a fresh retrieval of 2026-11-06 (the same file the candidate pack read). 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
Artificial intelligence and machine learning in financial services: Market developments and financial stability implications ↗ Financial Stability Board · 2017-11-01
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Source excerpt “While there is no evidence of this occurring to date, this could become relevant with greater adoption of such trading strategies. As with any herding behaviour in the market, this has the potential to amplify financial shocks.” Location in source Section 4.1, PDF p. 29 (printed p. 25)
How it was read Retrieved directly from the publisher
Machine-checked · 2026-11-06
Source details and check notes Authors Financial Stability Board Version Retrieved for the candidate pack on 2026-11-02 (SHA-256 25c70dafbd365900355dc39968f5c0be52117f52e246d29bb91c395d82701e93). Retrieved again at admission on 2026-11-06 (same file). PDF dated 1 November 2017 as served by fsb.org on 2026-11-02 (requested at the wp-content address, redirected to /uploads/P011117.pdf) Canonical address Open the canonical source ↗ Accessed 2026-11-06 Language English (en) Attribution Financial Stability Board, “Artificial intelligence and machine learning in financial services: Market developments and financial stability implications”, 2017-11-01. 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 (37 words) matched a fresh retrieval of 2026-11-06 (the same file the candidate pack read). 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
Artificial intelligence and machine learning in financial services: Market developments and financial stability implications ↗ Financial Stability Board · 2017-11-01
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Cite the original source Cite the original document, not Selekoa. Check these details against it.
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Source excerpt “If a critical segment of financial institutions rely on the same data sources and algorithmic strategies, then under certain market conditions a shock to those data sources … could affect that segment as if it were a single node.” Location in source Section 5.3 “Networks and interconnectedness”, PDF p. 35 (printed p. 31)
How it was read Retrieved directly from the publisher
Machine-checked · 2026-11-06
Source details and check notes Authors Financial Stability Board Version Retrieved for the candidate pack on 2026-11-02 (SHA-256 25c70dafbd365900355dc39968f5c0be52117f52e246d29bb91c395d82701e93). Retrieved again at admission on 2026-11-06 (same file). PDF dated 1 November 2017 as served by fsb.org on 2026-11-02 (requested at the wp-content address, redirected to /uploads/P011117.pdf) Canonical address Open the canonical source ↗ Accessed 2026-11-06 Language English (en) Attribution Financial Stability Board, “Artificial intelligence and machine learning in financial services: Market developments and financial stability implications”, 2017-11-01. 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 (39 words) matched a fresh retrieval of 2026-11-06 (the same file the candidate pack read). Matching ignored differences of whitespace, case, quotation marks, dashes, line-break hyphens and Unicode compatibility forms. 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-fsb-2017-ai-ml