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The FSB report of 1 November 2017 states that predictable patterns in the behaviour of automated trading strategies could be used by insiders or cybercriminals to manipulate market prices, and that uses of AI and machine learning should be assessed for risks including cybersecurity. Copy claim link
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Supporting evidence: primary · 1 source
Date 2017-11-01 · publication Records dated 2017 → Role Earliest located 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 manipulation passage concerns automated trading strategies, in a section on AI and machine learning in markets.
The evidence 02 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 “advanced optimisation techniques and predictable patterns in the behaviour of automated trading strategies could be used by insiders or by cybercriminals to manipulate market prices.” 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 (25 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 “It will be important to assess uses of AI and machine learning in view of their risks, including adherence to relevant protocols on data privacy, conduct risks, and cybersecurity.” Location in source Executive summary, PDF p. 6 (printed p. 2)
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 (29 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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Date. Date of publication, as the text gives it.
Record ID am-u03-fsb-2017-ai-ml