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The FSB report of 1 November 2017 states that the lack of interpretability or auditability of AI and machine-learning methods could become a macro-level risk if not appropriately supervised, and that widespread use of opaque models would make it very difficult for firms and supervisors to predict how model-directed actions affect markets. 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 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 “The lack of interpretability or ‘auditability’ of AI and machine learning methods has the potential to contribute to macro-level risk if not appropriately supervised by microprudential supervisors.” Location in source Section 6 “Conclusions”, PDF p. 37 (printed p. 33)
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 (27 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 would be very difficult for both firms and supervisors to predict how actions directed by models will affect markets.” Location in source Section 6, PDF p. 38 (printed p. 34)
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 (20 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-u04-fsb-2017-ai-ml