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The FSB report of 1 November 2017 states that there were no known dedicated international standards on AI and machine learning, and that, as the current regulatory framework was not designed with such tools in mind, some regulatory practices may need revising for their benefits to be harnessed. Copy claim link
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Supporting evidence: primary · 1 source
Date 2017-11-01 · publication Records dated 2017 → Role Context Register (kind of text) Nonfiction Missing element A statement on whether existing frameworks broadly apply to AI or whether AI requires a separate framework. Scope and limits The passage on revising practices concerns firms’ and supervisors’ use of AI for compliance (RegTech and SupTech), not a judgement on whether existing rules cover the risks of AI.
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 “Because AI and machine learning applications are relatively new, there are no known dedicated international standards in this area.” Location in source Section 4.4, PDF p. 32 (printed p. 28)
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 (19 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 “as the current regulatory framework is not designed with the use of such tools in mind, some regulatory practices may need to be revised for the benefits of AI and machine learning techniques to be fully harnessed.” Location in source Section 5.4, PDF p. 36 (printed p. 32)
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. 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.
Relation. A passage of the document bears on the proposition without meeting its criterion; the record names the missing element. It is not an articulation and implies no influence.
Date. Date of publication, as the text gives it.
Record ID am-u12-fsb-2017-ai-ml-context