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The FSB report of 27 June 2017 on financial stability implications from FinTech states that some firms use AI for anti-money-laundering and fraud detection, that firms can use machine learning for credit monitoring and risk mitigation, and that these applications can help institutions better manage risks. Copy claim link
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Supporting evidence: primary · 1 source
Date 2017-06-27 · 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. Descriptions of reported uses and possible benefits, not an assessment of performance.
The evidence 02 primary source Supports the claim
Financial Stability Implications from FinTech: Supervisory and Regulatory Issues that Merit Authorities’ Attention ↗ Financial Stability Board · 2017-06-27
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Source excerpt “Some firms use AI for AML and fraud detection at financial institutions. Firms can use machine learning for credit monitoring, risk mitigation as well as fraud monitoring in banking.” Location in source Annex G, “Description”, PDF p. 59 (printed p. 55)
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 700f5d772032e790ff4e67d7d6f5941584a427678ef23a56e7b9407d0c827243). Retrieved again at admission on 2026-11-06 (same file). PDF dated 27 June 2017 as served by fsb.org on 2026-11-02 (requested at the wp-content address, redirected to /uploads/R270617.pdf) Canonical address Open the canonical source ↗ Accessed 2026-11-06 Language English (en) Attribution Financial Stability Board, “Financial Stability Implications from FinTech: Supervisory and Regulatory Issues that Merit Authorities’ Attention”, 2017-06-27. 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. primary source Supports the claim
Financial Stability Implications from FinTech: Supervisory and Regulatory Issues that Merit Authorities’ Attention ↗ Financial Stability Board · 2017-06-27
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Source excerpt “These applications can help financial institutions, as well as supervisors, better understand causal relationships and better manage risks, and regulatory compliance.” Location in source Annex G, “Potential to support financial stability”, PDF p. 60 (printed p. 56)
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 700f5d772032e790ff4e67d7d6f5941584a427678ef23a56e7b9407d0c827243). Retrieved again at admission on 2026-11-06 (same file). PDF dated 27 June 2017 as served by fsb.org on 2026-11-02 (requested at the wp-content address, redirected to /uploads/R270617.pdf) Canonical address Open the canonical source ↗ Accessed 2026-11-06 Language English (en) Attribution Financial Stability Board, “Financial Stability Implications from FinTech: Supervisory and Regulatory Issues that Merit Authorities’ Attention”, 2017-06-27. 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 (21 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-u10-fsb-2017-fintech-fs