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BIS Working Paper No 930 of March 2021, by Sebastian Doerr, Leonardo Gambacorta and Jose Maria Serena, reports that several central banks face constraints in IT infrastructure and human capital for big data and machine learning, and states that cooperation among public authorities could improve central banks’ ability to collect, store and analyse big data. Copy claim link
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Supporting evidence: primary · 1 source; Context: primary · 1 source
Date 2021-03 · publication Records dated 2021 → Role Earliest located Register (kind of text) Nonfiction Scope and limits A staff working paper under its disclaimer, drawing on an IFC survey. Its subject is big data used with machine learning, not AI generally.
The evidence 02 primary source Supports the claim
Big data and machine learning in central banking (BIS Working Papers No 930) ↗ Bank for International Settlements · 2021-03
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Source excerpt “Several institutions report constraints in setting up an adequate IT infrastructure and in developing the necessary human capital. Cooperation among public authorities could improve central banks' ability to collect, store and analyse big data.” Location in source PDF p. 3, abstract
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Machine-checked · 2026-11-06
Source details and check notes Authors Sebastian Doerr; Leonardo Gambacorta; Jose Maria Serena Version Retrieved for the candidate pack on 2026-11-02 (SHA-256 a79c10f9424b5aeca5d4f362877c2572a0453bc2e1763fd1253020de785ad36c). Retrieved again at admission on 2026-11-06 (same file). PDF as served on 2026-11-02 Canonical address Open the canonical source ↗ Accessed 2026-11-06 Language English (en) Attribution Sebastian Doerr, Leonardo Gambacorta, Jose Maria Serena, “Big data and machine learning in central banking (BIS Working Papers No 930)”, 2021-03. 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 (34 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 Context only
Big data and machine learning in central banking (BIS Working Papers No 930) ↗ Bank for International Settlements · 2021-03
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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 “The views expressed are those of the authors and not necessarily those of the BIS.” Location in source PDF p. 3, author note
How it was read Retrieved directly from the publisher
Machine-checked · 2026-11-06
Source details and check notes Authors Sebastian Doerr; Leonardo Gambacorta; Jose Maria Serena Version Retrieved for the candidate pack on 2026-11-02 (SHA-256 a79c10f9424b5aeca5d4f362877c2572a0453bc2e1763fd1253020de785ad36c). Retrieved again at admission on 2026-11-06 (same file). PDF as served on 2026-11-02 Canonical address Open the canonical source ↗ Accessed 2026-11-06 Language English (en) Attribution Sebastian Doerr, Leonardo Gambacorta, Jose Maria Serena, “Big data and machine learning in central banking (BIS Working Papers No 930)”, 2021-03. 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 text’s own statement of whose views it gives, shown beside the record; it is context, not support. The quotation matched a fresh retrieval of 2026-11-06. 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-u11-bis-wp-930