Big data and machine learning in central banking
Working paper by Sebastian Doerr, Leonardo Gambacorta, Jose Maria Serena, published by the Bank for International Settlements. A staff paper is its authors’ text. Dated 2021-03.
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- Big data and machine learning in central banking (BIS Working Papers No 930) Bank for International Settlements · published 2021-03 · 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
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- AI and money: what central banks and financial authorities have said, 1997–2026 →1 record on this document
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- Central banks need to build their own AI capacityBIS 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.2021-03 · publication · Stated in source · Supported Inspect claim & evidence ↗Central banks need to build their own AI capacity: propositions page →
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