Machine learning at central banks
Working paper by Chiranjit Chakraborty, Andreas Joseph, published by the Bank of England. A staff paper is its authors’ text. Dated 2017-09.
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- Machine learning at central banks (Staff Working Paper No. 674) Bank of England · published 2017-09 · Retrieved for the candidate pack on 2026-11-02 (SHA-256 51eb4af7fa56e58d9a2d057dc51dda146ebb4842c98c8c1e87e1b667c14b425f). Retrieved again at admission on 2026-11-06 (same file). PDF of Staff Working Paper No. 674, September 2017, as served on 2026-11-02
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- AI and money: what central banks and financial authorities have said, 1997–2026 →2 records on this document
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- AI can improve nowcasting and policy analysisIn Bank of England Staff Working Paper No. 674 of September 2017, Chiranjit Chakraborty and Andreas Joseph introduce machine learning for central banking and policy analysis, present a case study projecting UK CPI inflation, and write that machine-learning models generally outperform traditional approaches in prediction tasks.2017-09 · publication · Stated in source · Supported Inspect claim & evidence ↗AI can improve nowcasting and policy analysis: propositions page →
- Supervisors should use AIIn Bank of England Staff Working Paper No. 674 of September 2017, Chiranjit Chakraborty and Andreas Joseph present a case study that models the detection of alerts on financial institutions’ balance sheets for banking supervision with machine-learning methods, which they write generally outperform traditional approaches in prediction.2017-09 · publication · Stated in source · Supported Inspect claim & evidence ↗Supervisors should use AI: propositions page →
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