Machine learning for IRB models: follow-up report from the consultation on the discussion paper on machine learning for IRB models (EBA/REP/2023/28)
Report published by the European Banking Authority as its own text. Dated 2023-08.
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- Machine learning for IRB models: follow-up report from the consultation on the discussion paper on machine learning for IRB models (EBA/REP/2023/28) European Banking Authority · published 2023-08 · Retrieved for the candidate pack on 2026-11-02 (SHA-256 2b0b4163180513fa04fc91ee705f1a9c7ff531ee1a3e537dff73d06c498d23e7). Retrieved again at admission on 2026-11-06 (same file). PDF dated August 2023 as served by eba.europa.eu 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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- The opacity of AI models complicates risk management and supervisionThe EBA follow-up report of August 2023 on machine learning for IRB models states that the main challenge discussed for using machine-learning techniques in IRB models is their complexity, which leads to difficulties in explaining their results, traceability and adequate understanding by management functions.2023-08 · publication · Stated in source · Supported Inspect claim & evidence ↗The opacity of AI models complicates risk management and supervision: propositions page →
- AI can improve financial firms’ risk managementThe EBA follow-up report of August 2023 on machine learning for IRB models states that, in credit risk, machine-learning models might improve predictive power, and that institutions use or intend to use them mainly for probability-of-default estimation.2023-08 · publication · Stated in source · Supported Inspect claim & evidence ↗AI can improve financial firms’ risk management: propositions page →
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