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The EBA Report on Big Data and Advanced Analytics of January 2020 states that machine-learning models can become “black boxes” whose reasoning is hard to understand and verify, and that lack of explainability could be an important risk for models bought from third parties, which the acquiring institution must be able to validate. Copy claim link
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Date 2020-01 · publication Records dated 2020 → 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. The passage concerns explainability as an element of trustworthy use by institutions.
The evidence 02 primary source Supports the claim
EBA Report on Big Data and Advanced Analytics (EBA/REP/2020/01) ↗ European Banking Authority · 2020-01
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Source excerpt “ML models can quickly become “black boxes”, opaque systems for which the internal behaviour cannot be easily understood, and for which therefore it is not easy to understand (and verify) how a model has reached a certain conclusion or prediction.” Location in source Section 4.2 “Explainability and interpretability”, PDF p. 35
How it was read Retrieved directly from the publisher
Machine-checked · 2026-11-06
Source details and check notes Authors European Banking Authority Version Retrieved for the candidate pack on 2026-11-02 (SHA-256 d8661c18c5e087f13c4a245896f077f64fb144413ea6f8f9379c3c7941fb09f6). Retrieved again at admission on 2026-11-06 (same file). PDF dated January 2020 as served by eba.europa.eu on 2026-11-02 Canonical address Open the canonical source ↗ Accessed 2026-11-06 Language English (en) Attribution European Banking Authority, “EBA Report on Big Data and Advanced Analytics (EBA/REP/2020/01)”, 2020-01. 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 (40 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
EBA Report on Big Data and Advanced Analytics (EBA/REP/2020/01) ↗ European Banking Authority · 2020-01
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Source excerpt “Lack of explainability could represent an important risk in the case of AI/ML models developed by external third parties and then sold as opaque black box packages.” Location in source Section 4.2, PDF p. 37
How it was read Retrieved directly from the publisher
Machine-checked · 2026-11-06
Source details and check notes Authors European Banking Authority Version Retrieved for the candidate pack on 2026-11-02 (SHA-256 d8661c18c5e087f13c4a245896f077f64fb144413ea6f8f9379c3c7941fb09f6). Retrieved again at admission on 2026-11-06 (same file). PDF dated January 2020 as served by eba.europa.eu on 2026-11-02 Canonical address Open the canonical source ↗ Accessed 2026-11-06 Language English (en) Attribution European Banking Authority, “EBA Report on Big Data and Advanced Analytics (EBA/REP/2020/01)”, 2020-01. 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 (27 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-u04-eba-2020-bdaa