Published document record
EBA Report on Big Data and Advanced Analytics
PDF source copies
These PDFs are hosted here for continued access. Each is labelled as an unmodified official PDF or a converted reading copy. They are saved copies, not a live statement of the latest law or institutional endorsement. Official source links remain below.
Official PDF — unmodified source copy
If the PDF does not display in your browser, Open PDF in a new tab or download it below. Both use the copy hosted on this site.
Download PDF — 60 pages (2.17 MB)EBA/REP/2020/01. Title page identifies this document.
Source: European Banking Authority. Retrieved 2026-09-10.
Copy provenance and reuse
Unmodified source PDF. Source attribution and original notices are retained; see the source reuse terms. Source reuse terms. The database metadata licence does not replace these terms.
SHA-256:
d8661c18c5e087f13c4a245896f077f64fb144413ea6f8f9379c3c7941fb09f6
Official metadata
- Official title
- EBA Report on Big Data and Advanced Analytics
- Official reference
- EBA/REP/2020/01
- Document type
- Report
- Document date
- 2020-01-13
- Document date kind
- Publication
- Document-date evidence
- European Banking Authority · EBA release dated 13 January 2020: published today; linked Final Report last update 13 January 2020. — Exact official publication is the fallback document date; no exact independent issue day established.
- Publication date
- 2020-01-13
- Publication-date evidence
- European Banking Authority · Release dated 13 January 2020: EBA published today; matching Final Report download. — Establishes official publication of this version on 2020-01-13, before the 4 September 2026 cutoff.
- Additional official dates
- Cover issue: 2020-01 (month) · European Banking Authority · Cover issue month (or official citation recommendation for EASA Issue 02).
- Legal status
- Non binding
- Legal-status evidence
- European Banking Authority · PDF pp.4-6, Executive summary: ML focus, four governance pillars and trust elements. — Non-legislative report, scientific guidance, strategic workplan or consultation text; not an act creating binding law.
- Language
- en
Research classifications
These are researcher classifications used to organise and analyse the corpus; they are not official EU metadata.
- Record level
- Principal
- Version status
- Final
- Temporal collection
- Contemporary EU AI policy
- Relevance class
- Direct AI relevance
- Policy stage
- Agenda setting
- Corpus tier
- Directly related
- Sectors
- Policy membership
Classification evidence
- Relevance class: Direct AI relevance · European Banking Authority · PDF pp.4-6, Executive summary: ML focus, four governance pillars and trust elements. — AI/ML is a substantive regulatory or sectoral subject.
- Sector tags: Financial services · European Banking Authority · PDF pp.4-6, Executive summary: ML focus, four governance pillars and trust elements. — Addresses regulated banking, insurance or securities activities.
- Provenance tags: Authored by an EU agency or body · European Banking Authority · PDF pp.4-6, Executive summary: ML focus, four governance pillars and trust elements. — Produced within the named EU agency/body; named personal author credits remain separate.
- Provenance tags: Officially published · European Banking Authority · Official record with linked English document. — Official EU endpoint distributes this independently citable English text.
Production provenance
- Provenance tags
- Named bibliographic authors
- European Banking Authority · European Banking Authority · PDF institutional title and imprint.
- Institutions and roles
-
- European Banking Authority · Author · role evidence · PDF institutional title/imprint and substantive text.
- European Banking Authority · Official host · role evidence · Official publication record and linked English PDF.
- European Banking Authority · Publisher · role evidence · Official publication record and linked English PDF.
Official sources and identifiers
- Official source · Publisher/host: European Banking Authority
- Official source · Publisher/host: European Banking Authority
Research assessment
- Inclusion rationale
- Machine learning is treated as a core advanced-analytics technique and the report develops governance pillars and trust elements for its use in regulated banking and financial services.
- Researcher notes
- Cover gives January 2020 only; exact publication is the document-date fallback. PDF software author metadata is not treated as bibliographic authorship.
- Review status
- verified
Relationships
-
EBA Discussion Paper on machine learning for IRB models · Based on · EBA Report on Big Data and Advanced Analytics
Official relationship · Verified
Official rationale: Discussion paper p.7 Introduction explicitly builds on the 13 January 2020 BD&AA report and its ML framing.
Verification
- Expanded evidence review
- Verified
- Reviewed by
- Yichen Hao
- Evidence review date
- 2026-09-05T23:48:11Z
The evidence review date is not a separate human sign-off date. Review credit and evidence-review actions
- Last verified: 2026-09-05T23:48:11Z · EBA release dated 13 January 2020: published today; linked Final Report last update 13 January 2020. Official linked English manifestation reviewed.
- Last verified: 2026-09-05T23:48:11Z · PDF pp.4-6, Executive summary: ML focus, four governance pillars and trust elements. English text inspected in web extraction or Node fetch plus pypdf; no retained file snapshot claimed.