Beneficial ownership data
Expert Claude skill for beneficial ownership data, the Beneficial Ownership Data Standard, international policy context, and country-specific registers
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Expert reference for beneficial ownership data, policy, and BODS. Trigger on: BODS JSON/schema/tools (bodsdata, CoVE-BODS, RDF/SPARQL, open issues), BO registries, FATF R24/R25, FATF mutual evaluations (MERs, FSRBs: APG/CFATF/MONEYVAL/ESAAMLG/MENAFATF/GIABA/EAG/GAFILAT), EU AML/AMLD6/AMLR/BORIS, country BO data (UK, Norway, France, Indonesia, Denmark, Canada/Ontario, Sri Lanka, BVI, Philippines, Ghana, Sweden), GLEIF, corporate data (OpenCorporates, Kyckr, Kausate, Sayari, ICIJ), FtM/OpenSanctions, Neo4j, BODS case studies (Latvia, Armenia, Nigeria), BO in procurement (OCDS, ChileCompra, Slovakia, PhilGEPS), BO in energy/extractives (EITI, GEM), BO in fisheries (GFW, FiTI), BO forms (Ghana, Namibia, PSC01), ICIJ/Panama Papers, BO reports (World Bank, TI, TI-UK), GODIN, UBO APIs (Kyckr, Kausate, KvK, Signicat, Companies House), BO verification (FATF, OECD toolkit, TJN), BOVS, or 2026 developments (BVI, Sri Lanka, Sweden, Ontario, Philippines, St Helena). If the question is about who owns what, use this skill.
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Beneficial Ownership Data — Expert Reference
This skill covers the full beneficial ownership data landscape: the BODS technical standard, OpenOwnership's ecosystem of tools, the regulatory policy context (FATF, EU AML), country-specific register designs, international advocacy, mapping corporate data sources to BODS, interoperability with other data models, beneficial ownership in procurement, and beneficial ownership in extractives.
Important context: This skill is used by Stephen Abbott Pugh — the original product owner of BODS at Open Ownership, now running the consultancy Understand Beneficial Ownership (beneficialownership.co.uk). His writing is at stephenabbottpugh.medium.com and beneficialownership.co.uk/news-articles-and-blog-posts. When helping Stephen, you can assume deep domain expertise on his part — be direct and specific rather than over-explaining fundamentals.
Always fetch live documentation when you need precise schema details; the standard is versioned and evolving.
Quick reference: Key URLs
BODS Standard & Tools
Stephen's BODS Conversion Repositories
GLEIF → BODS 0.4
| Resource | URL |
|---|---|
| OpenOwnership news: GLEIF data in BODS 0.4 | https://www.openownership.org/en/news/global-legal-entity-ownership-data-available-in-line-with-latest-version-of-data-standard/ |
| GLEIF BODS 0.4 dataset (explorer) | https://bods-data.openownership.org/source/gleif_version_0_4/ |
| bods-gleif-pipeline (GitHub) | https://github.com/openownership/bods-gleif-pipeline/ |
| Blog: updating GLEIF → BODS mapping | https://www.openownership.org/en/blog/updating-our-mapping-of-gleif-data-to-bods-to-better-capture-the-lifecycle-of-lei-data-changes/ |
Corporate Ownership Data Sources
Private Sector & Register APIs: UBO/PSC Data
| Resource | URL |
|---|---|
| Kyckr company API (v2) overview | https://developer.kyckr.com/api/company-v2/#/ |
| Kyckr CorporationUBO schema | https://developer.kyckr.com/api/company-v2/#/schemas/CorporationUBO |
| Kyckr IndividualUBO schema | https://developer.kyckr.com/api/company-v2/#/schemas/IndividualUBO |
| Kyckr OtherUBO schema | https://developer.kyckr.com/api/company-v2/#/schemas/OtherUBO |
| Stephen's bods-kyckr mapping repo | https://github.com/StephenAbbott/bods-kyckr |
| Kausate extractUBOs endpoint | https://docs.kausate.com/api-reference/company-data/extractUBOs |
| Netherlands KvK UBO register API (Dataservice) | https://developers.kvk.nl/ |
| Sweden Bolagsverket API — FAQ | https://bolagsverket.se/apierochoppnadata/fragorochsvaromapierna.4611.html |
| Signicat UBO lookup (Mint step) | https://developer.signicat.com/docs/mint/steps/reference/data-verification/organisation-ubo-lookup/ |
| UK Companies House PSC API reference | https://developer-specs.company-information.service.gov.uk/companies-house-public-data-api/reference/persons-with-significant-control |
Neo4j Graph Database: BO Ownership Analysis
| Resource | URL |
|---|---|
| Neo4j UBO developer guide (UK Companies House) | https://neo4j.com/developer/industry-use-cases/finserv/retail-banking/company-ownership-ubo-graphs/ |
| erikbijl/neo4j-company-house-demo (GitHub) | https://github.com/erikbijl/neo4j-company-house-demo |
| Neo4j FinServ webinar recording (on-demand) | https://go.neo4j.com/WBREDU260210FinServ_On-Demand.html |
| GraphAware Hume + BODS webinar (OpenOwnership blog) | https://www.openownership.org/en/blog/join-our-event-master-complex-ubo-investigations-with-advanced-graph-technology/ |
| GraphAware Hume + BODS webinar (YouTube recording) | https://www.youtube.com/watch?v=BO6TVN5UL14 |
BODS Interoperability: Other Data Models
| Resource | URL |
|---|---|
| Senzing sz-semantics RDF namespace | https://github.com/senzing-garage/sz-semantics/wiki/ns |
| OpenSanctions OpenOwnership dataset | https://www.opensanctions.org/datasets/openownership/ |
| opensanctions/bods-ftm (archived) | https://github.com/opensanctions/bods-ftm |
| opensanctions/graph (successor) | https://github.com/opensanctions/graph |
BODS RDF: Linked Data & SPARQL
Beneficial Ownership in Procurement
Beneficial Ownership in Extractives (EITI)
Public Beneficial Ownership Registers
Policy & Regulation
FATF Mutual Evaluations & Country Reports
International Endorsements & Resources
Country-Specific Registers
EU BORIS: BO Registers Interconnection System
Stephen's Writing & Consultancy
| Resource | URL |
|---|---|
| Stephen's Medium blog | https://stephenabbottpugh.medium.com/ |
| Stephen's website | https://www.beneficialownership.co.uk/ |
| Stephen's articles | https://www.beneficialownership.co.uk/news-articles-and-blog-posts |
| Case studies (BODS in use) | https://www.beneficialownership.co.uk/case-studies |
BODS Case Studies & Implementations
Full case studies index: https://www.beneficialownership.co.uk/case-studies
ICIJ Investigations & Offshore Leaks
| Resource | URL |
|---|---|
| ICIJ homepage | https://www.icij.org/ |
| ICIJ investigations index | https://www.icij.org/investigations/ |
| Panama Papers investigation | https://www.icij.org/investigations/panama-papers/ |
| Pandora Papers investigation | https://www.icij.org/investigations/pandora-papers/ |
| FinCEN Files investigation | https://www.icij.org/investigations/fincen-files/ |
| Offshore Leaks database | https://offshoreleaks.icij.org/ |
| Offshore Leaks data download | https://offshoreleaks.icij.org/pages/database |
| ICIJ GitHub (data tools) | https://github.com/ICIJ |
Key Beneficial Ownership Research Reports
GODIN: Global Open Data Integration Network
| Resource | URL |
|---|---|
| GODIN portal (hosted by GLEIF) | https://godin.gleif.org/ |
| Transparency Fabric (GODIN project) | https://transparencyfabric.gleif.org/ |
| GODIN GitHub repositories | https://github.com/orgs/Global-Open-Data-Integration-Network/repositories |
| GLEIF (member) | https://www.gleif.org/en |
| OpenOwnership (member) | https://www.openownership.org/en/ |
| Global Energy Monitor / GEOT (member) | https://globalenergymonitor.org/projects/global-energy-ownership-tracker/ |
| AC/DC — African Climate & Development (member) | https://acdatacollective.org/ |
| Media Registry (member) | https://www.mediaregistry.org/ |
| Open Data Services Co-op (member) | https://opendataservices.coop/ |
| OpenSanctions (member) | https://www.opensanctions.org/ |
| Data Research Center (member) | https://dataresearchcenter.org/ |
| Wikidata (supporter) | https://www.wikidata.org/wiki/Wikidata:Main_Page |
BO Declaration & Data Collection Forms
Beneficial Ownership Data Verification
BODS Development: GitHub Issues & Feature Tracker
Sectoral Use Cases: Energy & Extractives (Global Energy Monitor)
Sectoral Use Cases: Fisheries
For detailed reference material, read:
references/bods-standard.md— BODS 0.4 schema in depthreferences/tools-ecosystem.md— OpenOwnership toolsreferences/regulatory-context.md— FATF, EU AML, policy contextreferences/international-registers.md— country-specific BO register APIs
The BODS Data Model
BODS represents beneficial ownership as a collection of Statements. The current version is 0.4.
Three statement types
1. Person Statements
Describe a natural person who holds or may hold a beneficial ownership interest.
Key fields: statementId, statementType: "personStatement", names[], identifiers[], nationalities[], birthDate, placeOfBirth, addresses[], pepStatus[], hasPepStatus.
2. Entity Statements
Describe a legal entity (company, trust, foundation, etc.) in the ownership chain.
Key fields: statementId, statementType: "entityStatement", entityType, names[], identifiers[], incorporatedInJurisdiction, addresses[], foundingDate, dissolutionDate, isComponent.
3. Ownership-or-Control Statements
Link a person or entity (the interested party) to an entity (the subject), describing the nature of their interest.
Key fields: statementId, statementType: "ownershipOrControlStatement", subject (entity statementId), interestedParty (person or entity statementId), interests[] (type, share, directOrIndirect), isComponent, componentStatementIDs[].
Key structural concepts
statementId: UUID-based unique identifier for each statementisComponent: boolean; marks whether a statement is part of an indirect ownership chain (v0.4 addition)componentStatementIDs: array of statementIds making up an indirect chainpublicationDetails: metadata on publisher, date, bodsVersion- Temporal versioning: multiple statements can describe the same entity over time; use
replacesStatements[]to link them
A BODS dataset is a JSON array of statement objects. There is no wrapping container object — just a flat array.
Using BODS for Corporate Ownership Structures (without BO declarations)
BODS is designed for beneficial ownership but is equally capable of representing corporate ownership and control structures where the ultimate beneficial owners are unknown, undisclosed, or not the focus. This is a key use case for mapping commercial corporate data sources to BODS.
Why map corporate ownership data to BODS without BO declarations
Many real-world datasets — company registries, commercial data providers, financial data feeds — record legal entity ownership chains (parent/subsidiary relationships, shareholdings, directorship) without capturing natural-person beneficial owners. BODS accommodates this in several ways.
Entity-to-entity ownership: An ownership-or-control statement can link two entity statements, not just a person to an entity. This is the standard pattern for parent/subsidiary chains, joint ventures, and corporate group structures.
Unknown or anonymous interested parties: The interestedParty field supports unspecified as a value to indicate the interested party is not known. Use unknownPersons or anonymousEntity as the entity type when the ultimate owner is deliberately obscured or simply not recorded in the source data.
Partial chains: A dataset might record that Company A owns 60% of Company B, without knowing who owns Company A. This is perfectly valid BODS — just publish what is known. The isComponent flag and componentStatementIDs can be used to mark that a chain is incomplete.
entityType values for corporate structures: Beyond registeredEntity, BODS supports arrangement (for trusts, partnerships), anonymousEntity, unknownEntity, and stateBody. For offshore vehicles and special-purpose entities from sources like ICIJ Offshore Leaks, arrangement and anonymousEntity are most appropriate.
Mapping heuristics for source data without BO
When mapping a dataset that records corporate relationships but not BO:
- Map each company/legal entity to a BODS entity statement with the appropriate
entityType - Map each ownership/control link to a BODS ownership-or-control statement with
entityType-basedinterestedParty - For natural persons appearing in officer/director roles (not BO roles), create a person statement and an ownership-or-control statement with
interests[].type = "controlViaDirectorship"or"otherInfluenceOrControl" - Use heuristics to distinguish natural persons from corporate entities when source data is ambiguous (e.g. ICIJ officer names that could be either)
- Record
interests[].share.exactwhere share percentages are available; otherwise leave omitted or useminimum/maximumfields
Stephen's BODS Conversion Repositories
These are Stephen's Python repositories for transforming third-party corporate data sources into BODS 0.4. All are pure Python, structured as src/bods_<source>/ packages with tests.
bods-icij-offshoreleaks
Source: ICIJ Offshore Leaks database — covering Panama Papers (2016), Pandora Papers (2021), Bahamas Leaks (2016), Paradise Papers (2017), Offshore Leaks (2013). 810,000+ offshore entities.
Mapping approach:
- ICIJ
Entitynodes → BODS entity statements (registeredEntityorarrangementfor offshore vehicles) - ICIJ
Officernodes → person statements or entity statements (heuristics classify names as natural person vs. corporate) - ICIJ
Intermediarynodes → entity statements (registeredEntity, service provider firms) - ICIJ relationship types (
officer_of,intermediary_of, etc.) → BODS ownership-or-control statements with appropriateinterests[].type - Neo4J export also available for graph database workflows
Repo: https://github.com/StephenAbbott/bods-icij-offshoreleaks
bods-opencorporates
Source: OpenCorporates relationship data — the world's largest open company database, 200M+ companies.
OpenCorporates tracks four relationship types: control_statement, subsidiary, branch, and share_parcel. The Relationships Supplement contains 30M+ relationships extracted from primary datasets (SEC, UK Companies House, etc.).
Repo: https://github.com/StephenAbbott/bods-opencorporates
bods-brightquery
Source: BrightQuery corporate data via opendata.org — 324M organisations, 512M locations, 1.2B contacts across 222 countries. Government-sourced data including corporate family structures, legal status, and identity crosswalks (LEI, CIK, ISIN, NPI, etc.).
Repo: https://github.com/StephenAbbott/bods-brightquery
bods-kyckr
Source: Kyckr relationship data — a company intelligence platform providing corporate registry data and ownership relationships.
Repo: https://github.com/StephenAbbott/bods-kyckr
bods-ftm
Conversion: BODS 0.4 ↔ FollowTheMoney (FtM) — bidirectional.
Repo: https://github.com/StephenAbbott/bods-ftm
Note: this is distinct from the archived opensanctions/bods-ftm (which only converted OpenOwnership data dumps to FtM and is no longer maintained). Stephen's bods-ftm is a current, bidirectional converter designed for general BODS 0.4 data.
BODS → FtM mappings:
entityStatement→ FtMCompanypersonStatement→ FtMPersonownershipOrControlStatement→ FtMOwnership,Directorship, orUnknownLink(depending on interest type)
FtM → BODS mappings: reverse conversion using deterministic UUID5 hashing for consistent identifier generation.
Technical approach: two-pass processing (entities/persons first, then relationships); indirect ownership chains consolidated rather than split; converts between org-id.guide scheme codes (e.g., GB-COH) and FtM named properties (e.g., registrationNumber).
CLI: cli.py | Input: BODS or FtM JSON/JSONL | Output: converted format with full ownership relationship chains preserved.
bods-aml-ai
Conversion: BODS 0.4 → Google Anti-Money Laundering AI input format.
Repo: https://github.com/StephenAbbott/bods-aml-ai
Google's AML AI data model has no native concept of party-to-party ownership relationships, so the tool encodes beneficial ownership creatively through available AML AI constructs:
Output (three NDJSON files):
party.ndjson— persons and entities asCOMPANYorCONSUMERtypesparty_supplementary_data.ndjson— numeric ownership attributes (e.g.,bo_ownership_pct_{subject_id},bo_is_beneficial_owner, interest types)account_party_link.ndjson— synthetic "ownership accounts" linking subjects (PRIMARY_HOLDER) to owners (SUPPLEMENTARY_HOLDER)
CLI: cli.py | Input: BODS v0.4 JSON/JSONL | Output: NDJSON files for AML AI ingestion.
bods-neo4j
Conversion: BODS 0.4 ↔ Neo4j graph database — bidirectional, with built-in graph analysis.
Repo: https://github.com/StephenAbbott/bods-neo4j
Note: this is Stephen's BODS-native converter. For the broader Neo4j + UK Companies House PSC demo (without BODS), see erikbijl/neo4j-company-house-demo in the Neo4j section of Developer workflows.
Three primary workflows:
- BODS → Neo4j: import BODS ownership datasets into graph form via CSV export or direct driver loading; produces Neo4j-importable CSV files and Cypher scripts
- Neo4j → BODS: export graph data back to standardised BODS JSONL, preserving all metadata (round-trip fidelity)
- Graph analysis: built-in queries for UBO detection, corporate group mapping, and circular ownership identification
CLI: cli.py | Input: BODS v0.4 JSON/JSONL or Neo4j instance | Output: Neo4j CSVs/Cypher or BODS JSONL.
bods-xml
Conversion: BODS 0.4 JSON → XML, in two output modes.
Repo: https://github.com/StephenAbbott/bods-xml
Two modes:
- Canonical (
canonical.py): a faithful XML serialisation of BODS 0.4 that preserves every field and mirrors the JSON structure, under the standard's namespace - MRAS preBODS (
profiles/mras.py): transforms the flat BODS statement array into Canada's Multijurisdictional Registry Access Service (MRAS) hierarchical XML format
Architecture: extensible profile system — additional output profiles (BORIS, XBRL, etc.) can be added as modules alongside the existing two.
CLI: cli.py | Input: BODS 0.4 JSON or JSONL | Output: XML | Tests: 31
bods-stream
Type: Live streaming web application — UK beneficial ownership changes in real time as BODS v0.4.
Repo: https://github.com/StephenAbbott/bods-stream Live demo: https://bods-stream.onrender.com/
Consumes the Companies House PSC Streaming API and converts every live PSC (Person with Significant Control) filing event into BODS v0.4 statements the moment it's filed — displayed as a BOVS diagram with the raw Companies House event and the mapped BODS statements side by side.
This is notable because almost no beneficial ownership registers offer a streaming API. The UK PSC stream is the standout public exception, and BODS is purpose-built to represent change (recordStatus new/updated/closed, replacesStatements, append-only). bods-stream makes that change model visible live.
What you see per event:
- BOVS diagram: interested party → subject company, interest type on the edge, jurisdiction/nationality flags, identity-verification tick, tinted by lifecycle
- Lifecycle badge:
NEW/UPDATED/CEASED(driven by BODSrecordStatus) - Risk signals (structural, no external calls): FATF black/grey list, non-EU jurisdiction, trust/arrangement, nominee, super-secure (opaque), sanctioned flag
- Prolific PSC signal: flags when one person appears as PSC of multiple companies in the session
- Live insight bar: individual vs corporate split, cessation rate, identity-verification rate, prolific PSC of the day
- Top-20 PSC nationalities (live flag tally)
- Pause/play with live event counter
Architecture: FastAPI backend (SSE relay — one long-lived CH stream connection, fan-out to many browsers) + React/Vite frontend. Single-process, in-memory state (lifecycle tracking, prolific tracker); nothing persisted to disk.
Lifecycle handling: The CH stream has no new/updated/closed concept. bods-stream maintains an in-memory map keyed on resource_uri (stable PSC id) to emit correct recordStatus values and replacesStatements references, including reconstructing a closed record from last-seen state when a deletion event arrives.
Privacy: Address and date of birth stripped at ingress — never broadcast or shown in UI. Date of birth used only briefly in-process for the prolific disambiguator.
Key dependency: bods-mapper — a separate shared repo containing the core Companies House → BODS v0.4 mapping logic, used by both bods-stream and OpenCheck to prevent the two apps drifting.
Replay mode: Set BODS_STREAM_REPLAY_FILE to a captured .jsonl to feed pre-recorded events through the live pipeline (useful outside UK office hours when the live feed is quiet).
Deployment: Docker image builds frontend and serves it with the API (same origin). Deployed on Render via render.yaml. Must run as one instance/one worker (in-memory state).
bods-mapper
Type: Shared Python library — canonical UK Companies House PSC → BODS v0.4 mapping core.
Repo: https://github.com/StephenAbbott/bods-mapper
Extracted from OpenCheck so that both opencheck and bods-stream use one canonical mapper and cannot drift apart. Takes a single Companies House PSC streaming event (the data block is identical to the REST PSC endpoint response) and emits a BODS v0.4 bundle containing:
- the subject company entity statement
- the interested party — a
knownPerson(individual PSC), entity statement (corporate/legal-person PSC), oranonymousPerson(super-secure PSC) - an ownership-or-control relationship statement
Key features:
- All 86 official
natures_of_controlcodes mapped to valid BODSinterestType, each with the official Companies House short descriptor ininterest.details - Cessation lifecycle: a ceased PSC produces a relationship with
recordStatus: "closed"— stablerecordId, distinctstatementId,interest.endDate, andreplacesStatementspointing to the originalnewstatement, per BODS information updates / record identifiers modelling rules - Robust country handling: emits a BODS
Countrycodeonly when a valid 2-letter ISO code resolves
Public API: map_psc_event, company_number_from_uri, parse_nature, describe_nature, PSC_NATURE_DESCRIPTIONS, country_object, statement factories (make_entity_statement, make_person_statement, make_relationship_statement), BODSBundle, stable_id, validate_shape
Requirements: Python ≥ 3.10, pycountry. MIT license (vendored CH nature descriptors under OGL v3.0).
opencheck
Type: Full customer due diligence (CDD) web application — LEI-powered, BODS v0.4 throughout.
Repo: https://github.com/StephenAbbott/opencheck Live demo: https://opencheck.onrender.com/
OpenCheck is a comprehensive open-source CDD tool that uses the Legal Entity Identifier as a connector spine to fan out across 29 national and international corporate data sources, mapping everything to BODS v0.4. Currently at Phase 50 (50 phases of active development, 337+ commits).
How it works: paste a LEI → GLEIF lookup → derive every cross-source identifier available (Companies House number, Norwegian org number, Irish CRO, Finnish Y-tunnus, Latvian, Lithuanian, Estonian, Czech IČO, Polish KRS, Austrian Firmenbuchnummer, Slovak IČO, French SIREN, Dutch KvK, Swedish org number, Swiss UID, Canadian corp number, Belgian enterprise number, Danish CVR, Croatian MBS, Australian ACN/ABN, OpenCorporates ID, Wikidata Q-ID, and more) → fan out across all active adapters → assemble into a single BODS v0.4 bundle → apply risk signals → offer export.
National ID search (Phase 50): look up any company by local registration number (CH number, KvK, orgnr, CVR, SIREN, etc.) — queries GLEIF's three registration-ID filter fields in parallel, scoped to the RA code. Covers 17 countries with active adapters.
Risk signal layer (12 signals) — mirrors the EU AMLA draft CDD RTS conditions for "complex corporate structures":
- Source-derived signals (nominee, super-secure/opaque, sanctioned flag)
- AMLA CDD RTS signals (trust/arrangement, non-EU jurisdiction, ≥3 ownership layers, composite threshold rule, subjective obfuscation advisory)
- FATF jurisdiction (black/grey list)
- Cross-source name match discrepancies
- ICIJ Offshore Leaks match
Export formats: JSON / JSONL / XML / ZIP (downloaded bundle includes LICENSES.md listing every contributing source).
Architecture: FastAPI backend (Python 63%) + React/TypeScript frontend, cache-first dispatch (stub mode without API keys, live mode opt-in per source via env vars). Uses bods-dagre for BOVS ownership diagrams and bods-mapper for CH PSC → BODS mapping.
Roadmap: live opentender.eu procurement integration; BODS RDF/SPARQL backbone via Oxigraph (load assembled BODS bundle into triple store, expose /sparql for Open Ownership red-flag queries).
bods-gql
Conversion: BODS 0.4 → Google BigQuery property graph, queryable with GQL (ISO/IEC 39075).
Repo: https://github.com/StephenAbbott/bods-gql
GQL (ISO/IEC 39075) is the international standard graph query language adopted in April 2024. It uses pattern-matching syntax similar to Cypher but with different syntax for quantified paths and aggregation. BigQuery now supports GQL for property graph queries.
Output:
- Node tables: entity and person nodes with names, jurisdictions, and identifiers
- Edge tables: ownership interest relationships with stake percentages
- Property graph DDL:
CREATE PROPERTY GRAPHstatements viagraph_schema/property_graph.py
Includes 14 pre-built GQL queries across three modules covering UBO detection, corporate group mapping, and circular ownership analysis. 59 tests. Demonstrated with public BigQuery datasets containing GLEIF and UK Companies House beneficial ownership data.
CLI: cli.py | Input: BODS v0.4 JSON/JSONL | Output: BigQuery CSV tables + GQL schema.
GLEIF Level 1 & 2 Data → BODS 0.4
The Global Legal Entity Identifier Foundation (GLEIF) publishes two levels of open data for the 2.6M+ entities holding a Legal Entity Identifier (LEI):
- Level 1 (LEI-CDF): Entity identity data — legal name, registered address, jurisdiction, entity status, entity type, registration dates
- Level 2 (RR-CDF — Relationship Records): Ownership relationships between LEI holders — parent/subsidiary links, percentage ownership, relationship status, and dates
- Level 2 (Reporting Exceptions): Cases where an LEI holder cannot or will not report their direct/ultimate parent — with a stated reason code
GLEIF → BODS 0.4 mapping
| GLEIF data | BODS statement type |
|---|---|
| Level 1: LEI-CDF record | Entity statement |
| Level 2: Relationship Record (RR-CDF) | Ownership-or-control statement |
| Level 2: Reporting Exception | Entity, Person, or OOC statement (depending on exception type) |
The bods-gleif-pipeline (https://github.com/openownership/bods-gleif-pipeline) is the reference implementation. It runs on AWS (Kinesis data streams for pipeline stages, Elasticsearch for persistence between runs, EC2 for compute). The raw GLEIF concatenated files are 8GB+ uncompressed.
GLEIF was the first dataset published in BODS 0.4, making it the reference example for temporal change tracking with replacesStatements and the isComponent pattern.
Key mapping decisions in the BODS 0.4 update:
- Reporting Exceptions are now modelled as BODS statements (rather than being dropped), allowing the reason for non-disclosure to be captured
- Temporal lifecycle of LEI data changes is represented via
replacesStatementslinks rather than overwriting
Published data: https://bods-data.openownership.org/source/gleif_version_0_4/ OpenOwnership news release: https://www.openownership.org/en/news/global-legal-entity-ownership-data-available-in-line-with-latest-version-of-data-standard/ Mapping blog post: https://www.openownership.org/en/blog/updating-our-mapping-of-gleif-data-to-bods-to-better-capture-the-lifecycle-of-lei-data-changes/
Corporate Ownership Data Sources: Background Reference
These are sources useful for mapping work or for contextualising BO data. Fetch live documentation for precise field-level detail.
Sayari
A corporate intelligence platform covering 450M+ entities from 700+ sources across 250+ jurisdictions, with 2B+ ownership and control records. Sayari applies entity resolution to link records across sources, generating possibly-same-as relationships where confidence is insufficient to fully merge. Coverage includes parent-subsidiary, shareholder, and beneficial ownership structures. Particularly strong on hard-to-access jurisdictions.
- Data model: https://documentation.sayari.com/sayari-library/data-model/data-model
- Documentation: https://documentation.sayari.com/home/overview
OpenCorporates
The world's largest open company database (200M+ companies). Offers four relationship types in its Relationships File/Supplement: control_statement, subsidiary, branch, share_parcel. The Relationships Supplement has 30M+ relationships from primary sources (SEC, UK Companies House, etc.) and is separately licensed from the company data. Also provides person-with-significant-control and beneficial_owner flags. The API (v0.4.8) exposes companies, officers, and relationships.
- API reference: https://api.opencorporates.com/documentation/API-Reference
- Relationships dictionary: https://knowledge.opencorporates.com/knowledge-base/data-dictionary-relationships/
- Officers dictionary: https://knowledge.opencorporates.com/knowledge-base/data-dictionary-officers/
- Relationship file key info: https://knowledge.opencorporates.com/knowledge-base/count-of-relationship-records/
BrightQuery / OpenData.org
BrightQuery (founded OpenData.org) provides government-sourced corporate data on 324M organisations, 512M locations, and 1.2B contacts across 222 countries. Data is structured around three core data dictionaries: organisations, locations, and people-business relationships. Key differentiator: comprehensive reference ID crosswalks (LEI, CIK, ISIN, NPI, PermID, OpenFIGI, SAM UEI, PlaceKey, OSM ID, etc.) and corporate family/hierarchy structures. OpenData.org was built with Senzing AI for entity resolution and positions itself as a consortium-governed open data platform.
- Organisations dictionary: https://opendata.org/data-dictionary/organizations
- Locations dictionary: https://opendata.org/data-dictionary/locations
- People-business dictionary: https://opendata.org/data-dictionary/people-business
InfobelPro
A global company data provider with 375M companies across 220 countries, sourcing data from 1,100+ official registries, tax authorities, and regulated filings. Provides 460+ firmographic, hierarchical, and technographic attributes per record, including ownership links and up to 8 years of historical records. Claims to trace every record to an official source (not aggregators or web scrapes). GDPR/CCPA compliant with stable entity IDs and standardised delivery across 200+ markets.
- Data overview: https://www.infobelpro.com/data
- Methodology: https://www.infobelpro.com/data/methodology
OECD-UNSD Multinational Enterprise Information Platform (MEIP)
A joint OECD/UN Statistics Division initiative tracking the 500 largest MNEs globally. The platform comprises a Global Register (subsidiary ownership structures and geographic footprint), a web presence register, and a media monitor. The 2024 data release (covering data as of 31 December 2024) added financial data (employees, revenue, net profit, R&D) extracted via AI from company filings and annual reports. Structured as an interactive dashboard with downloadable XLSX.
This is a useful reference dataset for mapping MNE corporate group structures to BODS, and for validating coverage of other corporate data sources.
- Platform: https://www.oecd.org/en/data/dashboards/oecd-unsd-multinational-enterprise-information-platform.html
- Methodology publication: https://www.oecd.org/en/publications/the-oecd-unsd-multinational-enterprise-information-platform_b7d90a06-en.html
- Global Register 2024 (XLSX): https://www.oecd.org/content/dam/oecd/en/data/dashboards/oecd-unsd-multinational-enterprise-information-platform/Global%20Register%202024%20-%20OECD-UNSD%20Multinational%20Enterprise%20Information%20Platform.xlsx
- 2026 data release blog: https://www.oecd.org/en/blogs/2026/03/MNE-thing-is-possible-New-OECD-UNSD-data-release-strengthens-open-evidence-on-multinational-enterprises.html
BODS Interoperability: Mappings to Other Data Models
FollowTheMoney (FtM) / OpenSanctions
FollowTheMoney (FtM) is the data model used by OpenSanctions and the broader Aleph investigative data ecosystem. It represents persons, companies, assets, relationships, and documents in a property graph format designed for investigative and compliance work.
bods-ftm — there are two distinct repos with this name:
- StephenAbbott/bods-ftm (https://github.com/StephenAbbott/bods-ftm) — current, bidirectional BODS 0.4 ↔ FtM converter for general use (see Stephen's BODS Conversion Repositories section for full details)
- opensanctions/bods-ftm (https://github.com/opensanctions/bods-ftm) — archived; was a one-way converter from OpenOwnership BODS data dumps to FtM object graphs. Its functionality has been incorporated into opensanctions/graph (https://github.com/opensanctions/graph), which now handles BODS and GLEIF RR files as inputs.
The OpenOwnership dataset on OpenSanctions (https://www.opensanctions.org/datasets/openownership/) republishes OpenOwnership BODS data in FtM format, making it available for cross-dataset analysis alongside sanctions lists, PEPs data, and company registries.
Practical use: BODS data in FtM format can be combined with OpenSanctions sanctions data and public procurement data (Open Contracting Data Standard) for cross-dataset risk detection. The OpenScreening proof-of-concept built on this approach matches beneficial owners to sanctions names via a graph database.
Senzing sz-semantics / RDF
The Senzing sz-semantics namespace (https://github.com/senzing-garage/sz-semantics/wiki/ns) defines an RDF Metadata Application Profile for representing entity resolution results as a knowledge graph. It explicitly aligns with BODS, NIEM, and FollowTheMoney as "popular controlled vocabularies used by Senzing partners."
The namespace provides:
sz:Entity— resolved entity (top-level concept)sz:Person,sz:Organization— entity subtypessz:DataRecord— source records contributing to entity resolutionsz:member_of— relationship predicate applicable to ownership/membership
This is relevant when combining BODS data with Senzing entity resolution output, or when building linked data representations that need to align BODS concepts with Senzing's resolved-entity model. The OpenData.org platform (BrightQuery) was built using Senzing AI for entity resolution.
Developer workflows
Validating BODS data
Use CoVE-BODS web tool: https://datareview.openownership.org Or use lib-cove-bods from the command line:
pip install lib-cove-bods
libcovebods your-data.json
Checks: required fields, valid enums, internal reference integrity, version compliance (0.1–0.4).
bods-validator — an alternative online validation and visualisation tool for BODS v0.4 data: Repo: https://github.com/StephenAbbott/bods-validator
Built with FastAPI (backend) and React/TypeScript (frontend). Performs two layers of validation:
- JSON schema compliance checks against BODS v0.4 schema
- 26 additional regulatory compliance assessments via lib-cove-bods
Three input methods: direct JSON paste, file upload, or URL retrieval. Outputs validation results with actionable guidance, interactive ownership visualisations using BOVS design conventions, and side-by-side comparisons of national data formats mapped to BODS standards. Includes example datasets from UK, France, Indonesia, and Norway.
Testing BODS implementations
Two companion packages provide a shared, canonical fixture suite for testing any tool that ingests, transforms, or emits BODS v0.4 statements:
bods-fixtures — the fixture data pack:
- Repo: https://github.com/StephenAbbott/bods-fixtures
- PyPI: https://pypi.org/project/bods-v04-fixtures/ (
pip install bods-v04-fixtures) - Provides small, curated BODS v0.4 statement bundles targeting specific semantic edge cases, each paired with a
.expected.mdspecification file describing correct adapter/query engine behaviour - Current coverage (v0.1.1): direct ownership, circular ownership, anonymous persons
- Import:
from bods_fixtures import load, list_cases - Acts as "the single source of truth" for fixtures across the BODS adapter ecosystem — ensures an entity observed in two sources produces equivalent BODS output
pytest-bods-fixtures — pytest plugin wrapping the data pack:
- Repo: https://github.com/StephenAbbott/pytest-bods-fixtures
- PyPI: https://pypi.org/project/pytest-bods-v04-fixtures/ (
pip install pytest-bods-v04-fixtures) - Exposes
bods_fixtureas an auto-parametrized pytest fixture — one test function runs against every conformance case in the data pack without manual parametrization boilerplate - Displays fixture name in test IDs, making failures easy to identify
- Supports filtering by record type via
by_record_type()
Both packages require Python ≥ 3.9. Fixture content is licensed CC-BY-SA 4.0; code is MIT.
Processing BODS data into flat formats
bodsdata (https://github.com/openownership/bodsdata) converts BODS JSON to:
- CSV / TSV
- SQLite
- Parquet
- PostgreSQL dump
It also runs consistency checks (required fields, duplicate statement IDs, broken internal references) and supports pandas/polars dataframe workflows. Use it when you need to load BODS data into a database or do tabular analysis.
BODSKit (https://bodskit.readthedocs.io) is a newer CLI suite with similar goals — worth checking for the latest capabilities.
Analysing BODS data in Python (notebooks)
bodsanalysis (https://github.com/openownership/bodsanalysis) provides:
qbods.py: functions for reading, summarising and analysing BODS 0.2 data- Jupyter notebooks:
latvia_demo.ipynb(Latvia register),Insights_UK_PSC_BODS-02.ipynb(UK People with Significant Control) - Runs on local Jupyter, Deepnote, or Google Colab
Note: the notebooks currently target BODS 0.2. For 0.4 data, adapt the field names (especially for isComponent and statement references).
Beneficial Ownership Visualisation System (BOVS)
The Beneficial Ownership Visualisation System (BOVS) is an OpenOwnership specification for how to illustrate beneficial ownership structures as clearly as possible.
URL: https://www.openownership.org/en/publications/beneficial-ownership-visualisation-system/
BOVS defines the rules for drawing BOVS Diagrams — a standardised visual language for representing ownership and control structures. Key characteristics:
- Compatible with any brand, style, colour scheme, or language
- Published under the GNU Free Documentation License (free to use by anyone building BO visualisations)
- Designed to help implementers choose how to represent different aspects of ownership — direct vs. indirect interests, unknown intermediaries, control vs. ownership, etc.
- Offered to anyone building visualisations of beneficial ownership structures, not just BODS users
BODS Visualisation Library — the BODS-specific implementation of BOVS: URL: https://www.openownership.org/en/publications/beneficial-ownership-data-standard-visualisation-library/
The BODS Visualisation Library bakes many of the BOVS rules into a reusable library designed for rendering BODS-structured data. It is already in production use in the official beneficial ownership registers of Armenia, Bermuda, and Botswana.
The bods-dagre npm package (see below) is the developer-facing tool that implements this library.
Visualising ownership graphs
visualisation-tool / bods-dagre turns BODS JSON into directed graph diagrams.
Input: a JSON array of BODS statements (person, entity, ownership-or-control). Output: SVG/canvas network diagram with:
- Person nodes (name, nationality flag, person-type icon)
- Entity nodes (name, jurisdiction flag, entity-type icon, public company indicator)
- Directed edges showing ownership/control relationships
npm package: @openownership/bods-dagre
npm install @openownership/bods-dagre
The tool handles temporal data — it filters to a snapshot at a given point in time when multiple versions of records exist. See the full spec at https://github.com/openownership/visualisation-tool/blob/main/docs/spec.md.
Neo4j Graph Database: UK Companies House UBO Analysis
Graph databases are a natural fit for beneficial ownership data — ownership chains, loops, and ultimate parent traversal are graph problems that relational databases handle poorly. Two resources demonstrate this with UK data:
Neo4j developer guide — Company Ownership & UBO Graphs URL: https://neo4j.com/developer/industry-use-cases/finserv/retail-banking/company-ownership-ubo-graphs/
Covers the conceptual case for graph technology for UBO analysis in financial services (retail banking context). Explains variable-length path traversal for finding ultimate beneficial owners, and introduces the UK PSC dataset as a practical source.
erikbijl/neo4j-company-house-demo Repo: https://github.com/erikbijl/neo4j-company-house-demo Webinar recording: https://go.neo4j.com/WBREDU260210FinServ_On-Demand.html
A working implementation using UK Companies House open data (snapshots from January 2026):
- Data sources: Companies House Company Data Product + PSC Data Product
- Graph model: five node types (Company, LegalEntity, Individual, Address, SIC-code) with three relationship types (OWNS, REGISTERED_AT, HAS_SIC)
- Key notebooks:
company_house_companies.ipynb(loads company/address/SIC data) andcompany_house_psc.ipynb(processes PSC ownership relationships) - Includes: pre-built Neo4j dashboard (Company_Profile_Dashboard_2026-03-31.json) and a database backup via Google Drive
- Enables variable-length ownership traversal, root entity identification, and detection of circular ownership structures
GraphAware Hume platform: BODS data + graph technology for UBO investigations Blog/event page: https://www.openownership.org/en/blog/join-our-event-master-complex-ubo-investigations-with-advanced-graph-technology/ YouTube recording: https://www.youtube.com/watch?v=BO6TVN5UL14
A webinar co-presented with Stephen Abbott Pugh showing how BODS-structured beneficial ownership data can be used alongside other data types in GraphAware's Hume platform (powered by Neo4j). Hume is a graph-based investigation platform used in financial crime, compliance, and investigative journalism contexts. The session demonstrated how BODS data integrates with Hume's entity resolution and link analysis capabilities for complex UBO investigations.
Relationship to BODS: The neo4j-company-house-demo uses UK PSC data directly rather than BODS JSON, but the graph model (person/entity nodes + ownership edges) closely mirrors the BODS statement model. BODS data — which standardises this structure across jurisdictions — maps naturally onto Neo4j's property graph model and would enable cross-jurisdictional UBO traversal in a single graph.
Generating test / sample BODS data
The BODS data generator is a Google Sheets template that lets anyone produce valid BODS JSON without writing code. It's the fastest way to create test data or demonstrate the standard to non-technical audiences.
- Template: https://docs.google.com/spreadsheets/d/1PHjwqiOguG8DqyXN75dNSpl_tNhTyelYav1B6sk8nRQ/
- User guide: https://www.openownership.org/en/publications/beneficial-ownership-data-standard-generator/user-guidance/
The sheet has three tabs mirroring the three BODS statement types:
1_person_main— person statement data2_entity_main— entity statement data3_ownership_control_main— ownership-or-control statement data
Output: paste from the Upload sheet into CoVE-BODS for validation and JSON download. Can also feed directly into the bods-dagre visualiser.
Note: the generator currently targets BODS 0.3. For 0.4 you may need to adjust output for isComponent and componentStatementIDs fields.
Working with BODS as Linked Data / RDF
bodsld (https://github.com/openownership/bodsld) provides:
- BODS 0.4 RDF vocabulary in Turtle format:
bods-vocabulary-0.4.0.ttl - HTML documentation: https://vocab.openownership.org/terms/bods-vocabulary-0.4.0.html
- Scripts to regenerate vocabulary from the JSON Schema
Note: bodsld maps the BODS schema to RDF vocabulary — it does not convert BODS instance data to RDF triples. If you need to convert actual BODS records to RDF, you'll need to write a custom transformation.
Common patterns and gotchas
Resolving references: Ownership-or-control statements reference persons and entities by statementId. When loading data, build a lookup dict keyed by statementId first, then resolve references.
Indirect ownership chains: In BODS 0.4, isComponent: true marks statements that are part of an indirect chain. The top-level statement uses componentStatementIDs to list the supporting component statements.
Temporal data: The same real-world entity may have multiple statements over time. To get the current picture, filter to the most recent statement for each statementId group (using replacesStatements).
Version detection: Check publicationDetails.bodsVersion to know which version of BODS the data conforms to. Field names and required properties differ between 0.2, 0.3, and 0.4.
Missing beneficial owners: BODS allows for unknownPersons, anonymousEntity, and similar placeholders — your code should handle these rather than assuming all interested parties resolve to named individuals.
Corporate-only datasets: When the source has no BO data, every interestedParty in an ownership-or-control statement will reference an entity statement (not a person statement). This is valid BODS — entity-to-entity ownership chains are fully supported.
Policy & Regulatory Context (summary)
For full detail, read references/regulatory-context.md.
FATF Recommendations 24 & 25
The Financial Action Task Force sets the global anti-money-laundering standards that drive most beneficial ownership register legislation.
- R.24 (Legal Persons): Requires countries to ensure that competent authorities have timely access to adequate, accurate and up-to-date beneficial ownership information on companies and other legal persons. Revised to be significantly stronger in 2022. Guidance published March 2023.
- R.25 (Legal Arrangements): Parallel requirements for trusts and similar legal arrangements (fiducie, fideicomiso, Waqf, Treuhand, etc.). Revised 2023 to bring requirements broadly in line with R.24.
A country's compliance with R.24 and R.25 is assessed during FATF mutual evaluations, which have significant diplomatic and financial consequences.
FATF Mutual Evaluations: Country-Level AML/CFT Assessments
Mutual evaluations are the primary mechanism by which FATF assesses whether countries are actually implementing the 40 Recommendations. When researching what AML/CFT legislation or BO requirements a specific country has in place — or how effectively they are enforcing them — the published mutual evaluation reports (MERs) and follow-up reports are the most authoritative and detailed source available.
How to find country reports
All FATF publications, filterable by country, are at: https://www.fatf-gafi.org/en/publications.html
This page lists every published MER, follow-up report, and other country-specific output for all FATF members and associate members. Each country has a tag page accessible from the publications index. Important: for countries that are members of a FATF-Style Regional Body (FSRB) rather than FATF itself, the full mutual evaluation report may be published on the FSRB's own website, with the FATF country page linking out to it. The Montserrat example illustrates this: the FATF page (https://www.fatf-gafi.org/en/publications/Mutualevaluations/Follow-upreportstothemutualevaluationofmontserrat.html) links to a report hosted on the CFATF website (https://www.cfatf-gafic.org/). When looking for a country's full MER, always check the FSRB's own website if the FATF page only shows a summary or a link.
Additional entry points:
- All countries page: https://www.fatf-gafi.org/en/countries.html — direct links to each country's profile and published reports
- Consolidated assessment ratings: https://www.fatf-gafi.org/en/publications/Mutualevaluations/Assessment-ratings.html — a spreadsheet of all technical compliance and effectiveness ratings from 2014 onwards across all assessed countries; the fastest way to compare multiple countries at once
- Mutual evaluations topic page: https://www.fatf-gafi.org/en/topics/mutual-evaluations.html — explains the process and links to recent reports
What mutual evaluations assess
The 4th-round methodology (https://www.fatf-gafi.org/en/publications/Mutualevaluations/Fatf-methodology.html) assesses countries on two dimensions:
Technical compliance — whether the country's laws, regulations, and institutional frameworks meet the requirements of each of the 40 Recommendations. Rated: Compliant (C), Largely Compliant (LC), Partially Compliant (PC), or Non-Compliant (NC). For BO purposes, the key ratings are on R.24 (legal persons) and R.25 (legal arrangements).
Effectiveness — whether the country's AML/CFT system is actually working in practice. Assessed across 11 Immediate Outcomes (IOs). For BO specifically, IO.5 covers "Legal persons and arrangements are prevented from misuse for money laundering or terrorist financing, and information on their beneficial ownership is available to competent authorities without impediment." Effectiveness ratings: Substantial, Moderate, Low, or Negligible.
A country can have high technical compliance (good laws) but low effectiveness (poor enforcement) — a common pattern revealed in MERs. Conversely, some countries with imperfect legislation may have robust enforcement practices. Reading both dimensions together is essential.
Post-evaluation monitoring
After an MER is published, countries enter a follow-up process. Reports are typically published:
- Regular follow-up: annual or biennial reports on progress against recommended actions
- Enhanced follow-up: for countries with significant deficiencies, more frequent and intensive monitoring
Countries with serious and strategic AML/CFT deficiencies may be placed on the Jurisdictions under Increased Monitoring list (the "grey list") — https://www.fatf-gafi.org/en/publications/High-risk-and-other-monitored-jurisdictions/ — which triggers enhanced due diligence by financial institutions globally and carries significant reputational and economic consequences. Countries with the most serious deficiencies may be called to action on the High-Risk Jurisdictions list (the "black list").
The FATF Global Network: FSRBs
The FATF Global Network comprises FATF itself (39 member jurisdictions) plus nine FATF-Style Regional Bodies (FSRBs), which collectively cover more than 200 jurisdictions globally. FSRBs conduct mutual evaluations of their member jurisdictions using the same FATF methodology, and publish their own reports — which are the primary source for most non-FATF-member country assessments.
| FSRB | Region | Website |
|---|---|---|
| APG — Asia/Pacific Group on Money Laundering | Asia-Pacific | https://www.apgml.org/ |
| CFATF — Caribbean Financial Action Task Force | Caribbean | https://www.cfatf-gafic.org/ |
| MONEYVAL — Committee of Experts on AML/CFT Measures | Council of Europe member states | https://www.coe.int/en/web/moneyval |
| ESAAMLG — Eastern & Southern Africa AML Group | Eastern & Southern Africa | https://www.esaamlg.org/ |
| MENAFATF — Middle East & North Africa FATF | MENA | https://www.menafatf.org/ |
| GIABA — Inter-Governmental Action Group against ML in West Africa | West Africa | https://www.giaba.org/ |
| EAG — Eurasian Group | Central Asia & Russia region | https://www.eurasiangroup.org/ |
| GAFILAT — Financial Action Task Force of Latin America | Latin America | https://www.gafilat.org/ |
| GABAC — Action Group against ML in Central Africa | Central Africa | https://www.gabac.org/ |
When researching a non-FATF member country's AML/CFT framework or BO requirements, identify which FSRB it belongs to and check that FSRB's website for the most recent MER and follow-up reports — these will contain the most detailed analysis of what legislation is in place and how effectively it is being implemented.
Using MERs for BO research
Mutual evaluation reports are typically 200–400 pages and contain the most granular publicly available analysis of a country's BO legal framework. For BO-specific research within an MER, the most relevant sections are:
- The Technical Compliance Annexe: detailed analysis of R.24 (legal persons) and R.25 (legal arrangements) — what laws are in place, what they require, where they fall short of the FATF standard, and the resulting rating
- Immediate Outcome 5: the effectiveness assessment of whether the BO framework is working in practice — how well competent authorities access and use BO information, how well obliged entities conduct customer due diligence, and what the quality of BO information in registers actually is
- Country context (early chapters): background on the country's legal system, entity types, and the scale of the corporate sector — essential context for understanding why certain BO risks are higher or lower
EU AML Package (2024)
The EU adopted a sweeping new AML package in May 2024, effective from 2027:
- AMLR — Regulation 2024/1624: Directly applicable rules for obliged entities (banks, lawyers, crypto). Lowers UBO threshold from >25% to ≥25% shareholding/voting rights. Requires multi-source verification of BO information.
- AMLD6 — Directive 2024/1640: Member State rules for central BO registers. Registers must hold more data, cover more entity types including non-EU entities with EU business. Registers must interconnect via European Central Platform. Transposition deadline: 10 July 2026.
- EC consultation on BO data formats: The Commission is consulting on standardised data formats for BO submissions to central registers — directly relevant to BODS adoption. See https://ec.europa.eu/info/law/better-regulation/have-your-say/initiatives/14851
UK government endorsement of BODS
The UK has formally adopted BODS as its open standard for beneficial ownership data: https://www.gov.uk/government/publications/open-standards-for-government/collect-use-and-exchange-beneficial-ownership-information
The UK Anti-Corruption Strategy 2025 includes commitments to push for international adoption of BODS.
BODS RDF: Linked Data and SPARQL Querying
The BODS RDF vocabulary (https://vocab.openownership.org/) enables beneficial ownership data to be published and queried as linked data. This extends the power of BODS significantly: ownership chains become graph traversal problems expressible in SPARQL.
What the vocabulary provides
The BODS 0.4 RDF vocabulary maps all three BODS statement types — person, entity, and ownership-or-control — to RDF classes and properties. The key property is bods:ownsOrControls, which captures a direct ownership or control relationship between two entities (or between a person and an entity). This allows chains to be traversed with path queries.
The full vocabulary documentation is at https://vocab.openownership.org/ with the data model at https://vocab.openownership.org/pages/1_datamodel.html.
SPARQL use cases (world.hey.com/cos series)
Four blog posts by the BODS RDF team document real SPARQL queries against the Open Ownership register:
-
Linking BODS with other datasets (https://world.hey.com/cos/using-bods-rdf-to-link-beneficial-ownership-records-with-other-datasets-0383cbd9): How to combine BODS RDF with other linked datasets (e.g. Wikidata, company registries) using shared entity identifiers. Covers federated queries and URI alignment.
-
SPARQL examples for BO use cases (https://world.hey.com/cos/bods-rdf-sparql-examples-for-various-beneficial-ownership-use-cases-284d6f73): A broad collection of queries covering: finding all companies owned by a person, tracing ownership chains of a given depth, identifying share percentages along a chain, filtering by interest type, and finding companies with anonymous/unknown owners.
-
Ultimate parents and corporate control (https://world.hey.com/cos/ultimate-parents-and-corporate-control-with-open-ownership-bd1ee35b): How to use property path queries (
bods:ownsOrControls+) to traverse chains and identify ultimate controlling entities regardless of chain length. Covers the distinction between direct and indirect control. -
Querying UBOs (https://world.hey.com/cos/querying-ubos-with-open-ownership-and-bods-rdf-6a272004): How to identify ultimate beneficial owners — the natural persons at the end of an ownership chain — using SPARQL. Includes queries that retrieve share percentages and interest types across intermediate links.
Risk detection proof of concept (bodsriskdetection)
The bodsriskdetection repository (https://github.com/openownership/bodsriskdetection) is a proof-of-concept system built on BODS RDF. It combines:
- BODS data from the UK register (converted to RDF)
- Public procurement data published in OCDS format
- Sanctions data from OpenSanctions
- ICIJ Offshore Leaks data
The SPARQL graph can then identify: companies owned/controlled by sanctioned individuals; networks that have been awarded large volumes of public contracts; and indirect risks — third parties connected to a target that are themselves sanctioned or PEPs.
Technical details: https://www.openownership.org/en/publications/bods-risk-detection/bods-risk-tdetection-technical-details/
Beneficial Ownership in Public Procurement
Linking beneficial ownership data with public procurement (contracting) data is one of the highest-impact use cases for BO transparency. It enables detection of conflicts of interest, sanctions exposure, bid-rigging networks, and related-party contracts.
OCDS and BODS: the core linkage mechanism
The Open Contracting Data Standard (OCDS) (https://standard.open-contracting.org/) is the open standard for publishing procurement data. It covers the full contracting cycle: planning, tender, award, contract, and implementation.
The key to combining OCDS and BODS is shared organisation identifiers. Both datasets should use the same identifier scheme (typically from the org-id.guide list) for the same legal entities. The OCDS guidance page on beneficial ownership (https://standard.open-contracting.org/latest/en/guidance/map/beneficial_ownership/) explains two approaches:
-
Separate registers with linked identifiers: BO data is published using BODS; procurement data is published using OCDS; they are joined via shared company identifiers. This is the preferred approach for countries with a central BO register.
-
BO data embedded in OCDS: The OCDS beneficial owners extension (https://extensions.open-contracting.org/en/extensions/beneficialOwners/master/) allows BO information to be published directly within an OCDS contracting process record. Useful when no separate BO register exists, or when the procurement system has a lower disclosure threshold than the register.
ChileCompra: the leading implementation
Chile has the most advanced operational integration of BO and procurement data globally (as of 2025–2026).
- Chile's procurement law was amended in December 2023 to require BO disclosure by all suppliers as a condition of participation.
- Every supplier that participated in 2025 disclosed its ownership information — covering 1M+ procurement procedures worth US$13 billion (January–September 2025). Over 185,000 beneficial owners are now on record.
- ChileCompra, the Comptroller-General, and the National Economic Prosecutor's Office have full access to BO data and use it for investigating economic crimes and non-competitive bidding practices.
- The definition of conflict of interest was broadened to cover all public officials and their relatives. Over 7,000 complaints received via a whistleblower hotline between 2023–2025, including 114 relating to conflicts of interest.
- In January 2026, ChileCompra announced detection of potential conflicts of interest worth CLP 3.452 billion through mass data cross-referencing.
- ChileCompra uses OCDS for structured procurement data publication.
Case study (OCP/OO, May 2025): https://www.open-contracting.org/resources/casestudy-bot-pp-chile/ OO publication: https://www.openownership.org/en/publications/beneficial-ownership-in-chiles-public-procurement-reform/
Slovakia RPVS: procurement-linked BO register
The Slovak Register partnerov verejného sektora (RPVS) (https://rpvs.gov.sk/rpvs) was one of the first purpose-built procurement BO registers, established in 2015. It lists individuals and organisations receiving public funds above a legal threshold. Companies face a ban of up to three years and fines up to €1 million for participating in procurement without registering.
RPVS data is available on OpenSanctions (https://www.opensanctions.org/datasets/sk_rpvs/) — sourced directly from the Ministry of Justice API — and on the BODS data explorer (https://bods-data.openownership.org/source/slovakia/).
Philippines PhilGEPS
The Philippines passed the New Government Procurement Act (Republic Act No. 12009) in July 2024, mandating BO disclosure by all bidders and contractors, with public access to the data. Key milestones:
- From 15 July 2025, corporations must submit GIS forms reflecting BO information to the Securities and Exchange Commission (SEC).
- A Data Sharing Agreement between PS-DBM and the SEC facilitates data exchange.
- PhilGEPS enhanced its Open Data Portal in October 2025, providing real-time procurement data including BO information.
Open data: https://philgeps.gov.ph/CmsHomePages/open-data
Entity identifiers in UK procurement data
A key technical challenge for joining BODS and OCDS data is identifier quality. A detailed analysis of entity identifier practices in UK public procurement data is available at: https://world.hey.com/cos/entity-identifiers-in-uk-public-procurement-data-5f3f3815
Beneficial Ownership in Extractives (EITI)
The Extractive Industries Transparency Initiative (EITI) is the primary global framework for transparency in the oil, gas, and mining sectors. BO disclosure is a mandatory requirement for EITI implementing countries.
EITI 2023 Standard: strengthened BO requirements
The 2023 EITI Standard significantly strengthened BO requirements (Requirement 2.5):
- Countries are encouraged to adopt a BO threshold of 10% or lower (down from the previous 25% norm). As of 2025, 50 EITI countries have defined BO thresholds; half set it at 10% or below. Specific examples: Argentina (1 share), Colombia (5%), Nigeria (5%), Senegal (2%).
- New requirement for full disclosure by politically exposed persons (PEPs) regardless of ownership level — to detect conflicts of interest in licensing.
- New requirement to disclose legal ownership structures as well as beneficial ownership, to enable tracing of full ownership chains.
- Encouragement for companies to disclose their complete ownership structure and chain where beneficial ownership is held indirectly.
2023 Standard PDF: https://eiti.org/sites/default/files/2023-06/2023%20EITI%20Standard.pdf
EITI State-Owned Enterprises (SOE) database
EITI launched a dedicated database of state-owned enterprises (https://soe-database.eiti.org/) covering ~100 SOEs across EITI implementing countries, with data going back to 2017. Key features:
- Data on SOE payments to government and other extractives disclosures
- Uses UUIDs for entities, enabling time-series analysis and interoperability with international databases
- Filterable by country, company, and sector
- API endpoint: https://soe-database.eiti.org/eiti_database
BODS mapping: A Jupyter notebook demonstrating how the EITI SOE database maps to BODS is at: https://github.com/civicliteracies/EITI_SDT_data_verification_and_validation/blob/sqlite/5_publish/1_test/eiti_bods_mapping.ipynb
The notebook shows how state bodies (ministries, agencies) holding direct or indirect controlling interests in SOEs can be represented using BODS entity statements and ownership-or-control statements, including the stateBody entityType and control interests without share percentages.
BODS guidance for representing SOEs
The BODS standard has specific guidance on representing state-owned enterprises: https://standard.openownership.org/en/0.3.0/schema/guidance/repr-state-owned-enterprises.html
Key modelling decisions for SOEs in BODS:
- Use
entityType: "stateBody"for the state or government agency holding the interest - Control relationships (e.g. board appointment powers, policy direction) use
interests[].type: "otherInfluenceOrControl"rather than shareholding types - Where the state holds both equity and control, use multiple
interests[]entries within a single OOC statement
Public Beneficial Ownership Registers: Selected Examples
These are examples of live public BO registers — useful as reference implementations, data sources for mapping work, or for understanding diverse approaches to BO disclosure.
| Country/System | Register | Notes |
|---|---|---|
| Armenia | https://old.e-register.am/en/ | Early public BO register; BODS-aligned; company and BO data searchable online |
| Botswana | https://www.cipa.co.bw/master/ui/start/CIPARegisterSearch | CIPA register; BODS data collection + visualisation library; online search |
| Canada | https://ised-isde.canada.ca/cc/lgcy/fdrlCrpSrch.html?lang=eng | Corporations Canada federal register (live January 2024); BODS-powered; Bill C-42 mandate |
| BVI | https://gov.vg/news/legitimate-interest-access-now-fully-operational-virgin-islands | Legitimate interest access live from 1 April 2026; one of the first UK Overseas Territories to go live |
| EU (BORIS) | https://webgate.ec.europa.eu/e-justice/searchBoris.do | Cross-border search of EU/EEA member state registers; Norway joined April 2026 as 17th connected jurisdiction; mostly paywalled |
| Ghana | https://orc.dntsystems.net/beneficial-ownership/ | ORC BO register; Companies Act 2019; BO1–BO4 form suite |
| Latvia | https://www.lursoft.lv/en/latvian-company-register | First country to publish national BO data in BODS (2021) |
| Namibia | https://www.bipa.na/beneficial-ownership/ | BIPA BO register; Companies Amendment Act 2023; ~45% compliance as of 2026 |
| Nigeria | https://bor.cac.gov.ng/ | CAC Beneficial Ownership Register; first African BODS implementation; 5% threshold |
| Philippines | http://linkedin.com/feed/update/urn:li:activity:7442395219033219072 | Public BO data for companies in public procurement; New Government Procurement Act (RA 12009, 2024) |
| Slovakia (RPVS) | https://rpvs.gov.sk/rpvs | Procurement-linked BO register; one of the first purpose-built procurement BO registers (2015) |
| Sri Lanka | https://bo.drc.gov.lk/login | BO Registry Module live from 30 March 2026 (Gazette 2480/48); BO1–BO7 form suite; Registrar of Companies |
| St Helena | https://drive.proton.me/urls/WEC6VHS4DW#GmckfehJ8yk2 | UK Overseas Territory; public BO register delivered via a shared Proton Drive folder |
| UK | https://find-and-update.company-information.service.gov.uk/ | Companies House PSC register; largest public BO dataset globally; canonical BODS reference implementation |
For a global overview of BO register status by country, see the OpenOwnership map: https://www.openownership.org/en/map/
EU BORIS: Beneficial Ownership Registers Interconnection System
BORIS (Beneficial Ownership Registers Interconnection System) is the EU's attempt to create a single search point for beneficial ownership data across EU and EEA member states, hosted on the European e-Justice Portal. In concept it should allow anyone — a compliance officer, investigator, or journalist — to conduct a single search and retrieve BO records from all connected national registers. In practice, its implementation has fallen significantly short of this goal.
Regulatory basis
BORIS is mandated by three successive AML directives and an implementing regulation:
- AMLD4 (2015/849): First required member states to establish central BO registers. https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=celex%3A32015L0849
- AMLD5 (2018/843): Required public access to BO registers and mandated interconnection of national registers. https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=celex%3A32018L0843
- Regulation 2021/369: The specific implementing regulation establishing the technical and functional specifications for BORIS. https://eur-lex.europa.eu/legal-content/EN/TXT/HTML/?uri=CELEX%3A32021R0369&from=EN
AMLD6 (2024/1640) and the 2024 AML Regulation (2024/1624) will significantly reshape the BO disclosure landscape from 2027, including interconnection requirements.
Current status and limitations
As of April 2026, BORIS has fallen well short of its original 2020 go-live target, though connectivity is gradually growing. Only 6 member states (Austria, Denmark, Greece, Latvia, Malta, Netherlands) have records fully searchable by name or company ID through the portal. Norway joined in April 2026 as the 17th connected jurisdiction, bringing the total number of EU/EEA countries that have completed the technical steps to provide data to the platform to 17 of 30 — but most records are either inaccessible or accessible only in paid PDF format.
Key structural limitations Stephen identifies in his Medium analysis (https://stephenabbottpugh.medium.com/challenges-in-realising-the-goal-of-the-eus-beneficial-ownership-registers-interconnection-system-7ec7b52575ae):
- No machine-readable data: Users can only download BO records as PDFs for individual companies; bulk data access is not available through BORIS
- Paywalled records: Most records require payment to access, limiting use by civil society and journalists
- Incomplete ownership chains: Records often show only direct beneficial owners; full chains through intermediate holding companies are rarely visible
- UBO Data Rulebook scope gap: The Rulebook underlying BORIS only covers legal persons — not legal arrangements (trusts, nominee relationships). BODS supports both, creating a structural gap between what BORIS captures and what full BO transparency requires
- Identifier fragmentation: BORIS relies on EUID-structured identifiers but many legal persons and arrangements lack an EUID, creating linkage failures across borders
- Uneven national data quality: The 17 connected registers have highly variable data quality, field coverage, and update frequencies. A search across BORIS does not guarantee comparable results across jurisdictions
Related analysis
- Stephen's Bluesky post on BORIS: https://bsky.app/profile/stephenabbottpugh.bsky.social/post/3lkbe4wona22j
- OO: value of connecting EU BO data: https://www.openownership.org/en/blog/the-value-of-connecting-beneficial-ownership-data-across-the-european-union/
- Transparency International: barriers for investigators across EU: https://www.transparency.org/en/news/barriers-investigators-face-across-eu-tracing-asset-ownership
Canada: Corporations Canada and the Pan-Canadian BO Register
Canada has moved from a fragmented, non-public BO regime to a public federal register and an ambitious programme to create a pan-Canadian repository using BODS.
Corporations Canada federal register
Canada launched its public, searchable beneficial ownership registry in January 2024 under Bill C-42 (An Act to amend the Canada Business Corporations Act). The register covers corporations incorporated under the Canada Business Corporations Act (CBCA), which includes all federally incorporated companies.
- Register search: https://ised-isde.canada.ca/cc/lgcy/fdrlCrpSrch.html?lang=eng
- The federal register uses BODS to structure and publish BO data. Open Ownership worked directly with ISED to implement BODS as the technical foundation.
- OO news: https://www.openownership.org/en/news/canada-passes-law-to-create-public-beneficial-ownership-register/
BOP2P: Beneficial Ownership Policy to Practice
The Beneficial Ownership Policy to Practice (BOP2P) programme (https://ised-isde.canada.ca/mras/partners/bop2p/) is Canada's federal-provincial-territorial initiative to create a pan-Canadian BO repository — a single point of access to BO data from federal and provincial/territorial registries across Canada, not just CBCA companies.
The programme operates through the Multijurisdictional Registry Access Service (MRAS), which already interconnects business registry data across Canadian jurisdictions. BOP2P is extending this to include BO data using BODS as the common data standard across jurisdictions.
Key design choices: BODS enables each jurisdiction to publish BO data in its own format and map to the standard, while the central MRAS layer aggregates into a coherent pan-Canadian view. Open Ownership is providing technical support including working with British Columbia — one of the first provinces implementing a provincial BO register expected around 2025.
Beneficial Ownership Declaration and Data Collection Forms
BO declaration forms are the primary mechanism through which companies and their owners submit beneficial ownership information to a register. Form design has significant downstream implications for data quality: poorly specified fields, missing validation, and ambiguous instructions produce unreliable data that cannot be effectively used or linked across registers.
OpenOwnership guidance: design principles and recommended fields
OpenOwnership has produced a suite of resources specifically for regulators and form designers.
Guide for regulators and designers (https://www.openownership.org/en/publications/beneficial-ownership-declaration-forms-guide-for-regulators-and-designers/): Covers the full process of form design — from defining legal scope, to structuring questions, to handling edge cases (joint ownership, nominee arrangements, trusts). Key principles: use unambiguous legal definitions for each data field; capture machine-readable identifiers (national ID number, date of birth, country of nationality) rather than relying on free-text names alone; include a clear effective date for each declaration; and design explicitly for update workflows, not just initial registration.
Example declaration form (https://www.openownership.org/en/publications/example-beneficial-ownership-declaration-form/): A reference implementation of a BO declaration form reflecting BODS data model requirements. Contains separate sections for: (1) company/legal entity being declared; (2) each beneficial owner — name, date of birth, nationality, country of residence, national identifier, nature of interest (shareholding percentage, voting rights, control mechanisms); (3) declarant details and signed attestation.
Example paper forms (https://www.openownership.org/en/publications/example-paper-forms-for-collecting-beneficial-ownership-data/): A set of five modular paper forms designed to be adaptable to different legal contexts. Covers natural persons, corporate beneficial owners, trusts, nominees, and declarations of no beneficial owner meeting the threshold.
Annex — information fields (https://www.openownership.org/en/publications/sufficiently-detailed-beneficial-ownership-information/annex-examples-of-information-fields-in-beneficial-ownership-declaration-forms/): A comparative analysis of the actual data fields used in BO forms across multiple jurisdictions. Useful for benchmarking what a register collects against best practice and BODS field coverage.
EITI model declaration form
The EITI model beneficial ownership declaration form (https://eiti.org/guidance-notes/beneficial-ownership-model-declaration-form) is designed for the extractive sector and aligned with the 2023 EITI Standard (Requirement 2.5). It collects: beneficial owner full name, nationality, country of residence, national ID number, date of birth; level of ownership (percentage); how control is exerted (direct equity, indirect equity, voting rights, right to appoint management, other); whether the owner is a PEP (full disclosure required regardless of ownership level); and a signed attestation with effective date. The form explicitly captures reporting exceptions — cases where a BO cannot be identified — with a reason field.
Country examples
Ghana — Office of the Registrar of Companies (ORC)
Ghana's Companies Act 2019 (Act 992) mandates BO disclosure for all companies registered in Ghana. The ORC uses a suite of differentiated forms depending on entity type:
- BO1 — general companies (natural persons as beneficial owners)
- BO2 — companies whose beneficial owners are themselves companies
- BO3 (https://orc.dntsystems.net/wp-content/uploads/2025/08/BO3-Listed-Company-BO-Form.pdf) — listed companies: captures the same core fields but with additional sections for stock exchange listing, ISIN/ticker, public float percentage, and identification of any beneficial owners who hold ≥5% of listed shares directly or indirectly
- BO4 (https://orc.dntsystems.net/wp-content/uploads/2025/08/BO4-Government-BO-Form.pdf) — government-owned entities: covers state bodies and SOEs; replaces natural-person BO identification with the details of the government ministry or agency holding the interest, the name and role of the political or administrative authority responsible, and the legal basis for government ownership
The form family illustrates how a register can accommodate the full range of entity types BODS models — registeredEntity, publiclyListedCompany, stateBody — within a single coherent disclosure regime.
Namibia — Business and Intellectual Property Authority (BIPA)
Namibia's Companies Amendment Act 2 of 2023 introduced mandatory BO disclosure. BIPA administers two forms:
- BO1: The primary declaration. Three sections — (A) company information and BO type; (B) beneficial owner particulars (full names, date of birth, nationality, residential address, national ID number, nature and extent of the beneficial interest); (C) completion notes and attestation. Covers natural persons, publicly listed companies, and government agencies as possible beneficial owner types.
- BO2 (https://www.bipa.na/download/beneficial-ownership-declaration-form-bo2/): A "no change" declaration for annual returns confirming that no material change to BO information has occurred since the last filing.
The August 2024 deadline required all existing companies to file or bring BO information up to date. As of 2026, compliance stands at approximately 45%.
UK — PSC01 (Companies House)
The UK PSC (Persons with Significant Control) regime is the world's largest public BO register by record count and the canonical reference implementation for BODS. The PSC01 form v4.0 (https://assets.publishing.service.gov.uk/media/6911eb1ce9348ac8fb54f480/PSC01_v4.0-FINAL.pdf) — updated November 2025 — is used to notify Companies House of an individual PSC.
Five conditions for significant control (any one triggers PSC status):
- Holds, directly or indirectly, more than 25% of shares
- Holds, directly or indirectly, more than 25% of voting rights
- Holds the right, directly or indirectly, to appoint or remove a majority of the board of directors
- Has the right to exercise, or actually exercises, significant influence or control over the company
- Has the right to exercise, or actually exercises, significant influence or control over a trust or firm that itself meets one of the above conditions
Fields collected: full name; date of birth (month and year only — day withheld from public register); nationality; country/state of residence; service address; usual residential address (protected — not on public register); nature of control (checkbox against each of the five conditions, with percentage bands for conditions 1–2: 25–50%, 50–75%, 75–100%); date of notification; and from November 2025, confirmation of identity verification status.
The v4.0 update brings mandatory identity verification into the form, aligning with the Economic Crime and Corporate Transparency Act 2023. PSCs are required to verify their identity with Companies House directly.
BODS Development: Open Issues and Feature Tracker
The BODS data-standard repository (https://github.com/openownership/data-standard) currently has 79 open issues. The BODS Feature Tracker project board (https://github.com/orgs/openownership/projects/9/views/1) organises feature development into Research, Proposed, and Implementation phases.
When helping with BODS schema questions, check this tracker first — some apparent "gaps" in 0.4 are already documented as known issues with active research underway.
Feature: Representing Assets (#752)
Status: Research. Urgency: Not currently urgent.
Proposal to extend BODS beyond its current scope of legal vehicles to represent the assets connected to beneficial ownership networks. Minimum viable fields suggested: assetType, assetId, assetName.
Asset classes identified as requiring representation: mining and drilling concessions (EITI); media outlets (Euromedia Ownership Monitor); energy projects (Global Energy Ownership Tracker); fishing and shipping vessels (Global Fishing Watch, Triton); financial assets (EU AMLD6, OECD CRS); mixed assets for wealth investigations.
Key design decision: financial assets derived from legal entity ownership (shares, options, fund units) should remain as interest types rather than distinct asset objects, to avoid complexity. Physical assets — land, vessels, bank accounts, concessions — are the primary target for a new assetStatement type.
See also: OO publication Bridging the Gap (https://www.openownership.org/en/publications/bridging-the-gap-for-effective-asset-transparency/).
Feature: BODS Simplification (#737)
Status: Open / Backlog.
Goal: identify and remove unnecessary complexity from BODS to make it easier to understand and implement. Areas under discussion:
- Terminology: Remove redundant synonyms (
element,claim,assertion); renameassertedBy→statedBy; replacesubjectwith clearer language - Schema restructuring: Streamline metadata outside
recordDetails; clarifydeclarationvsrecorddistinction - Potential removal:
isComponentandcomponentRecordIdsfields (#718) — these add significant complexity for a use case that may be better handled differently - Scope: Challenge whether PEP information belongs in a BO standard at all
Changes range from straightforward terminology fixes to potentially breaking schema restructuring, so the issue distinguishes quick wins from changes requiring broad stakeholder input.
Feature: Interest Modelling (#466)
Status: Research. Target: Potential BODS v1.0.
The ~20 existing interest types in BODS 0.4 have two core problems:
- Prescriptive definitions: Descriptions are tied to specific legal forms (e.g. voting rights defined as "rights of shareholders") that don't hold across all jurisdictions (UK companies limited by guarantee have voting members, not shareholders)
- Mixed categorisation: The codelist conflates roles (e.g. board chair) with mechanisms (e.g. asset enjoyment), making mapping from local disclosure requirements ambiguous
Three proposed approaches under discussion: exhaustive codelist (research all disclosure regimes); hierarchical taxonomy (Ownership / Control / Benefit / Other); binary classifications (decompose rights into conveyance + exercise mechanism questions).
See also: OO research note Describing Interests (https://www.openownership.org/en/publications/describing-interests-research-note/).
Feature: Republishing, Provenance and Transformation (#464)
Status: Research.
BODS was designed for original declarations, but aggregators (like the Open Ownership Register) republish and reconcile data from multiple jurisdictions. Current BODS structure cannot represent multiple-source provenance adequately.
Five user stories driving the feature: business analysts documenting data combination; NGOs demonstrating data provenance for trust; journalists verifying original sources; KYC architects distinguishing original vs republished datasets; end-users knowing whether data is confirmed, corroborated, or contradicted.
Main constraint: field-level provenance within BODS statements would make the standard "extremely unwieldy." The proposed solution combines schema changes with guidance — metadata-level provenance rather than field-level. Depends on related features: change-over-time representation, and separation of core data and metadata within statements.
Feature: Representing Missing Information (#389)
Status: Research. Comments: 13 (active).
Covers 10 categories of missing or incomplete BO information: exempted entities; undisclosed shareholders known to be public companies; no beneficial owners meeting the threshold; inaccessible upstream information; uncooperative parties; unknown interest types; anonymous beneficial owners; non-filing companies.
Proposed typology distinguishes:
- Exemptions: Entity type or revenue threshold means disclosure not required
- Missing by design: Information not required to be collected
- Required but missing: Disclosure obligation exists but unfulfilled
- Withheld: Data collected but not published for legitimate reasons (protection, legal restriction)
Key modelling principle: separate that data is missing from why it is missing — these serve different analytical purposes. The GLEIF Level 2 Reporting Exceptions model is cited as a reference for how to handle this in practice.
See also: OO publication Building an Auditable Record (https://www.openownership.org/en/publications/building-an-auditable-record-of-beneficial-ownership/).
Other notable open issues (selected)
| Issue | Title | Status |
|---|---|---|
| #742 | Unspecified or unknown entity | feature: missing information |
| #744 | publicationDetails no longer required? | under discussion |
| #743 | Consolidate placeOfBirth into addresses | enhancement |
| #741 | Open OOC statement referencing closed entity | documentation |
| #733 | Review conceptual and data model | conceptual model |
| #731 | Reconsider statementId length constraints | bug |
| #753 | Primer improvements needed | documentation |
Global Energy Monitor: Global Energy Ownership Tracker
The Global Energy Ownership Tracker (GEOT) is a dataset maintained by Global Energy Monitor (GEM) tracking ownership of fossil fuel and heavy industry assets worldwide. As of the February 2026 release, it covers: coal plants, oil and gas plants, bioenergy plants, iron and steel plants, coal mines, iron ore mines, cement and concrete plants, and natural gas pipelines.
BODS alignment: The GEOT explicitly organises ownership data following the Beneficial Ownership Data Standard. The tracker follows the SEC's 5% beneficial ownership reporting threshold (Schedule 13D) — by capturing ≥5% ownership stakes, it provides a near-comprehensive view of controlling and significant minority interests, not just majority owners. The schema differentiates privately owned and publicly traded companies in line with BODS entityType, partly because US-listed companies are required to publish audited financials and BO information above 5%.
OpenSanctions dataset: The GEOT data is published on OpenSanctions (https://www.opensanctions.org/datasets/gem_energy_ownership/) in FollowTheMoney format, enabling cross-dataset analysis with sanctions lists, PEPs data, and procurement data.
Why it matters for energy transition and climate accountability:
- Hidden climate liabilities: GEM's report World's Largest Oil and Gas Plant Owners Hide Billions of Dollars in Climate Costs (https://globalenergymonitor.org/report/worlds-largest-oil-and-gas-plant-owners-hide-billions-of-dollars-in-climate-costs/) demonstrates how opaque ownership structures allow major fossil fuel operators to obscure their true climate exposure from investors and regulators.
- Nominee structures: The Fossil Fuel Middlemen (https://globalenergymonitor.org/report/the-fossil-fuel-middlemen-how-nominee-structures-obscure-australian-investments-in-coal-oil-and-gas/) shows how nominee arrangements in Australia obscure beneficial ownership of coal, oil, and gas investments.
- Pension fund exposure: Danwatch's investigation (https://danwatch.dk/en/hidden-co2-emissions-your-pension-money-is-polluting-the-planet-more-than-you-are-told/) used GEOT data to show how pension funds are exposed to hidden CO2 emissions through complex ownership chains.
- Investment treaty risk: E3G analysis (https://www.e3g.org/publications/investment-treaties-are-undermining-the-global-energy-transition/) shows how opaque ownership undermines accountability in energy transition investment treaties.
- Policy brief: OpenOwnership's Shining a Light on Company Ownership (https://www.openownership.org/en/publications/shining-a-light-on-company-ownership-the-role-of-beneficial-ownership-transparency-in-the-energy-transition/) links BO transparency directly to energy transition governance.
Stephen's analysis: https://www.linkedin.com/posts/stephenabbottpugh_energy-heavyindustry-opendata-activity-7435326197955260416--6uB/
Beneficial Ownership in Fisheries Governance
Fisheries is one of the clearest sectoral use cases for BO transparency: opaque vessel and company ownership is a primary enabler of illegal, unreported and unregulated (IUU) fishing, which accounts for more than 1 in 5 fish taken globally and costs the global economy billions annually. The commercial fishing industry generates ~$141 billion/year; determining who benefits is often impossible through official records alone.
Why UBO matters in fisheries
Beneficial owners of fishing vessels and quota holders routinely hide behind flags of convenience, shell companies, and nominee directors. Without UBO transparency:
- Licensing authorities cannot verify who actually controls a vessel or quota
- Sanctions and debarment are evaded by restructuring ownership
- Repeat IUU offenders reappear under new company names
- Subsidies flow to unscrupulous operators who remain unidentifiable
Transparency of UBO information — combined with vessel monitoring systems (VMS) and automatic identification systems (AIS) — enables authorities to: identify hidden links across fleets and flags; build enforcement cases that follow the money to beneficial owners; and detect beneficial owner connections between licensed and unlicensed vessels.
Global Fishing Watch
Global Fishing Watch is the leading organisation advancing UBO transparency in fisheries globally. Their Vessel Viewer platform integrates ownership history with vessel tracking data. Key resources:
- UBO overview: https://globalfishingwatch.org/ultimate-beneficial-ownership-ubo/
- Fact sheet: https://globalfishingwatch.org/fact-sheet/ultimate-beneficial-ownership-why-transparency-is-vital-for-effective-fisheries-governance/
- Vision document (PDF): https://globalfishingwatch.org/wp-content/uploads/Global_Fishing_Watch-A-Vision-for-Ultimate-Beneficial-Ownership-in-Fisheries_ENG.pdf
GFW actively supports the integration of UBO data into national fisheries management systems and advocated at the FAO COFI meeting for vessel ownership transparency standards. In December 2024, the UN General Assembly adopted a resolution on sustainable fisheries that includes UBO transparency provisions — a milestone GFW helped advance.
Standards and frameworks
-
FiTI Standard 2.0 (launched February 2026): The Fisheries Transparency Initiative's first major update since 2017. Beneficial ownership now has a central place alongside small-scale fisheries and development finance. The standard requires fishing licence holders and vessel owners to disclose their beneficial owners; countries are under increasing pressure to identify UBOs across the full fishing supply chain including transshipment and transport vessels.
-
Coalition for Fisheries Transparency Global Charter 2024 (https://fisheriestransparency.net/wp-content/uploads/2024/10/Coalition-for-Fisheries-Transparency-Global-Charter-2024-EN.pdf): Multi-stakeholder framework committing signatories to advance UBO disclosure as part of broader fisheries transparency.
-
Oceans 5 has funded work on developing a standard specifically for UBO reporting in the fisheries sector: https://www.oceans5.org/project/standard-for-ultimate-beneficial-ownership-reporting/
Research and investigations
- C4ADS — Anchors Away (https://c4ads.org/commentary/anchors-away/): Analysis of how shell company structures shield fishing vessel owners from accountability.
- C4ADS — Sea Shells (https://c4ads.org/issue-briefs/sea-shells/): Deep-dive investigation into beneficial ownership in the fishing industry using open data.
- Pew Charitable Trusts (https://www.pew.org/-/media/assets/2023/10/ownership-of-fishing-companies-vessels-need-greater-transparency-and-accountability.pdf): 2023 report on the need for greater transparency and accountability in fishing company and vessel ownership.
OpenOwnership publications on fisheries
-
Using Beneficial Ownership Information in Fisheries Governance (https://www.openownership.org/en/publications/using-beneficial-ownership-information-in-fisheries-governance/): Policy brief on how existing BO transparency infrastructure can be leveraged for fisheries governance; includes use cases (licensing, corruption detection, policy monitoring) and recommended actions for governments, RFMOs, industry, and civil society.
-
Charting New Waters (https://www.openownership.org/en/publications/charting-new-waters/): Joint UNODC/OpenOwnership report. Identifies structural challenges (quota trading, jurisdictional patchwork, industry fragmentation) and provides actionable recommendations. Key finding: systematic use of BO information could significantly improve fisheries governance through better licensing, corruption detection, and policy oversight.
BODS in Practice: Case Studies and Real-World Implementations
The beneficialownership.co.uk/case-studies page curates the principal real-world deployments of BODS. These cases span national registers, EITI extractives reporting, energy ownership tracking, commercial compliance tools, and register-technology products. Together they demonstrate the breadth of contexts in which BODS has been adopted as the common interchange format for beneficial ownership data.
National Register Publications
Latvia — first national BODS publication (2021): Latvia's Enterprise Register became the first national register to publish BODS-compliant data, establishing the template for how central registers can expose BO data in a machine-readable, interoperable format. The Latvia case study is the canonical proof-of-concept that a production national register can serialise to BODS. Case study: https://www.openownership.org/en/publications/latvia-beneficial-ownership-data-standard-case-study/
Armenia — BODS beneficial ownership declarations: Armenia implemented BODS for its BO declaration system, covering the lifecycle from collection to publication. The implementation shows how BODS structures person statements (declarants), entity statements (companies), and ownership-or-control statements (the links between them) in a live national context. Case study: https://www.openownership.org/en/publications/armenia-beneficial-ownership-data-standard-case-study/
Botswana CIPA — data collection and visualisation: The Companies and Intellectual Property Authority of Botswana adopted BODS for structured data collection from registrants and linked it to a dedicated visualisation library. The Botswana case is notable for covering the full pipeline: form → structured BODS data → network visualisation. Case study: https://www.openownership.org/en/publications/botswana-beneficial-ownership-data-standard-case-study/
Nigeria CAC — first African BODS implementation: The Corporate Affairs Commission of Nigeria was the first African registry to implement BODS, demonstrating applicability in a large, complex jurisdiction with high volumes of entity registrations. Case study: https://www.openownership.org/en/publications/nigeria-beneficial-ownership-data-standard-case-study/
Indonesia — BODS 0.4 mapping: Indonesia's BO register data has been mapped to BODS 0.4, providing a worked example of how a jurisdiction with a complex national data model can be normalised to the standard. See also the Indonesia country data profile in the OpenOwnership data repository.
Slovakia RPVS — BODS data explorer: Slovakia's Register Partnerov Verejného Sektora (partners of the public sector) has been mapped to BODS and published with an accompanying data explorer, making it one of the best-documented examples of a procurement-linked BO register publishing to BODS. Case study: https://www.beneficialownership.co.uk/case-studies
Sector-Specific Implementations
EITI SOE database — BODS mapping notebook: The Extractive Industries Transparency Initiative's state-owned enterprise (SOE) database has been mapped to BODS in a published Jupyter notebook. This is the reference implementation for how EITI data (produced under Requirement 2.5 of the 2023 EITI Standard) can be represented as BODS statements, enabling cross-dataset analysis with national register data. Notebook: see EITI SOE database entry in the Extractives section above.
Global Energy Ownership Tracker (GEOT): The Global Energy Monitor's tracker covers ~50,000 fossil fuel and power assets and their owners. GEOT is published as a BODS-aligned dataset and simultaneously on OpenSanctions in FollowTheMoney format — making it one of the largest real-world applications of BODS for energy sector ownership transparency. The 5% ownership threshold mirrors SEC reporting requirements. Full detail in the Global Energy Monitor section above.
Canada BOP2P — pan-Canadian BO repository: The Beneficial Ownership Policy to Practice (BOP2P) programme, delivered through MRAS, uses BODS as the common data format for a federated repository aggregating BO data across federal, provincial, and territorial jurisdictions. Canada is therefore the largest-scale deployment of BODS for cross-jurisdictional data aggregation. Full detail in the Canada section above.
Commercial and Technology Implementations
Structuriser: A compliance SaaS platform that uses BODS as its internal data model for representing corporate structure and beneficial ownership information, enabling portability and interoperability of corporate ownership data across compliance workflows. https://structuriser.com/
Foster Moore Verne®: A register technology product built on BODS as its native data model. Verne demonstrates that register vendors are beginning to embed BODS natively rather than treating it as an export format, which has significant implications for data quality and interoperability at point of collection. https://www.fostermoore.com/verne
NRD Companies BOREG©: A beneficial ownership register product (developed by NRD Companies) that outputs BODS-compliant data. Another example of commercial register technology adopting BODS natively as output format. https://www.nrdcompanies.com/
What these cases demonstrate collectively
Across these twelve implementations, BODS has been used in five distinct roles:
- National register publication format — serialising existing register data into a standard interchange format (Latvia, Armenia, Nigeria, Indonesia, Slovakia)
- Data collection schema — structuring the forms and back-end database that captures declarations from registrants (Botswana, Armenia)
- Cross-jurisdictional aggregation layer — federating BO data from multiple jurisdictions into a single repository (Canada BOP2P)
- Sector-specific dataset format — applying BODS outside company registers, to extractives (EITI SOE), energy (GEOT), and procurement (Slovakia RPVS) data
- Native data model in register/compliance products — commercial products building BODS in from the start rather than as an afterthought (Structuriser, Foster Moore Verne, NRD BOREG)
The progression from "export format" to "native data model" in commercial products (roles 1→5) is a significant signal of BODS maturity.
ICIJ: Investigative Journalism and Leaked Beneficial Ownership Data
The International Consortium of Investigative Journalists (ICIJ — https://www.icij.org/) is the world's leading cross-border investigative journalism network. Its landmark investigations — most notably the Panama Papers — have been the single most influential force in driving global political momentum for beneficial ownership transparency. ICIJ's work makes the harms of opaque company ownership concrete and legible to policymakers, civil society, and the public in a way that policy reports alone rarely achieve.
ICIJ Investigations
Panama Papers (2016) (https://www.icij.org/investigations/panama-papers/): The largest data leak in history at the time of publication — 11.5 million documents from the Panamanian law firm Mossack Fonseca, revealing how offshore shell companies were used by politicians, business leaders, criminals, and celebrities to hide wealth, evade tax, and launder money. The investigation was published simultaneously by more than 100 media partners in 76 countries and is widely credited with accelerating the global move towards mandatory BO registers. Within months of publication, the UK expanded PSC registration requirements; the EU fast-tracked AMLD4; and the OECD and FATF both cited the Papers in pushing for stronger standards.
Pandora Papers (2021) (https://www.icij.org/investigations/pandora-papers/): A follow-up of similar scale — 11.9 million records from 14 financial service providers across the world. Revealed how the offshore system continued to operate despite post-Panama Papers reforms, with a particular focus on trusts (a significant gap in most BO register frameworks at the time) and real estate. Directly informed policy debates about BO requirements for trusts under AMLD5/AMLD6 and FATF Recommendation 25.
FinCEN Files (2020) (https://www.icij.org/investigations/fincen-files/): Based on leaked Suspicious Activity Reports (SARs) from the US Financial Crimes Enforcement Network. Showed that major global banks moved more than $2 trillion in transactions flagged by their own compliance staff as potentially suspicious — often through shell companies with opaque beneficial owners. Reinforced the case that BO transparency is necessary but not sufficient: BO data must be usable by financial institutions and law enforcement to be effective.
Other major ICIJ investigations relevant to BO include the Luanda Leaks (Angola sovereign wealth), the Luxembourg Leaks (EU tax avoidance), Swiss Leaks (HSBC/Falciani data), and the Malta Files. The full investigations index is at https://www.icij.org/investigations/.
Offshore Leaks Database
ICIJ publishes a structured, searchable database of entities, officers, and relationships from its major data leaks at https://offshoreleaks.icij.org/. The database covers entities from the Panama Papers, Pandora Papers, Offshore Leaks (2013), Bahamas Leaks, and Paradise Papers. It is one of the largest publicly available sources of leaked beneficial ownership-relevant data and is widely used by journalists, researchers, and civil society to trace offshore ownership networks.
Key characteristics: The Offshore Leaks database is graph-structured (entities → relationships → officers/addresses), with node and edge data downloadable in bulk from https://offshoreleaks.icij.org/pages/database. It is one of Stephen's BODS mapping targets (see the bods-icij-offshoreleaks repository in Stephen's BODS Mapping Repositories section above). The data does not necessarily reflect current ownership — it captures a point-in-time snapshot from the leaked documents — but it is invaluable for historical investigation and network tracing.
Important caveat for BO practitioners: Presence in the Offshore Leaks database does not imply wrongdoing. Many offshore structures are legal, even if the context of their use is ethically questionable. This distinction is important when using the database as a reference source in BO-related analysis.
Key Beneficial Ownership Research Reports
These reports are the foundational reference literature for the field of BO transparency and anti-corruption. They are regularly cited in policy documents, standard-setting processes, and advocacy work.
World Bank: The Puppet Masters (2011)
Full title: The Puppet Masters: How the Corrupt Use Legal Structures to Hide Stolen Assets and What to Do About It URL: https://documents.worldbank.org/en/publication/documents-reports/documentdetail/784961468152973030
The Puppet Masters is the seminal empirical study of how corrupt actors use legal persons and arrangements to conceal and move stolen assets. Analysing 150 grand corruption cases, it found that corporate vehicles — particularly chains of shell companies across multiple jurisdictions — were the mechanism of choice in the vast majority of cases. The study was foundational for the development of FATF Recommendations 24 and 25 (the core international BO standards) and remains the most-cited empirical basis for why mandatory BO registers are necessary.
Key findings: in nearly all cases studied, the corrupt used multiple jurisdictions; nominee shareholders and directors were used systematically to obscure true owners; and company service providers (CSPs) played a central facilitation role. The recommendations prefigure the approach now embodied in FATF R24/R25 and the EU AML package.
World Bank: Signatures for Sale (2023)
Full title: Signatures for Sale: How Nominee Services for Shell Companies are Abused to Conceal Beneficial Owners URL: https://openknowledge.worldbank.org/entities/publication/32914fa8-e9d5-59cc-b599-105962e9b390
A more recent World Bank analysis focusing specifically on nominee directors and shareholders — the human layer used to obscure beneficial ownership behind ostensibly compliant company records. The study investigates how nominee service providers operate globally, how they are used to circumvent BO disclosure requirements, and what reforms to CSP regulation and BO register design can address the problem. Directly relevant to debates about the reliability of BO data collected through self-declaration.
Transparency International
Into the Light — Benchmarking BO Transparency Frameworks: MENA (https://www.transparency.org/en/publications/into-the-light-benchmarking-beneficial-ownership-transparency-frameworks-mena): Assesses the state of BO transparency in Middle East and North Africa countries, benchmarked against FATF standards and good practice. Useful reference for MENA register design work.
Chasing Grand Corruption (https://www.transparency.org/en/publications/chasing-grand-corruption): TI's investigation into how grand corruption networks — typically involving senior politicians and state officials — use offshore structures. Covers how BO opacity enables impunity and what investigative and enforcement tools can help.
Legitimate Interest: Measures for Public Interest Stakeholders (https://www.transparency.org/en/publications/legitimate-interest-measures-for-public-interest-stakeholders): A key policy paper on the "legitimate interest" access regime — the mechanism under EU AML law (post-Sovim judgment) by which journalists, civil society, and researchers can access non-public BO register data. Directly relevant to the ongoing EU debate about who can access BO data and under what conditions.
Opacity in Real Estate Ownership Index 2025 (https://www.transparency.org/en/publications/opacity-in-real-estate-ownership-index-2025): A 2025 ranking of jurisdictions by the opacity of their real estate ownership regimes. Real estate is one of the most significant channels for BO-obscured money laundering; this index provides comparative data for policy and advocacy work.
Transparency International UK
TI-UK has produced a series of reports on BO transparency with particular focus on UK Overseas Territories, Crown Dependencies, and the UK's own register quality. These are especially relevant given Stephen's work on UK and Crown Dependency BO regimes.
- Opening Offshore Secrecy (https://www.transparency.org.uk/publications/opening-offshore-secrecy): The case for public BO registers in Overseas Territories and Crown Dependencies — foundational advocacy document.
- Improving the UK's Trust Registration Service (https://www.transparency.org.uk/publications/improving-uks-trust-registration-service): Analysis of the UK's TRS (the register for express trusts), its current gaps, and recommended improvements. Highly relevant to FATF R25 implementation.
- Unlocking Ownership Data (https://www.transparency.org.uk/publications/unlocking-ownership-data): Broader analysis of how BO data quality and accessibility can be improved across UK registers.
- Legitimate Interest access — Anguilla (https://www.transparency.org.uk/publications/providing-legitimate-interest-access-anguillas-beneficial-ownership-data): Practical guidance on implementing legitimate interest access frameworks in Anguilla's BO register context.
- Legitimate Interest access — British Virgin Islands (https://www.transparency.org.uk/publications/providing-legitimate-interest-access-british-virgin-islands-beneficial-ownership-data): Same for the BVI — one of the largest offshore jurisdictions by entity count.
- Legitimate Interest access — Bermuda (https://www.transparency.org.uk/publications/providing-legitimate-interest-access-bermudas-beneficial-ownership-data): Same for Bermuda.
- Legitimate Interest access — Cayman Islands (https://www.transparency.org.uk/publications/providing-legitimate-interest-access-cayman-islands-beneficial-ownership-data): Same for Cayman — the world's largest offshore financial centre by assets under management.
The legitimate interest series is particularly important in light of the CJEU's Sovim judgment (November 2022), which ruled that unrestricted public access to BO register data under AMLD5 violated GDPR. The EU's response — a legitimate interest access regime under AMLR 2024/1624 — is still being implemented; TI-UK's country-specific guidance is among the most practically useful available.
GODIN: Global Open Data Integration Network
The Global Open Data Integration Network (GODIN — https://godin.gleif.org/) is a collaborative initiative to enhance global data interoperability by connecting organisations that publish open data or create open data standards, aligning their data to common global frameworks — principally the Global Legal Entity Identifier (LEI) system managed by GLEIF.
Stephen Abbott Pugh is a co-organiser of GODIN, which reflects the network's position at the intersection of his work on BODS, GLEIF/LEI integration, and the broader open data ecosystem.
What GODIN does
GODIN's core mission is to make open datasets more interoperable by: establishing shared entity identifiers (primarily the LEI, but also other open identifiers like Wikidata Q-IDs); creating mappings between member datasets; and publishing alignment data that enables cross-dataset analysis. The practical goal is a "Transparency Fabric" — a linked layer of open data connecting entities across registers, databases, and datasets using common identifiers.
The GODIN Transparency Fabric (https://transparencyfabric.gleif.org/) is the primary output: a growing set of mappings between GLEIF's LEI data and other open datasets from member organisations, enabling queries like "which entities in the OpenSanctions database have an LEI?" or "which BODS-published entities can be matched to a GEOT energy asset?"
GODIN member organisations
| Organisation | Role in GODIN |
|---|---|
| GLEIF (https://www.gleif.org/en) | Host organisation; LEI system is the anchor identifier |
| OpenOwnership (https://www.openownership.org/en/) | BO data standard (BODS) and register data |
| Global Energy Monitor / GEOT (https://globalenergymonitor.org/projects/global-energy-ownership-tracker/) | Energy ownership dataset |
| AC/DC — African Climate & Development Data Collective (https://acdatacollective.org/) | African open data |
| Media Registry (https://www.mediaregistry.org/) | Media ownership transparency data |
| Open Data Services Co-op (https://opendataservices.coop/) | Technical implementation, standards tooling |
| OpenSanctions (https://www.opensanctions.org/) | Sanctions, PEPs, and FollowTheMoney data |
| Data Research Center (https://dataresearchcenter.org/) | Open data research and analysis |
Wikidata (https://www.wikidata.org/) is a GODIN supporter — its Q-identifiers are used as a secondary entity linkage mechanism alongside the LEI, particularly for entities that don't have or require an LEI (individuals, governments, some NGOs).
GODIN GitHub repositories
The GODIN GitHub organisation (https://github.com/orgs/Global-Open-Data-Integration-Network/repositories) hosts the technical outputs: alignment datasets, mapping scripts, and Transparency Fabric tooling. This is where the practical data integration work is published in machine-readable form.
GODIN in context of BO data work
GODIN is directly relevant to BODS and BO data interoperability in several ways:
- LEI as entity identifier in BODS: GLEIF's LEI is one of the identifier schemes supported in BODS entity statements. GODIN's alignment work makes it easier to match BODS-published entities with GLEIF Level 1 and Level 2 data.
- Cross-dataset entity resolution: When working across OpenSanctions (FollowTheMoney), GEOT (BODS-aligned), and GLEIF (LEI-CDF/RR-CDF), GODIN's mappings provide the linkage layer.
- Media ownership: The Media Registry's participation brings media ownership into the same interoperability framework — a growing area where BO transparency tools are being applied.
- OpenSanctions integration: OpenSanctions' membership means GODIN alignment data feeds into the world's most widely used open sanctions and PEPs dataset.
Private Sector and Register APIs: How UBO/PSC Data Is Structured and Published
This section documents the principal APIs and data schemas used by commercial data providers and national registers to expose beneficial ownership and persons with significant control (PSC) data. These are the sources that practitioners integrate when building BO data pipelines, compliance tools, or register-to-BODS mappings.
Kyckr
Kyckr (https://developer.kyckr.com/api/company-v2/#/) is a corporate data aggregator providing structured company and UBO data from multiple jurisdictions via a single API. It is one of the principal commercial intermediaries between national registers and compliance workflows, and is a primary target for Stephen's BODS mapping work.
UBO schemas in the Kyckr v2 API: Kyckr distinguishes three types of UBO entities:
- CorporationUBO (https://developer.kyckr.com/api/company-v2/#/schemas/CorporationUBO): Represents a corporate entity that is itself a beneficial owner — i.e., a legal person that holds an interest. Fields include the entity's name, registration number, jurisdiction, and the nature/percentage of its holding.
- IndividualUBO (https://developer.kyckr.com/api/company-v2/#/schemas/IndividualUBO): Represents a natural person who is the ultimate beneficial owner. Fields include name, date of birth, nationality, country of residence, and the nature and percentage of their interest. This is the most common UBO type.
- OtherUBO (https://developer.kyckr.com/api/company-v2/#/schemas/OtherUBO): Covers cases where the UBO is neither a standard corporation nor an identifiable individual — e.g., a government entity, a trust, or a case where ownership is unverifiable. Used for edge cases and "unknown UBO" representations.
This three-way split maps naturally onto BODS concepts: CorporationUBO → entityStatement + ownershipOrControlStatement; IndividualUBO → personStatement + ownershipOrControlStatement; OtherUBO → entityStatement with an unknown/other entity type + ownershipOrControlStatement with appropriate missingInfoReason or unspecifiedReason fields.
Stephen's BODS mapping: https://github.com/StephenAbbott/bods-kyckr — a working implementation of the Kyckr → BODS transformation. See also the Kyckr section in the "Corporate Ownership Data Sources: Background Reference" section above for broader context on Kyckr as a data source.
Kausate
Kausate (https://docs.kausate.com/api-reference/company-data/extractUBOs) provides a dedicated extractUBOs endpoint as part of its corporate data API. The endpoint takes a company identifier and returns a structured representation of the company's UBO chain, including the ultimate natural persons at the end of the ownership chain and intermediate holding entities. Kausate's data model follows the pattern of layered entity resolution — traversing the ownership tree until natural persons are reached — which aligns with the BODS concept of chained ownershipOrControlStatements. Useful reference for understanding how commercial providers handle multi-hop ownership resolution vs. how BODS represents the same information.
Netherlands KvK UBO Register API
The Dutch Chamber of Commerce (Kamer van Koophandel, KvK) operates the Netherlands UBO register as part of the Handelsregister (Companies Register). The register came into force on 27 September 2020 pursuant to AMLD4/AMLD5 implementation. UBO data is available via the KVK Dataservice in XML format, or as a certified PDF via KVK Online.
Key data product: KVK uittreksel UBO-register
The product is queried by KVK-nummer (8-digit company identifier) or RSIN (legal entity number). The response includes:
- Maatschappelijke Activiteit / Onderneming: company name, KVK-nummer, RSIN, legal form
- UBO records (one or more per company), each containing:
- Formele registratie:
registratietijdstip(timestamp of registration in the register) - Materiële registratie:
datumAanvang(start date of the interest),datumEinde(end date, if applicable) - Belang (interest):
aard(nature of the interest — e.g., "Houder van feitelijke zeggenschap" / holder of actual control, or "Houder van economisch belang" / holder of economic interest) andomvang(extent/percentage band — e.g., ">25% and ≤50%") - Is Afgeschermd (is shielded): boolean indicating whether the UBO's personal data is restricted due to a protection order
- Natuurlijk Persoon (natural person): name, date and place and country of birth, address (restricted), land (country of residence), BSN or TIN + issuing country (restricted), nationality
- Formele registratie:
Access tiers: Some fields (marked with * in the data model) — including date/place of birth, address, BSN/TIN — are non-public and only available to authorised organisations under Article 51b of the Handelsregisterbesluit (financial institutions, competent authorities). Public data includes name, nature of interest, and extent of interest.
UBO obligation scope: Registration is required for non-listed BVs and NVs, foundations (stichtingen), associations (verenigingen), mutual guarantee societies, cooperatives, partnerships (maatschappen, VOF, CV), shipping companies, church organisations, and European company forms (SE, SCE, EESV) with their statutory seat in the Netherlands. Foreign branch offices (Ltd, GmbH with Dutch branches) are exempt — their UBOs must be registered in the country of incorporation.
Error/warning codes of note for data pipeline work: IPD0015 (entity not subject to UBO obligation), IPD0016 (UBO-obligated entity but no UBOs yet registered), IPD5101 (UBO data under investigation — a financial institution has queried the accuracy of the registered UBO(s) and triggered a review).
BODS mapping notes: The aard (nature) field maps to BODS interests[].type; omvang (extent percentage band) maps to interests[].share.minimum/maximum; Is Afgeschermd maps to BODS interests[].unspecifiedReason or person-level redaction flags. The tiered access model (public vs. restricted fields) is directly relevant to BODS discussions about what data to include in public vs. restricted BODS publications.
Sweden Bolagsverket API
Bolagsverket is the Swedish Companies Registration Office. It provides APIs and open data for company information including beneficial ownership data registered under Sweden's implementation of AMLD5. The FAQ/overview of their API offering is at https://bolagsverket.se/apierochoppnadata/fragorochsvaromapierna.4611.html. Sweden's BO register, like the Netherlands', is a natural candidate for BODS mapping given its structured data model and public accessibility.
Signicat UBO Lookup
Signicat (https://developer.signicat.com/docs/mint/steps/reference/data-verification/organisation-ubo-lookup/) provides a UBO lookup step within its Mint identity orchestration platform. The endpoint takes an organisation identifier and returns UBO data sourced from national registers, formatted for use in Know Your Business (KYB) and Know Your Customer (KYC) compliance workflows. Signicat's approach illustrates how BO data from registers is consumed in real-time identity verification contexts — a different use pattern from batch data pipelines. The data model exposed by Signicat reflects what is practically available from source registers, making it a useful reference for understanding cross-jurisdictional BO data field availability.
UK Companies House: Persons with Significant Control (PSC) API
The UK's PSC regime is the most mature and technically well-documented BO register API in the world, and is the reference implementation for many BODS mapping discussions. The full API reference for PSC data is at https://developer-specs.company-information.service.gov.uk/companies-house-public-data-api/reference/persons-with-significant-control.
The PSC API exposes individual PSCs, corporate PSCs ("relevant legal entities", RLEs), other registrable persons, and "super secure PSCs" (where personal data is protected by a court order). Key fields include: name, date_of_birth (month and year only, publicly), nationality, country_of_residence, natures_of_control (a codelist of PSC control categories — percentage thresholds, voting rights, appointment rights, significant influence), and notified_on/ceased_on dates.
The natures_of_control codelist is one of the most detailed standardised BO control-type taxonomies available and is directly relevant to BODS interests[].type mapping. The UK PSC data is Stephen's canonical reference for BODS personStatement and ownershipOrControlStatement field design, and the UK is one of the few jurisdictions where BODS has an official government endorsement (see Policy & Regulation section above).
Beneficial Ownership Data Verification
Verification is a critical and often underestimated element of beneficial ownership reform. Collecting and publishing BO data is only valuable if that data can be trusted to reflect reality. This section covers the concepts, practical steps, BODS technical mechanisms, international standards, and country examples relevant to designing and implementing BO data verification systems.
Primary OO references: principle page (https://www.openownership.org/en/principles/verification/), verification policy briefing (https://www.openownership.org/en/publications/verification-of-beneficial-ownership-data/), implementation checklist (https://www.openownership.org/en/news/designing-verification-systems-a-sample-implementation-checklist-for-beneficial-ownership-data/), and implementation guide data considerations (https://www.openownership.org/en/publications/guide-to-implementing-beneficial-ownership-transparency/data-considerations-for-beneficial-ownership-registers/).
What verification means
Verification is a combination of checks and processes that aim to ensure that beneficial ownership statements are accurate and complete at a given point in time. This is distinct from authentication (confirming who is submitting) and from investigation (determining whether a declared structure reflects economic reality in a deeper sense). Verification addresses two failure modes: accidental error (data entered wrongly by mistake, e.g. typos, wrong field formats) and deliberate falsehood (data entered wrongly with intent to deceive).
Checks can be deployed at two stages:
- At the point of submission: format validation, cross-reference checks against other government databases, guided data entry to reduce errors
- After submission/publication: ongoing data quality monitoring, periodic rechecks, investigations triggered by suspicious or inconsistent data, third-party reporting obligations
A good verification system delivers data that is accurate (free from accidental error and falsehood), complete (free from omissions), and reliable — providing clarity about the provenance of the data and what checks have been applied, reducing risks of false data, and triggering appropriate alerts when data is incomplete, false, or suspicious.
The three-part verification framework
BO data comprises three interconnected categories of information. Verification approaches differ across each.
1. Verifying natural persons
Key fields: name (including alternatives), nationalities, date of birth, place of birth, identification numbers (national ID, passport, tax number), place of residence, tax residencies, other addresses, PEP status, details of PEP status, unknown person indicators.
Verification mechanisms include: checking ID numbers against national identity registers or tax authority databases (where legislation permits); validating that addresses exist and match other government records; structured name fields (first/middle/last rather than a single freetext field) to reduce ambiguity; cross-referencing with PEP and sanctions lists; and confirming that the identification number format is valid (check digit verification). Automatic checks are most effective here because the data is structured and reference databases exist.
2. Verifying entities
Key fields: entity type (registered company, legal arrangement, anonymous, unknown), reasons for anonymity/unknown status, name and alternatives, incorporation details, identification numbers (company number, LEI), foundation date, dissolution date, addresses.
Verification mechanisms include: checking that the company number and name correspond to the details held in the national business register; flagging dissolved companies; validating addresses against official address registers; and detecting mismatches between the declared entity type and the company register record. Critically, these checks become far easier to automate when the BO system and the company register use the same identifiers for entities — a strong argument for aligned identifier schemes (see BODS entity identifiers, GLEIF LEI).
3. Verifying ownership or control relationships
Key fields: subject of the relationship (entity being owned/controlled), whether ownership is direct or indirect, the interested party, type of interest (shareholding, voting rights, appointment rights, significant influence/control), interest level/percentage share, start date, end date.
Ownership or control structures are harder to check automatically than person or entity fields because there is no single reference database of "true" ownership. Some automatic checks are still possible: verifying that a start date is not in the future; that an end date follows the start date; that all required fields are populated; that the entity ID used in the relationship statement is valid and matches a known entity. Beyond these, verification typically requires manual cross-referencing against other records, notarial documentation, or intelligence from financial institutions.
Verification stages and workflow
A worked verification workflow proceeds as follows:
- Pre-submission guidance: Well-designed data collection forms with field-level guidance reduce error at source. Structured fields (separate first/middle/last name; date picker rather than freetext date; validated ID number format) prevent the most common accidental errors before the data enters the system.
- Automatic checks at submission: On receipt of a submission, the system runs: format validation; database cross-checks (company register, identity register, address register, PEP/sanctions lists); business rule checks (no impossible dates, no already-dissolved company as subject, no self-referential ownership). Submissions failing checks are returned to the declarant with specific error messages.
- Human review queue: Submissions flagging potential issues — but not definitively invalid — enter a review queue for manual assessment by register staff. Staff may request additional supporting documentation: certified company formation documents, shareholder agreements, certified translation of foreign documents.
- Post-publication monitoring: Published data is periodically rechecked against updated reference databases. Changes in the company register (dissolution, change of directors) trigger alerts for corresponding BO records. Financial institutions and other obliged entities subject to Know Your Customer/Know Your Business requirements have an obligation to consult the BO register and report discrepancies they find to the register authority.
- Ongoing update obligations: Declarants are required to update BO information within a specified timeframe (typically 14–30 days) when it changes. Failure to update is itself a compliance failure subject to sanctions.
Sanctions and enforcement
Verification is only effective if non-compliance has consequences. An effective sanctions regime should:
- Cover all forms of non-compliance: non-submission, late submission, incomplete submission, and false submission
- Apply to all relevant parties: the person making the declaration, the beneficial owner themselves, registered officers of the company, and the declaring company
- Include both monetary penalties (fines) and non-monetary penalties (striking off, disqualification from public procurement, licence revocation) — the latter are often more powerful deterrents
- Empower relevant agencies (register authority, financial intelligence unit, tax authority, sector regulators) to enforce
- Align sanctions with policy goals: if BO transparency is mandated for public procurement, non-compliance should trigger procurement exclusion; if mandated for extractives licensing, non-compliance should be grounds for licence refusal or termination
- Make data on non-compliance publicly available to enable civil society and media scrutiny
The Kyrgyz Republic's 2018 subsoil use regulation is an example of sector-aligned sanctions: false or missing BO data is explicitly grounds for licence termination under Article 21.9.
BODS technical mechanisms for verification
BODS 0.4 provides a source object on all three statement types. The source.type field supports "selfDeclaration" (the declarant provided the information themselves) and "verified" (the information has been subject to verification by the publishing authority). When source.type is "verified", the source object can additionally record:
description: a narrative description of how verification was carried outurl: a link to the verification methodology or evidenceretrievedAt: when the verification was performedassertedBy: the person or organisation that carried out the verification
This mechanism allows BODS publishers to mark an entire statement — a person, an entity, or an ownership/control relationship — as verified, and to record the provenance of that verification. It is the primary technical mechanism by which data trust can be encoded in a BODS dataset.
Future direction: As of the 2022 OO analysis, there was active consideration of extending verification to the field level — i.e., marking individual attributes within a statement as verified (e.g., "this person's ID number has been verified against the national identity register") rather than only marking the whole statement. This was being tracked as a BODS feature development issue on GitHub. See BODS open issues section above for the feature tracker.
FATF standards on verification
FATF Recommendation 24 — Legal Persons: Section 7 of FATF's Guidance on Beneficial Ownership of Legal Persons (https://www.fatf-gafi.org/en/publications/Fatfrecommendations/Guidance-Beneficial-Ownership-Legal-Persons.html) addresses "Accurate information – means of verification of beneficial ownership information." It sets out the range of mechanisms countries may use to verify BO information held in central registers, covering: self-declaration with criminal liability for false statements; cross-checking against other government databases (company register, tax authority, financial supervisors); obliged entity reporting requirements; and risk-based enhanced verification for higher-risk companies. FATF distinguishes between information that can be verified automatically and information requiring more resource-intensive checks, and expects countries to adopt a layered approach.
FATF Recommendation 25 — Legal Arrangements: Section 4 of the Guidance on Beneficial Ownership and Transparency of Legal Arrangements (https://www.fatf-gafi.org/en/publications/Fatfrecommendations/Guidance-Beneficial-Ownership-Transparency-Legal-Arrangements.html) covers "Adequate, accurate and up-to-date information" for trusts and similar arrangements. The verification challenge for legal arrangements is structurally different from companies: there is no universal register of trusts in most jurisdictions, and the trustee (rather than a central authority) is typically the primary record-keeper. FATF R25 therefore focuses on: obligations on trustees to maintain accurate records; obligations on professional trustees and trust service providers to verify beneficiary information; and the role of tax authorities (via automatic exchange of information) in identifying trust-held assets.
Country examples: Latvia and Denmark
Latvia undertook a five-year reform process to update its BO legislation, sanctions regime, and data publication framework. Latvia now publishes open BODS-compliant data from its Enterprise Register. The verification system includes:
- In-depth checks at registration: assessment of risks associated with the country of residence of the declared beneficial owner; examination of the UBO's involvement in other legal persons; review of publicly available information on the beneficial owner's reputation
- Request for additional documentation when checks raise doubts: certified evidence of the basis for control claimed; certified identity documentation; evidence that it is genuinely impossible to determine the beneficial owner; documents proving the full ownership structure
- FIU referral: where potential risks are identified during registration, the Enterprise Register disseminates a report to the Financial Intelligence Unit
Denmark's Central Business Register (CVR) uses a combination of automatic and manual verification with some machine learning:
- Automatic checks: the civil registration number (CPR number) is unique and validated automatically; addresses are checked against the Danish Address Register; business rules prevent logically impossible situations (e.g., registering a deceased person as a UBO; declaring a company that has been dissolved)
- Prefilling from authoritative sources: key entity details are prefilled by pulling data from the company register based on the company registration number, reducing data entry errors
- Machine learning: used to identify patterns associated with potential risk or data quality issues in submitted BO information
- Random audits: in 2019, the Danish Business Authority randomly selected 500 companies with recorded BO information to verify their submissions
- Dissolution power: the Danish Business Authority has a legal basis to dissolve companies where BO information is missing or inadequate — a powerful non-monetary sanction
- Third-party reporting: external parties (financial institutions, lawyers, accountants) are legally obliged to report BO discrepancies they identify
Additional reference resources
- OECD Effective Beneficial Ownership Frameworks Toolkit (2nd edition, 2024) (https://www.oecd.org/content/dam/oecd/en/networks/global-forum-tax-transparency/effective-beneficial-ownership-frameworks-toolkit-second-edition-2024.pdf): Comprehensive toolkit from the OECD Global Forum on Tax Transparency, including detailed guidance on verification mechanisms as part of building effective BO frameworks. The 2nd edition updates the original 2023 toolkit with new country examples and implementation guidance.
- OECD BO Toolkit (original) (https://www.oecd.org/content/dam/oecd/en/networks/global-forum-tax-transparency/beneficial-ownership-toolkit.pdf): The foundation document; covers the full BO framework design including data collection, verification, access, and international cooperation.
- Tax Justice Network: Beneficial Ownership Verification (https://taxjustice.net/reports/beneficial-ownership-verification-ensuring-the-truthfulness-and-accuracy-of-registered-ownership-information/): TJN's analysis of what makes BO verification effective, focusing on the truthfulness and accuracy of registered information. Provides a civil society perspective on gaps in current verification practices and recommendations for strengthening them.
- Moody's KYC: Brief Guide to UBO Verification Legislation (https://www.moodys.com/web/en/us/kyc/resources/insights/who-is-in-charge-here-brief-guide-to-ultimate-beneficial-owners-verification-legislation.html): A private sector/compliance perspective on UBO verification requirements as seen by financial institutions subject to KYC/KYB obligations. Useful for understanding how the compliance industry approaches verification and what data they require from registers.
Recent Register Developments (2026)
This section records significant developments in beneficial ownership registers and access regimes that occurred in 2026, providing a running reference for the fast-moving reform landscape.
BVI: Legitimate Interest Access Live (1 April 2026)
The British Virgin Islands activated legitimate interest access to its beneficial ownership register on 1 April 2026, making it one of the first UK Overseas Territories to go live with a functional access mechanism for journalists, civil society, and other public interest stakeholders following years of pressure from the UK Parliament and anti-corruption campaigners.
The access framework is governed by revised BO guidelines published in January 2026 (https://www.bvifsc.vg/sites/default/files/revised_bo_guidelines_final_version_for_publication_02.01.26_0.pdf) and implemented via the BVI Financial Services Commission's Industry Circular 11-2026 (https://www.bvifsc.vg/news/industry-updates/industry-circular-11-2026-launch-legitimate-interest-transactions-and-request). Requestors must demonstrate a legitimate interest and undergo an application process; access is not unrestricted public access. Official announcement: https://gov.vg/news/legitimate-interest-access-now-fully-operational-virgin-islands.
This is directly relevant to the TI-UK legitimate interest access series (see Key Beneficial Ownership Research Reports section), which includes a specific publication on providing legitimate interest access to BVI BO data.
Sri Lanka: BO Registry Module Live (30 March 2026)
Sri Lanka launched its Beneficial Ownership Registry Module on 30 March 2026, hosted by the Registrar of Companies (Department of the Registrar of Companies): https://bo.drc.gov.lk/login.
The legal basis is the Sri Lanka BO Regulations gazetted on 21 March 2026 under Gazette No. 2480/48, effective 30 March 2026. The regulations introduce a suite of seven BO forms (BO1–BO7), each tied to a specific corporate event:
| Form | Trigger | Filing deadline |
|---|---|---|
| BO1 | Incorporation | Filed together with Form 1 at incorporation |
| BO2 | Share issue (Form 6) | Within 20 working days of issue |
| BO3 | Share transfer | Within 20 working days of transfer |
| BO4 | Annual Return (Form 15) | Simultaneously with the annual return |
| BO5 | Appointment/change of authorised BO person | On appointment or change |
| BO6 | Location of BO records | Declares where physical BO records are held |
| BO7 | Core BO data form | Data capture for each individual beneficial owner |
The BO1–BO6 forms are event triggers; BO7 is the substantive data form that captures the beneficial owner's personal and interest details. This event-linked form architecture — where a separate form is filed for each corporate event that changes BO status — is a distinct approach compared to jurisdictions that use a single annual disclosure form. For analysis see: https://www.linkedin.com/pulse/sri-lankas-beneficial-ownership-registry-now-live-heres-medagoda-5sn2c/
Note: Sri Lanka's BO regulations are in Sinhalese (the Gazette is not translated into English). The form architecture described above is drawn from an English-language summary of the regulations.
Sweden: Legitimate Interest Access Approved (from 1 July 2026)
The Swedish Parliament (Riksdag) has approved legislation to introduce robust legitimate interest access to Sweden's beneficial ownership register, aligned with the requirements of the Sixth Anti-Money Laundering Directive (AMLD6). The changes apply from 1 July 2026. Parliamentary document: https://www.riksdagen.se/sv/dokument-och-lagar/dokument/betankande/utlamnande-av-uppgifter-ur-registret-over-verkliga_hd01fiu35/
Sweden's register is operated by Bolagsverket (see Private Sector and Register APIs section). This development brings Sweden's access regime into line with the AMLD6 requirement for a legitimate interest access mechanism following the CJEU's Sovim judgment, which struck down unrestricted public access.
Norway: 17th Jurisdiction to Join BORIS (April 2026)
Norway became the 17th jurisdiction to make its beneficial ownership information searchable via the EU's BORIS system in April 2026, notable because Norway is not an EU member state but participates as an EEA country. This brings the total connected jurisdictions to 17 out of 30 EU/EEA countries. The EU BORIS section above has been updated to reflect this.
Norway's BO register (Brønnøysundregistrene) already has a well-documented public API (see Country-Specific Registers table) — BORIS connectivity adds a cross-border search layer on top of the existing national data.
Ontario: BO Registry Committed by 2027
The Canadian province of Ontario committed in its 2026 budget to establish a beneficial ownership registry by 2027 as part of efforts to combat money laundering and fraud through enhanced corporate transparency. Budget reference: https://budget.ontario.ca/2026/chapter-1b-safety.html#section-9
This adds Ontario to the growing list of Canadian sub-national jurisdictions working toward BO disclosure, and represents a significant development given Ontario's size as Canada's largest provincial economy. At the federal level, Corporations Canada and BOP2P are already operational (see Canada section above).
Philippines: Public BO for Procurement Now Live
The Philippines now makes beneficial ownership information publicly available for companies involved in public procurement, following the New Government Procurement Act (Republic Act No. 12009, July 2024). This means that information on who ultimately owns and controls companies bidding for or holding government contracts is accessible publicly — a significant step beyond the initial BO disclosure requirement, which mandated collection but not necessarily public access. LinkedIn post: http://linkedin.com/feed/update/urn:li:activity:7442395219033219072
This builds on the Philippines' existing BO framework via PhilGEPS and is covered in more detail in the Beneficial Ownership in Public Procurement section above.
St Helena: Public BO Register via Proton Drive
The St Helena beneficial ownership register — for this UK Overseas Territory in the South Atlantic — is published as a publicly accessible Proton Drive folder: https://drive.proton.me/urls/WEC6VHS4DW#GmckfehJ8yk2. This is a notable example of a minimalist, low-cost approach to public BO disclosure: rather than a formal register portal or API, the territory makes its BO data available directly via a shared cloud storage link.
St Helena is a small jurisdiction (population ~4,500) with a correspondingly small number of registered companies, making a document-store approach more feasible than it would be for larger territories. It nonetheless represents a pragmatic implementation of the principle of public access to BO information, and demonstrates that public disclosure does not necessarily require bespoke technical infrastructure.
When you need more detail
- BODS schema: https://standard.openownership.org/en/0.4.0/standard/reference.html
- BODS examples: https://standard.openownership.org/en/latest/examples/
- Visualisation spec: https://github.com/openownership/visualisation-tool/blob/main/docs/spec.md
- All OpenOwnership repos: https://github.com/orgs/openownership/repositories
- Regulatory detail: read
references/regulatory-context.md - Country register APIs: read
references/international-registers.md - Corporate data sources: fetch live docs from Sayari, OpenCorporates, BrightQuery, InfobelPro URLs above
- GLEIF pipeline code: https://github.com/openownership/bods-gleif-pipeline
- FtM/OpenSanctions conversion: https://github.com/opensanctions/graph
- BODS RDF/SPARQL: https://vocab.openownership.org/ and world.hey.com/cos posts above
- Procurement + BO: OCDS guidance, ChileCompra case study, bodsriskdetection repo
- Extractives + BO: EITI 2023 Standard, SOE database, BODS mapping notebook
- Public registers: see "Public Beneficial Ownership Registers" table above
- BO declaration forms: OO guide for regulators, OO example forms, EITI model form, Ghana BO3/BO4, Namibia BIPA, UK PSC01
- BODS open issues: https://github.com/openownership/data-standard/issues — feature tracker at https://github.com/orgs/openownership/projects/9/views/1
- Energy + BO: Global Energy Ownership Tracker, GEM reports, OpenSanctions GEOT dataset
- Fisheries + BO: Global Fishing Watch, FiTI 2.0, OO Charting New Waters, C4ADS, Pew
- EU BORIS: e-Justice portal, Regulation 2021/369, Stephen's Medium article on BORIS challenges
- Canada BO: Corporations Canada federal register, BOP2P MRAS programme, CBCA amendments
- BODS case studies: https://www.beneficialownership.co.uk/case-studies — Latvia, Armenia, Botswana, Nigeria, Indonesia, Slovakia, Canada, EITI SOE, GEOT, Structuriser, Foster Moore Verne, NRD BOREG
- ICIJ + Offshore Leaks: https://www.icij.org/investigations/ — Panama Papers, Pandora Papers, FinCEN Files; Offshore Leaks database https://offshoreleaks.icij.org/
- Key BO reports: World Bank Puppet Masters, Signatures for Sale; Transparency International (MENA, Chasing Grand Corruption, Legitimate Interest, Real Estate Opacity 2025); TI-UK (Offshore Secrecy, Trust Registration, Unlocking Ownership, OT/CD legitimate interest series)
- GODIN: https://godin.gleif.org/ — Transparency Fabric, member datasets (GLEIF, OO, GEM, OpenSanctions, Media Registry, AC/DC, Open Data Services, Data Research Center), GitHub repos
- Private sector/register UBO APIs: Kyckr (CorporationUBO/IndividualUBO/OtherUBO schemas + bods-kyckr mapping), Kausate (extractUBOs), Netherlands KvK (Dataservice XML, IPD codes, access tiers), Sweden Bolagsverket, Signicat (Mint UBO lookup), UK Companies House PSC API (natures_of_control codelist)
- BO data verification: OO verification principle + checklist + publication; FATF R24 section 7 (legal persons) + R25 section 4 (legal arrangements); OECD BO toolkits; Tax Justice Network; Moody's KYC; Latvia + Denmark country examples; BODS sourceType verified
- FATF mutual evaluations & country reports: https://www.fatf-gafi.org/en/publications.html (filter by country); consolidated ratings spreadsheet; IO.5 + R.24/R.25 sections in MERs; follow-up reports; grey/black lists; FSRBs (APG, CFATF, MONEYVAL, ESAAMLG, MENAFATF, GIABA, EAG, GAFILAT, GABAC) — check FSRB websites for full reports on non-FATF members
- 2026 register developments: BVI legitimate interest (live 1 Apr 2026); Sri Lanka BO Registry Module + BO1–BO7 forms (live 30 Mar 2026); Sweden legitimate interest (from 1 Jul 2026); Norway 17th BORIS jurisdiction; Ontario BO registry by 2027; Philippines public BO for procurement; St Helena Proton Drive register