Use cases & endpoints
LEI, CIK and CNPJ mapping API for cross-border data
Regulators do not coordinate identifiers. An LEI is issued for entities transacting in financial markets, a CIK is assigned by the SEC to anything that files, and a CNPJ is a Brazilian tax registration. The same corporate group can hold all three plus a dozen more, distributed across subsidiaries in ways that reflect legal structure rather than how anyone thinks about the business.
Joining datasets across these identifiers by company name is the classic mistake — names differ by punctuation, legal suffix, transliteration and vintage, and a fuzzy match that works for large caps fails silently on exactly the mid-cap subsidiary you were investigating.
Hindcast maintains explicit mappings between the identifier systems, anchored to entity nodes and dated so a historical question resolves against the structure that existed then. When no reliable link exists, the absence is returned rather than guessed, because a wrong join is more expensive than a missing one.
hindcast — session
previewhindcast> resolve an LEI to its SEC filer and Brazilian registrations
→ tool: entity_resolve { id:"...", type:"lei", include:["cik","cnpj"] }
✓ linked identifiers with relationship type and validity dates
source: registry records across jurisdictions, links dated
What's covered
- LEI, CIK, CNPJ, ISIN, CUSIP and tickers on one graph
- Relationship type recorded — same entity, parent, subsidiary, issuer
- Mappings dated so historical joins resolve correctly
- Missing links returned as absent rather than fuzzy-matched
- Name history retained across renames and transliterations
- Used internally by every other dataset in the catalog
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Questions
What if two identifiers cannot be linked reliably?
The response says there is no link. Returning a probable match without saying so is how a portfolio ends up attributing a subsidiary's filings to its parent, and that error is very hard to detect downstream.
Is this just a static reference file?
No — it is versioned. Corporate structures change, identifiers get reassigned, and a mapping without dates will quietly corrupt any analysis that reaches back more than a couple of years.
Related
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