Data & Identifiers

Overview

Accurate security identification is foundational to the data provided by datawiser.

Financial instruments may be referenced using multiple identifier systems, each with different properties and limitations. datawiser standardizes these references to support consistency across datasets, APIs, and time.

Identifier Hierarchy

datawiser distinguishes between canonical identifiers and convenience identifiers.

Canonical identifiers:

• FIGI
• Internal entity and security mappings maintained by datawiser

Convenience identifiers:

• Ticker symbols, with exchange context where relevant

All API requests are normalized internally before processing.

FIGI

datawiser uses FIGIs as the primary public security identifier.

FIGIs provide:

• Globally unique instrument identification
• Separation of share classes
• Cross-market consistency

Where available, FIGIs are used as the canonical public identifier for securities across datasets and APIs.

Entity Resolution

datawiser maintains its own internal entity resolution framework to support continuity across datasets, securities, and time.

This framework is built from public filings, internal mapping logic, and supporting reference data. It is used to group related instruments and preserve continuity through structural changes such as share class differences, depositary receipt relationships, ticker changes, and selected corporate actions.

Ticker Symbols

Ticker symbols are provided for convenience and user familiarity only.

Tickers:

• Are exchange-specific
• May be reused over time
• May not uniquely identify a security without exchange context
• Do not, by themselves, fully capture share-class or entity-level relationships

datawiser does not treat tickers as stable canonical identifiers.

Ticker-based inputs are resolved internally before processing.

Identifier Mapping

datawiser maintains an internal mapping layer to resolve relationships between identifiers and securities over time.

This includes, where relevant:

• Share-class relationships
• Depositary receipt relationships
• Historical ticker changes
• Selected corporate actions affecting security continuity

Mappings are designed to preserve consistency and auditability across datasets.

Edge Cases

Certain scenarios require additional care in identifier resolution, including:

• Dual-class or multi-class share structures
• Depositary receipts
• Delisted or inactive securities
• Corporate actions affecting continuity

datawiser aims to handle these consistently within its internal mapping framework.

Third-Party Reference Data

datawiser may incorporate industry-standard reference data to support identifier normalization and entity resolution.

Such reference data supports, but does not define, datawiser's internal identity model.

Summary

• FIGI - primary public security identifier
• Internal mappings - entity and security continuity
• Tickers - convenience input and output only

All data is normalized internally to support consistency, stability, and auditability.