Investment Funds Taxonomy Template v1.0

Why a Taxonomy for Investment Funds?

Investment funds come in many shapesmutual funds, ETFs, hedge funds, privateequity vehicles, and more. Market participants, regulators, data providers and technology platforms need a common language to:

• Compare products across jurisdictions.
• Automate reporting and compliance checks.
• Enable advanced analytics and ESG scoring.
• Reduce ambiguity in contracts and marketing material.

The Investment Funds Taxonomy Template (IFTT) provides a reusable, versioncontrolled schema that satisfies those needs while remaining flexible enough to evolve with the market.

Core Principles of the Template

1. Clarity: Every term is defined in plain language and linked to a unique identifier.
2. Extensibility: New categories or attributes can be added without breaking existing implementations.
3. Interoperability: The schema aligns with existing standards such as ISO20022, XBRL, and the Global Investment Funds Classification (GIFC).
4. Governance: A transparent changemanagement process governs updates, with stakeholder voting and public comment periods.
5. Technologyagnostic: The template can be expressed in JSONLD, XML, or CSV, allowing easy integration into any system.

Structure of v1.0

1. TopLevel Domains

Four primary domains organise all fund types:

• Asset Class: Equities, Fixed Income, MultiAsset, Real Estate, Commodities, etc.
• Legal Structure: Openended, Closedended, Unit Trust, SICAV, Limited Partnership, etc.
• Management Style: Actively Managed, Passive (Index), Smart Beta, Hedgestyle, etc.
• Geographic Scope: Domestic, Regional, Global, Emerging Markets.

2. Attribute Sets

Each fund record carries a defined set of attributes grouped into logical sets:

• Identification: ISIN, LEI, Fund Name, Ticker.
• Investment Strategy: Benchmark, Riskreturn profile, ESG focus.
• Regulatory Information: Jurisdiction, Regulatory status, Registration number.
• Operational Details: Management fee, Performance fee, Minimum investment, Liquidity terms.
• Data Quality Flags: Source reliability, Last update timestamp, Validation status.

3. Hierarchical Relationships

The taxonomy captures parentchild relationships, for example:

• A Global Equity Fund (parent) can contain US LargeCap Core and EM SmallCap Growth (children).
• Series structures (e.g., Class A, Class B) are linked via the hasSeries property.

4. Controlled Vocabularies

All enumerated fields pull from controlled vocabularies stored in separate lookup tables. Version identifiers (e.g., CVAssetClassv1.0) ensure that downstream systems can map historic data correctly.

Implementation Guidance

Data Modelling

Adopt a graphoriented model (RDF or propertygraph) for maximum flexibility. Each fund is a node with edges to classification nodes, attribute nodes and relationship nodes.

File Formats

Typical exchange formats include:

• JSONLD: Ideal for web APIs and linked data applications.
• XML (XSDvalidated): Preferred by legacy reporting pipelines.
• CSV with schema header: Simple bulk load for data warehouses.

Validation Rules

Every payload must pass the following checks before acceptance:

1. All required identifiers (ISIN, LEI) are present and checksumvalidated.
2. Classification codes belong to the current controlled vocabularies.
3. Numeric fields (fees, minimums) fall within industryaccepted ranges.
4. Temporal fields (inception date, reporting period) are logical (e.g., inception today).

Version Management

When a new version of the taxonomy is released, providers should:

• Maintain a taxonomyVersion field on each record.
• Provide a migration guide that maps deprecated codes to their replacements.
• Run dualvalidation against both old and new schemas for a 6month transition period.

Benefits for Stakeholders

Asset Managers

Clear, consistent product descriptions reduce marketing friction, simplify prospectus creation, and enable faster onboarding of institutional clients.

Investors & Advisors

Standardised data makes duediligence faster, supports automated suitability checks, and improves comparability across platforms.

Regulators

Uniform classification eases monitoring of systemic risk, facilitates crossborder supervision, and underpins consistent reporting under MiFIDII, AIFMD and other regimes.

Data Vendors

One taxonomy eliminates the need to maintain multiple mapping tables, reducing operational cost and improving data quality.

Sample Data Record (JSONLD)

{  "@context": "https://example.org/iftt/v1.0/context",  "id": "urn:isin:US1234567890",  "type": "InvestmentFund",  "taxonomyVersion": "v1.0",  "identification": {    "isin": "US1234567890",    "lei": "5493001KJTIIGC8Y1R12",    "name": "Global Growth Equity Fund",    "ticker": "GGX"  },  "classification": {    "assetClass": "Equity",    "legalStructure": "OpenEnded",    "managementStyle": "Active",    "geographicScope": "Global"  },  "attributes": {    "benchmark": "MSCI World Index",    "managementFee": 0.0125,    "performanceFee": 0.2,    "minimumInvestment": 5000,    "inceptionDate": "2015-03-15",    "currency": "USD",    "esgFocus": true  },  "regulatory": {    "jurisdiction": "USA",    "registrationNumber": "12345-ABC",    "status": "Authorized"  },  "quality": {    "source": "FundProviderAPI",    "lastUpdate": "2026-05-28T10:00:00Z",    "validationStatus": "Validated"  }}    

Roadmap Beyond v1.0

The taxonomy is designed as a living document. Planned enhancements for the next two years include:

• ESG SubTaxonomies: Detailed carbonintensity tiers, sustainablethemed classifications, and impactmeasurement attributes.
• Digital Asset Funds: Separate branch to capture cryptofocused funds, tokenised securities, and related risk metrics.
• Dynamic Benchmark Mapping: APIdriven linking to benchmark providers for realtime reference data.
• MachineReadable Change Log: An RSS/Atom feed that publishes every amendment to the schema.

Stakeholder feedback will be gathered through quarterly workshops and an online public comment portal.

Getting Started

To adopt the Investment Funds Taxonomy Template v1.0, follow these steps:

1. Download the official schema package from https://example.org/iftt/v1.0.
2. Integrate the JSONLD context (or XML XSD) into your data ingestion pipeline.
3. Run the supplied validation suite against a sample data set.
4. Map any internal classification codes to the IFTT controlled vocabularies.
5. Publish a taxonomyVersion field on all outgoing fund data feeds.

Support channels include a dedicated Slack community, a public issue tracker on GitHub, and quarterly webinars hosted by the governing board.

Contact & Resources

For more information, consult the following resources:

• Official Specification (PDF): spec.pdf
• Implementation Guide (HTML): guide.html
• GitHub Repository (schema & tools): github.com/example/iftt
• Community Forum: forum.example.org/iftt