Business Relevance of Fund Data Quality

Global institutional players nowadays have to rely on structured and quality-assured data-provision. Whether for ESG screening, cost analyses or as distribution requirement – every aspect counts. Missing fund data means missed opportunities. Incorrect fund data means risk. And only valid data create trust.

Our clients confirm: With the Fenion Fund Data Stream, they receive not just fund data – but a complex, dynamic data product as the foundation for reliable fund processes.

Fund data quality is not an IT issue, but a potential (additional) cost factor. Incorrect or missing fund data might become expensive.

Garbage in – Garbage out: data errors block operational chains.

Here is a real-world example: A sustainable Fund-of-Funds intends to invest exclusively in Article 8 or Article 9 target funds with a positive PAI rating. However, in the EET, several target funds are missing parameters relevant for ESG risk analysis. As a result, these target funds fail the ESG screening – not because they are unsuitable, but because relevant data is missing or inconsistent. Blurred categorizations and classifications, missing price and dividend histories are likewise among common fund data errors. These often do not arise from negligence or manual data entry, but because fund data originates from different sources (KIIDs, EETs, PDFs, XML feeds) – each with varying degrees of timeliness and formats.

In the Fenion Fund Data Stream, quality is no coincidence, but rather an integral component and the foundation of the fund database: daily quality checks for completeness, timeliness, source provenance, auditable timelines for all data points, and data rule sets per use case are implemented as standard. By deploying professional data management and a rule-based quality framework that combines subject-matter validation with technical control, we provide complete, correct, consistent, and traceable fund data.