5 mistakes to avoid when structuring investment fund data

So much information shapes final performance. Yet, in many asset management practices, this data is still managed as a dormant asset rather than a strategic asset. The result: wasted time, regulatory risks and difficulty in innovating. Here are five common pitfalls, observed in funds of all sizes, and some strategies for avoiding them.

Mistake no. 1: stacking spreadsheets like bricks

In many investment funds, the first pitfall is to stack spreadsheets like building a brick wall: a financial controller updates "Valo_final_v12(1)" while an analyst works on "PIPE_mars_clean_V34". As each version is updated, the figures diverge insensitively, and eventually make their way to the investment committee. As long as each team has its own "good" local copy, more energy is spent reconciling data than analyzing it. The only way out is through a single repository (base SQL robust on a shared local server or sovereign cloud warehouse) where access rights replace the frenetic circulation of attachments. The spreadsheet then reverts to being a one-off simulation tool, no longer the official foundation.

Error n°2: ignoring data lineage

When an LP asks for the complete history of a holding's cash flows, the hunt for tabs and e-mails opens up, revealing the absence of tracking. Without a breadcrumb trail, proving the origin of a figure becomes perilous when faced with the AMF or an auditor. Conversely, a data catalog (open source or proprietary, hosted on a French server) preserves each transformation, identifies the owner of each field and finally brings the serenity that investors and regulators require.

Mistake #3: blindly outsourcing your infrastructure outside Europe

To move fast, some teams deploy CRM, EDM or dataroom on a "plug and play" extra-European cloud. On the face of it, everything works; however, the American Cloud Act looms over this confidential data. For a fund positioned in strategic sectors, ceding its sovereignty in this way is tantamount to leaving an open door on its deals. Choosing a certified European provider, encrypting data at rest and in transit, and contracting a strict location are the minimum safeguards.

Error #4: believing that governance is the sole responsibility of the CTO

It is often believed that data governance is the sole responsibility of the CTO or outsourcing company. An RGPD policy written in black and white is worthless if no one knows who actually owns the data concerned. Processes erode as talent rotates, and compliance becomes cosmetic. Gathering Front Office, Middle, Compliance and IT around a Data committee every quarter changes the game: indicators of completeness, freshness or quality are no longer technical abstractions but shared objectives.

Error n°5: launching into AI before making the base reliable

Finally, many GPs launch into artificial intelligence without having made their base reliable. They dream of a chatbot that writes the investment committee memo or answers the LP without hallucinations. But the model gets it wrong because it queries PDF poorly structured. A malnourished AI amplifies inconsistencies and threatens the fund's reputation. The remedy starts with rigorous quality control, coupled with clear classification of sensitive data. Once this foundation has been laid, an LLM encapsulated in a factual verification layer becomes an ally, not a risk.

Sovereignty as a performance lever

By avoiding these five missteps, a fund transforms its dormant asset data into a genuine performance lever, while preserving its sovereignty and the trust of its investors. Structuring data is not just a regulatory obligation: it's a competitive advantage. A fund capable of tracing the origin of each KPI, ensuring the sovereign localization of its data and deploying reliable AI creates a climate of trust with its LPs. At a time when Europe is pushing the AI Act for summer 2026 and more digital sovereignty, avoiding these mistakes comes down to making data a driver, not a brake, in value creation

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