A mid-size institutional allocator typically spends between two and three months and upwards of €50,000 in internal and external cost to evaluate a single private equity fund. Multiply that by the number of commitments in a vintage and the cumulative cost becomes meaningful, but the direct cash cost is not the whole story. The process itself introduces risk.
Where the inefficiency sits
Three cost centres dominate. The first is manual data capture from the data room: extracting numerical disclosures, reconciling them against prior communications, and normalising them into the allocator's internal templates. The second is peer benchmarking against whatever dataset the allocator happens to have access to, which in practice is usually incomplete. The third is memo drafting, which is repeated from scratch for every fund.
Each of these steps is performed by senior analysts whose time has a high opportunity cost. The result is that allocators systematically under-evaluate funds that do not clear a subjective initial threshold, because the marginal cost of a second look is too high.
Why the process itself becomes a risk
When evaluation capacity is the binding constraint, the allocator's pipeline is biased toward funds that are easy to evaluate rather than funds that deliver the best risk-adjusted return. Adverse selection follows. It also follows that the quality of evaluation degrades under time pressure at quarter end, exactly when IC calendars are full and the latest funds in a vintage are competing for the last slots of attention.
The infrastructure answer is to separate the mechanical work of data capture and benchmarking from the analytical work of judgement. The mechanical work should be automated and repeatable; the judgement should be where senior time is spent. Closing that gap is the premise of QFT's Fund Due Diligence module.