Key Takeaways
- • Dakota argues that private fund software reports performance metrics such as net IRR, TVPI and DPI but does not show whether those figures are strong relative to comparable funds.
- • Family offices held 21% of portfolios in private equity in 2024, according to the UBS Global Family Office Report 2025, and nearly half of RIAs allocate 10% or more of AUM to private markets, per the KKR 2025 RIA Survey.
- • Peer benchmarking by strategy, vintage, sector and methodology provides the context needed for quartile ranking and due diligence.
- • Dakota's private fund benchmarking data covers 18,000+ private funds and can be integrated into wealth management platforms via API, embedded Peer Group Builder, white-label module or dataset license.
Summary
This article, published on Dakota's website, contends that wealth management and family office software has become adept at reporting private fund performance but has not helped users interpret it. The piece cites UBS's Global Family Office Report 2025, which found family offices held 21% of their portfolios in private equity in 2024, and the KKR 2025 RIA Survey, which found nearly half of RIAs allocate 10% or more of AUM to private markets.
The article distinguishes between reporting and intelligence. Traditional reporting captures capital committed, capital called, distributions and current value. Its three core metrics each leave a gap: net IRR does not indicate whether a return is strong for a given vintage and strategy, TVPI does not show how a multiple compares with similar funds, and DPI does not reveal whether distributions are ahead of or behind peers.
Using an illustrative example, the article notes that a 2021-vintage fund with an 18% net IRR and 0.3x DPI may appear superior to a 2017-vintage fund with a 14% IRR, 1.9x TVPI and 1.2x DPI, yet the comparison is misleading because the funds differ in vintage and maturity. The author argues that the appropriate question is how each fund ranks against peers of the same strategy and vintage, measured on consistent dates. The article also identifies strategy, vintage, sector and methodology as factors that complicate private market benchmarking.
The article offers a hypothetical case in which a 2020-vintage buyout fund with a 15.2% net IRR and 1.8x TVPI is compared with an assumed peer median of 12.5% IRR and 1.6x TVPI, a difference of 2.7 percentage points and 0.2x. The article states these benchmark figures are hypothetical and not actual Dakota data.
The article outlines five ways benchmarks could change wealth management software, including surfacing outliers, improving due diligence and enabling premium analytics tiers. It concludes by promoting Dakota's benchmarking data, which covers 18,000+ private funds with net IRR, TVPI, DPI, RVPI and PME metrics, available through API, embedded Peer Group Builder, white-label module or dataset license. The piece is commercially oriented and promotes Dakota's services.
The article distinguishes between reporting and intelligence. Traditional reporting captures capital committed, capital called, distributions and current value. Its three core metrics each leave a gap: net IRR does not indicate whether a return is strong for a given vintage and strategy, TVPI does not show how a multiple compares with similar funds, and DPI does not reveal whether distributions are ahead of or behind peers.
Using an illustrative example, the article notes that a 2021-vintage fund with an 18% net IRR and 0.3x DPI may appear superior to a 2017-vintage fund with a 14% IRR, 1.9x TVPI and 1.2x DPI, yet the comparison is misleading because the funds differ in vintage and maturity. The author argues that the appropriate question is how each fund ranks against peers of the same strategy and vintage, measured on consistent dates. The article also identifies strategy, vintage, sector and methodology as factors that complicate private market benchmarking.
The article offers a hypothetical case in which a 2020-vintage buyout fund with a 15.2% net IRR and 1.8x TVPI is compared with an assumed peer median of 12.5% IRR and 1.6x TVPI, a difference of 2.7 percentage points and 0.2x. The article states these benchmark figures are hypothetical and not actual Dakota data.
The article outlines five ways benchmarks could change wealth management software, including surfacing outliers, improving due diligence and enabling premium analytics tiers. It concludes by promoting Dakota's benchmarking data, which covers 18,000+ private funds with net IRR, TVPI, DPI, RVPI and PME metrics, available through API, embedded Peer Group Builder, white-label module or dataset license. The piece is commercially oriented and promotes Dakota's services.
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