What Standardized, Auditable Cross-Fund Analytics Actually Unlocks for Private Markets Managers

In our recent blog post, we talked about how performance reporting is ultimately a mechanism of trust and confidence and how you cannot vibe code standardized, auditable cross-fund intelligence. Managers are feeling the pressure from all sides to elevate their private markets performance reporting game. Bloomberg recently reported that private credit investors have become more discerning about dispersion in investment marks, heaving greater weight on realized asset performance and portfolio quality.ⁱ Not only are limited partners (LPs) demanding more frequent, customized, and sometimes ad hoc performance updates, but internal stakeholders need timely analytics to make returns-generating moves in times of volatile market movements.

Private market managers can move beyond haphazard, latent reporting and answer high-stakes questions – if they have unified data analytics across all liquid, illiquid, and structured products. Only institutional data infrastructure and an automated private market reporting platform can enable cross-fund performance analytics and auditability for LP reporting. At that time, managers can confidently answer urgent analytical questions from LPs and the c-suite bosses about the total portfolio’s liquidity, positions, exposures, and collateral.

Private market structures muddy performance reporting

Twenty-three percent of asset managers and asset owners indicated that the increasing frequency of NAV calculations to daily was a top pain point. Half of global GPs (49%) reported that portfolio-level data is a significant problem.ⁱⁱ

Tax optimization, co-investments, and tailored financing arrangements have led to a proliferation of multi-layered entities, stacked with creative fund-structuring vehicles. Every month, accounting must take all the income that the portfolio generated and allocate it to these various entities. Income generated at the master fund level must be routed back through every entity layer down to individual investor balances.

An investor accounting manager for a fund with 400 investors and 5 layers of entities is pushing the boulder up a mountain before reaching the final capital balance for every investor account.

Spreadsheet-based models can buckle, producing significant latency or even crash when handling high volumes of accounts and complex deal-level data. This process involves long-nested conditional statements that are prone to calculation errors. If your number is wrong, you are either paying them too much or not enough. Both are unacceptable. As such, private market firms have an urgent need for automated, repeatable workflows and standardized performance analytics. 

Answering the tough questions from the LP

What would the performance fee be if time stopped right now? What is the investor's return before and after specific bespoke fees? What happens to our NAV and fee income if we apply a haircut to a specific security? The inability to get prompt answers to these questions is a detriment to the operation.

You may rely on your fund administrator to serve up these answers. But a fund administrator's main business objective is to produce a net asset value (NAV) for the fund and calculate investor capital balances. Generally, fund administrators’ remit doesn’t include the detailed, bespoke reporting that investors demand. This can leave GPs in a fragmented data chase, trying to cobble together precise numbers to appease the LP.

Objective: the automatic flow of standardized performance data

To bind and centralize all of the security and reference data under a firm’s roof, it needs a unified data foundation that can handle both structured and unstructured private market data. Additionally, the data platform needs capacity to handle huge volumes of data. Spreadsheets can, up to a point. A cloud-native data foundation will not only handle enormous volumes of investment data but also allow for a firm’s perpetually expanding data stores as it scales the business.

Subsequently, the operational solutions layered on top of the data foundation can be connected and automated, including performance and investor allocations and portfolio accounting solutions. A configurable performance allocations solution will execute all bespoke fund accounting situations, calculating and maintaining the underlying data of income allocations and fee calculations, natively. Once the structure is configured, the system takes over.

A finance-native system like this is designed to handle whatever complex situation a manager serves up. It manages the routing of data, systematically handling commitments, capital calls, and distributions through the entire entity chain.

Don’t go chasing waterfalls into a performance allocations hole

The explosion of private markets investments has muddied operational waters in numerous ways, including American and European waterfall methods to charge performance fees for closed-end funds. Even the more straightforward European method, prioritizing the return of the investor's original capital before the manager can collect incentive fees, can gum up workflows and lead to lots of manual calculations. The investment accounting manager must configure their performance allocations system to manage who gets paid when, how much carry is earned, and if clawbacks apply. Ideally, they have a clear investment performance dashboard to pull up reports for PE or private credit funds.

American waterfalls require more frequent calculations on a deal-by-deal basis, more acute clawback complexity, and more intricate investor accounting. Firms use waterfalls to charge incentive allocations or carried interest for many private credit classes like direct lending, infrastructure funds, and asset-based finance (ABF), which requires near-real-time asset valuation, precise interest accruals, and collateral tracking. This is when spreadsheets disintegrate, resulting in missed borrower delinquencies, defaults, or restructuring. Waterfall triggers cannot slip through the cracks to cause errant P&Ls.

Centralized and automated data flows for superior benchmarking

A firm running on a centralized security and reference data foundation and automated private markets performance allocation engine can gain the self-assurance when reporting to an investor, and their investor won’t become disgruntled by tardy distributions or reports. Modern data infrastructure can pull in data and validate it from numerous sources dealing with multiple borrowers and data for the underlying collateral.

Moreover, this level of analytics and reporting agility benefits other functions, from reconciliation to liquidity risk management. The notoriously difficult process of investment-level, cross-fund benchmarking becomes much easier and more reliable. Finally, you can serve up accurate answers to questions like, is private credit outperforming real estate, or which strategy is attracting the highest returns on invested capital.