You Can’t Vibe Code Cross-Fund Performance Analytics
Summary
Everyone wants cross-fund performance intelligence, but spreadsheets, one-off engineering projects, and AI-generated code rarely scale. Private markets analytics require standardized, governed data before dashboards or reporting can succeed. Learn why PerformA and Aquata provide the institutional foundation for auditable cross-fund performance analytics across complex fund structures.
Private markets growth should be a positive thing instead of an operational anchor that drags down the back-office fund performance reporting efforts. This year, Nuveen bought Schroders Capital's private markets business to birth a giant with $414 billion in combined private markets assetsi; Mercer agreed to acquire AltamarCAM, which manages about $22 billion in private market AUMii; and in 2025 BlackRock acquired HPS Investment Partners to deploy $220 billion in private credit.
While the front office uncorks their champagne, the operations teams are adding lines to interminable spreadsheets and diving into a perplexing cross-fund performance analytics morass. Fund accounting and performance measurement teams know what they want: cross-fund performance intelligence, the ability to extract insights and track performance across any and all asset classes or structures in a firm’s portfolio. Once they conclude it is onerous to do it the old-fashioned way, they may summon IT to do one-off engineering projects or do some vibe coding.
This level of analytical sophistication for illiquid and structured products requires institutional infrastructure, not ad hoc tooling that crumples under the weight of scale. This is why you cannot vibe code standardized, auditable cross-fund intelligence.
Structural complexity is the quiet cost of growth by acquisition
For a firm trying to compete on the strength of its brand equity, this is the quiet cost of growth by acquisition: more funds, multiple methodologies, more manual work, and performance numbers that are never quite as fresh or trustworthy as they need to be. Unified private markets data becomes a distant dream.
Real-world scenario: fund manager acquires three subsidiaries
Suppose a $30 billion fund manager acquired three established private credit subsidiaries that, combined, will give it $25 billion additional AUM to manage. Suddenly, the manager’s single operating model is asked to integrate 30 or 40 active funds of multiple vintages and fund administrators. The confetti falls to celebrate the newfound scale, almost doubling the size of the firm. However, the deal has created a data management problem that poses serious challenges to the firm's ability to tell its own performance story.
Three managers with three methods of tracking and measurement
Each acquired subsidiary comes to the party with its own operational processes, people, and models. All three routinely track fund performance using spreadsheets, but these three sheets are not all the same. There are no standardized formulas or performance calculation methodologies.
Three answers to one important performance question
Each acquired firm had meticulously designed their spreadsheets over the years, in accordance with their own IRR methodologies, with their own assumptions, cash flow conventions, and formulas embedded in cell logic – key-person logic that is not easily understood by colleagues. Any fat-finger mistake could distort an IRR figure, and nothing in the process would necessarily catch the discrepancy. Instead of a single clean answer, three fund managers give three different answers to a question. And all three could be wrong.
An investment performance reporting bottleneck
In the newly scaled $55 billion firm, fund administrators have to value each portfolio and calculate net asset value (NAV) before any total performance figure can be computed. Unfortunately, instead of a daily or weekly cadence, net assets are calculated quarterly, fund by fund. Therefore, the performance calculation becomes beholden to the quarterly valuation cycle. That will not suffice in the competition for investors.
Prospective investors receive stale data
Meanwhile, the business development team manually pulls performance figures out of each fund's spreadsheet and transcribes them into marketing materials. Precise results typically are not released until a manual, fund-by-fund extraction exercise was completed, as late as the second month of the following quarter. By the time performance information reaches prospective investors, it is weeks old. The quiet cost of the acquisitions becomes loud and obvious to all. The result: a rickety performance reporting workflow, strained at every stage, and late to the party.
“While data are becoming more available, the lack of data still presents a significant barrier to analyzing performance for many investors. Additionally, while these data may become more available, the lags in reporting and low frequency of observation pose additional challenges. For example, quarterly fund net asset values (NAVs) are not true market values and are only available with a substantial lag. While efforts have been made to create more frequent valuation measures in PE, the majority of usable data are reported on a monthly, quarterly, or even annual basis. Additionally, this creates limitations for model estimation and inference.” — Institute for Private Capital, Performance Analysis and Attribution with Alternative Investmentsiii
Fund Structure Complexity and Bespoke Economics
Modern private fund structures can be highly complex and include multiple layers of legal entities plus numerous SPV’s. There are expenses at every level, and investor capital balances and performance fees are often tracked on a deal-by-deal basis. The complexity of these multi-layered structures creates a significant operational burden. Every month, firms must take the income generated at the master fund level and allocate it back down through every entity layer to the individual investor. On top of all this, private funds utilize highly bespoke economic arrangements, including tiered fee structures, hurdle rates, and complex waterfall calculations that are difficult to manage systematically. The end result, frequently, are labyrinthine, fragile spreadsheets that track a manager’s most critical client account data.
Performance reporting software to enable unified analytics platform for private markets
The roadblock in getting accurate and timely performance dashboards across multiple funds is the array of disparate systems, data models, and sometimes even calculation methodologies. Vibe coding and engineering band-aids may be brilliant, but they cannot last under the speed and volume of private markets.
The simple objective is standardized, auditable cross-fund intelligence. Firms need a single-pane, private markets performance dashboard across multiple funds.This requires centralized data infrastructure to provide automated, repeatable cross-fund capabilities that track ownership, capital balances, and IRRs across this complex entity chain. With unified private markets data, a newly scaled firm gets a common dataset that allows the application to speak the same language across funds of all types, bridging them together and running analytics and reports on top of it.
The common, standardized data platform smoothly distributes capital and P&L flow from the master fund level through the various entities all the way down to individual investor balances, which can involve hundreds and perhaps thousands of unique accounts. Automated total performance analytics and reporting become reality. The firm can now dazzle investors with pinpoint cross-fund comparisons, exposure summaries, historical performance, and customized reporting. The reports will not be late, nor will they have undetectable errors buried within. Further, cloud-based data infrastructure built for investment management is scalable, able to handle these high volumes natively.
When a company like Mercer agrees to acquire AltamarCAM, it would ideally have centralized data infrastructure to integrate performance reporting for legacy Mercer portfolios, multiple private asset classes, multiple client segments, and AltamarCAM funds – which include PE, infrastructure, private credit, and secondaries.iv
Private markets performance analytics is a trust play
Performance reporting is ultimately a mechanism of trust and confidence. Unlike standard trade errors where a client might scold a fund manager, investor accounting errors result in LPs questioning the manager's credibility. If your firm is receiving friction from dissatisfied investors on reporting, fees, and performance, it may be time to modernize and standardize private market performance analytics. Trust and confidence can be a viral phenomenon. If your firm’s risk managers, fund accounting, and performance measurement teams work with less than 100% confidence in the data, then the investment committee and executives will have no confidence. Big decisions will need to wait on painstaking reviews of the numbers.
A firm’s reputation is highly connected to financial penalties, re-issued statements, and liquidity shortages if capital calls are sent to the wrong investors. A single view of performance that everyone under the roof can trust reverses the virus of lost trust, producing a contagion in confidence that makes everybody more effective.
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Amit Mehta
Amit is Vice President, Product Management at Arcesium, co-leading the transformation of the firm's Investor Allocation platform, helping shape the roadmap and expanding it into new market segments to unlock value for customers running complex fund structures. He brings 16 years of experience across fintech and fund operations, with deep expertise in fund accounting and investor allocations.
Sources:
[i] Reuters, February 12, 2026. https://www.reuters.com/business/nuveen-agrees-buy-schroders-135-billion-2026-02-12/
[ii] Marsh, 2026. https://www.corporate.marsh.com/news-events/2026/march/marsh-to-expand-its-private-markets-capabilities-with-the-addition-of-altamarcam.htm
[iii] Institute for Private Capital, February 2022. https://uncipc.org/wp-content/uploads/2022/02/IPC-Performance-Attribution-Analysis-v2022-02-12.pdf
[iv] Marsh, March 2026. https://www.corporate.marsh.com/news-events/2026/march/marsh-to-expand-its-private-markets-capabilities-with-the-addition-of-altamarcam.html
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