Jose Sobrinho is Head of U.S. Technology at Aztec Group.
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The first piece in this series explored machine intelligence in private markets, focusing on workflow automation, the removal of manual bottlenecks and greater centralization of data.
That foundation matters, but data on its own does not move a fund forward. What moves a fund forward is the ability to turn insight into action. In private markets today, that shift is increasingly being supported by connected reporting and dynamic waterfall modeling. While not a universal solution, these capabilities are emerging as important enablers of operational resilience and investor confidence.
Private markets are accelerating. Regulatory expectations are tightening across jurisdictions, and fund structures are becoming more complex, with evergreen and semi-liquid vehicles increasingly common.
Environmental, social and governance reporting adds another layer of pressure. As PwC’s "Asset and Wealth Management Revolution 2022" report highlights, the share of ESG assets over total global assets under management is projected to rise from 14.4% in 2021 to 21.5% by 2026, meaning more assets will sit under heightened disclosure and reporting standards. This level of growth demands reporting that is consistent, auditable and defensible, not reporting rebuilt manually every cycle.
Compliance complexity is already constraining organizations. PwC’s "Global Compliance Survey 2025" found that 77% of organizations said they "had been negatively impacted to some or a great extent" by compliance complexity across areas that directly affect growth.
On the ground, the pressure is becoming increasingly visible. In many organizations, manual processes are struggling to keep pace, reporting teams operate across disconnected systems and waterfall calculations that determine investor distributions are still often managed in spreadsheets that can become difficult to scale as fund structures grow more complex. In this environment, maintaining both precision and agility is becoming progressively more challenging.
For years, reporting was largely a documentation exercise. Templates were populated after the fact. Reconciliations followed the month-end close. The output was a static record rather than a tool that informed decisions. Connected reporting and waterfall platforms are changing that dynamic in two important ways.
First, reporting becomes traceable and governed. When financial performance, compliance data and ESG metrics are brought into a connected environment, reporting can become faster, more consistent and easier to defend under regulatory scrutiny. The role of reporting teams can shift from producing numbers to validating and governing them.
Second, waterfall modeling is beginning to shift toward a more scenario-based approach. Moving distribution logic out of spreadsheets can allow managers to test assumptions, model potential outcomes and adjust as investor composition evolves. What has historically been treated as a back-office calculation can, in this context, start to function as a planning capability that informs decision-making.
This is not simply automation but rather a shift from reactive processing toward more proactive management.
This evolution is cultural as much as technical. Reporting teams are increasingly becoming stewards of data quality and control rather than report producers. Waterfall modeling is shifting toward scenario-driven operation by default, particularly for evergreen vehicles where investor composition evolves continuously.
Artificial intelligence will likely widen the gap between firms with connected data foundations and those without. As McKinsey’s analysis on the economics of asset management notes, the potential impact of AI, generative AI and agent-based automation for an average asset manager could be "equivalent to 25 to 40 percent of their cost base." Realizing those gains, however, depends on mature data governance and integration. Automation is difficult to scale in environments still reliant on disconnected spreadsheets and undocumented processes.
Based on this evolution, there are three steps I recommend firms take to translate strategy into execution.
Start by mapping reporting inputs and ownership. Standardize definitions and metrics. Make approvals, lineage and evidence storage visible and repeatable.
Document distribution rules and edge cases. Create a small library of standard scenarios, and ensure every run produces outputs that are clear and explainable to investors and auditors alike.
The starting point is not new software but connecting what already exists. Identifying the most manual handoffs between fund accounting, reporting, compliance and investor teams can remove significant friction.
As Salesforce’s MuleSoft "Connectivity Benchmark Report" makes clear, many organizations still "struggle to integrate data across systems." The firms that address this early can build a structural advantage that compounds over time.
Private markets are moving toward a model where transparency is continuous rather than periodic. A strategic approach to connected reporting and dynamic waterfall modeling can help make that model workable at scale.
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