Despite generally positive second-quarter earnings, health insurers are heading into the final months of 2026 and early 2027 facing a slew of market and regulatory pressures, including persistently high medical costs, enrollment declines (stemming from new restrictions and verification rules related to marketplace plans and Medicaid), a sicker risk pool, rising inflation, and broader economic uncertainty. Moreover, some actuarial teams might be reporting different numbers to leadership due to inconsistent data sources, timing, and definitions.
The combination of these factors is making trend analysis and forecasting an increasingly difficult operating challenge. Understanding where medical costs are headed and giving leaders a more reliable view of what that means for their business is vital.
But most of the work needed to produce that view rarely sits in one place. Pricing, for instance, is usually organized by line of business. Valuation tends to be centralized. Medical economics may sit within actuarial or a closely linked analytics or finance organization. Technology and data responsibilities are often shared with enterprise IT. The data itself is often just as scattered. Valuation, pricing, medical economics, finance, and market data live in separate systems, at different levels of granularity, and definitions can vary from team to team.
That fragmentation exposes operational gaps. In a series of interviews with chief actuaries at some of the nation's largest payers, representing more than 70% of covered lives, our conversations suggest that the gaps are most visible in trend and forecasting. Leaders still need actuaries who have a deep understanding of specific lines of business and regions while also seeking an enterprise-wide view of performance and financial outlook. Organizations should take a close look at how the pieces fit together. The issue comes down to who owns key decisions, how teams work across functions, and whether leaders ultimately receive one coherent view of the business.
Why health actuarial organizations need a new operating model
Health actuarial organizations are complex. Commercial, Medicare, and Medicaid businesses operate in different markets and regulatory environments. Pricing requires deep line-of-business expertise, but valuation benefits from enterprise-wide methodologies. Meanwhile, medical economics draws on clinical, network, pharmacy, and utilization data.
The problem occurs when those capabilities are disjointed rather than part of a larger decision-making system. Consider forecasting: finance typically generates the enterprise outlook, actuarial teams own most of the underlying assumptions, and line-of-business teams maintain their own views of emerging performance. Without clear governance, organizations can end up with multiple forecasts, each defensible on its own, but lacking a consistent enterprise perspective.
Part of that divergence is judgment. Actuaries can reasonably differ on trend picks and completion factors, and a healthy organization wants that debate. But much of the divergence leaders described to us was more mundane, with teams pulling the same concept from different systems, at different points in time, under slightly different definitions. A single quarter of medical cost trend can leave the building with four different numbers — on a paid, incurred, booked, and normalized basis. Each is right on its own terms, and they are reconciled by hand every quarter, usually in spreadsheets. Governance forums end up settling arithmetic when they should be debating implications.
Several leaders described the solution in practical terms: someone needs to quarterback the forecast, teams need to agree on which assumptions feed it, and differences need to be resolved before the numbers reach senior leadership. Increasingly, that comes with a prerequisite. The quarterback needs one set of numbers to call plays from.
Four principles for a stronger health actuarial operating model
One of the clearest takeaways from our interviews is that governance and relationship-building are more important than reporting lines. And there isn’t a universal operating model that can — or should — be applied across all companies. Geographic footprints, legal entities, lines of business, and the degree of integration with finance and analytics all play a role in how insurers can revamp their actuarial operating model. We identified the following four principles that health plan leaders should consider:
1. Centralize actuarial data and governance for consistent decisions
Some actuarial capabilities are more valuable when the enterprise shares common methodologies, data, and governance. Most of the health plan leaders we interviewed have already centralized valuation. We saw similar thinking applied to other capabilities, including trend methodology, parts of medical economics, and the technology and data layer supporting actuarial work. While medical costs, for instance, are influenced by multiple components like utilization, unit cost, pharmacy, and value-based care arrangements, leadership often needs one coherent explanation of what is happening and why. Some plans have responded by naming owners of major trend components and establishing trend-management or medical-cost-steering committees. The point of those forums is to settle methodological differences before they turn into competing explanations in front of leadership. Not everything needs to be centralized. But where senior management needs one enterprise answer, ownership cannot be ambiguous.
2. Embed expertise where business context and trust matter
Pricing and forecasting decisions require knowledge of local market dynamics, competitive conditions, provider relationships, regulatory developments, and line-of-business strategy. Those insights are difficult to provide from a centralized function. Through our interviews, we found that many health plans address this by maintaining clear actuarial relationships with individual businesses and markets. A common model gives line-of-business pricing leaders a solid reporting line to the chief actuary and a dotted-line to P&L or regional leadership. Many plans also designate specific actuarial contacts, so business leaders know exactly who to call for questions about pricing, trends, forecasting, and performance. Those relationships are reinforced through recurring monthly results discussions, trend reviews, forecasting forums, and other structured touchpoints.
3. Strengthen actuarial and finance alignment through governance
Reporting lines establish accountability, but they do not by themselves determine how actuarial, finance, medical economics, technology, and business leaders work together. Organization design is about more than reporting lines. Problems can’t be fixed by shuffling lines and boxes around on a chart. That’s not the problem. Standing governance forums can establish common methodologies and ensure that differing interpretations are resolved before they reach senior leaders. Across our interviews, we heard less emphasis on finding the perfect reporting line and more on making sure someone clearly owns the answer.
4. Create a single source of truth for health plan actuarial data
The organizational questions sit on top of a quieter problem. Valuation, pricing, medical economics, finance, and market data typically live in separate systems and at different levels of granularity. Each team assembles its own working version. Small differences in extracts, timing, and definitions become competing answers that governance forums must arbitrate. In our experience, the health plans making the most progress are those building a single governed data layer, with certified data products and a semantic layer that defines each measure once. When core trend or member months carry one definition, one formula, and one owner, every report uses the same foundational facts. The measures also need to carry their context. A trend figure should declare its basis, whether paid, incurred, booked, or normalized, and the date as of which it was known, because claims restate for months. Assumptions like trend picks and completion factors belong there, too. Versioned and owned, and model outputs should flow back in with clear lineage. A shared foundation does not remove judgment. It removes the argument about what happened, so the debate leaders hear what is going on and what it means.
Scale AI in actuarial workflows with a strong data foundation
A new actuarial operating model also requires clearer choices about technology and data, especially as use of artificial intelligence (AI) expands. Health plan leaders say they are experimenting with AI in actuarial workflows, including coding assistance, narrative drafting, competitor filing analysis, anomaly detection, and deeper exploration of trend drivers. But none described AI as being fully scaled across core actuarial processes.
That gap is less about the models and more about the foundation underneath them. Each of those use cases depends on AI that is grounded in governed data and standard definitions, so that answers resolve to specific formulas, driver hierarchies, and approved assumptions. The same foundation makes self-service realistic, including conversational interfaces that let leaders query certified data directly, because the definitions and calculations underneath are fixed. Health plans that build the foundation first will find the use cases compound, while plans that skip it will keep accumulating pilots.
For chief actuaries, the near-term priority should be to identify a limited number of valuable use cases, prove them within appropriate enterprise controls, and determine how successful capabilities fit into the broader technology operating model.
How AI is transforming actuarial roles and skills in health plans
The shift to AI and the new operating model also changes what health plans need from their actuaries. As data assembly, reconciliation, and first-draft reporting become automated, actuarial time shifts toward owning assumptions, reviewing exceptions, validating model and AI output, and advising the businesses on what the numbers mean. The embedded roles described above are advisory, and they reward actuaries who can move between deep technical work and executives running each line.
The health plan leaders we interviewed are already building for that range. Most run formal early-career rotation programs, typically involving 18- to 24-month rotations and multiple moves, that produce exactly the mix of technical depth and business fluency upon which the model depends. Hybrid work remains part of the recruiting equation, and some chief actuaries have carved out flexibility for actuaries even where the broader enterprise policy is stricter. Seen this way, rotations and flexibility are operating-model investments rather than perks.
Key actions for chief actuaries to improve the operating model
The chief actuaries we spoke with reinforced the notion that following through on deliberate choices on ownership, governance, and accountability was more critical than finding one universal structure. Here are a few actions organizations can take right away:
- Name an owner for the enterprise trend and make sure major cost components roll up into one coherent narrative for leadership.
- Build a single source-of-truth forecast process, with clear quarterbacks and sign-off steps, even where actuarial and finance both contribute to it.
- Stand up one governed data layer that publishes certified data products, defines each measure once in a semantic layer, and assigns versioned ownership of key assumptions, then points reports, models, and downstream systems at it.
- Centralize where rigor matters most and embed where business relationships matter most — with an explicit rationale for the split.
- Make sure every line of business knows exactly which actuary to call for answers to pricing, trend, and forecasting questions.
- Rationalize the models, data marts, and business-built tools actuaries depend on before redundancy quietly accumulates, and give model outputs a governed home so results carry lineage.
- Match your AI roadmap to a small number of proven use cases — grounded in the governed data layer and inside enterprise guardrails — rather than letting enthusiasm run ahead of adoption.
- Treat flexibility and rotation programs as deliberate talent investments, not perks. The operating model depends on having people who can move between technical work and business-facing roles.
The health plan leaders who make deliberate choices about where expertise and trusted data live, who own critical decisions, understand how teams work across organizational boundaries, and know how actuarial insight reaches the people running the business will be equipped to make decisions when conditions change quickly. For chief actuaries, that is the broader operating-model challenge: preserving the specialized expertise health insurance requires while making it easier for the enterprise to arrive at one view of performance — and act on it.