Ask any insurance executive if they’re fully satisfied with their pricing function, and odds are you’ll get a thoughtful pause — followed by a list of frustrations.
It's not that pricing models are inaccurate or the math is flawed. In fact, insurance as a field has developed an impressive science of risk prediction over the decades. The real issue isn’t the science of pricing. It’s the process.
At its core, insurance pricing is an attempt to predict the future. When an insurer sells a policy, they’re committing to cover potential costs — some of which may be minor, others catastrophic, and some that may never arise at all. To manage this uncertainty, insurers rely on risk pooling and statistical modeling. But it’s not the inherent unpredictability of risk that makes pricing hard — it’s how pricing is operationalized inside the organization.
In this three-part blog series, we’ll unpack the core challenges that make insurance pricing one of the most persistent headaches in the industry — and discuss strategies to overcome them. This first installment focuses on the foundational issue: the misalignment between the key stakeholders who own, build, and inform pricing decisions — and how these disconnects undermine speed, accuracy, and adaptability.
The Stakeholders of Insurance Pricing
Insurance pricing can be considered to involve three primary stakeholder groups:
- Business owners – These include Chief Underwriting Officers, product owners, and heads of operations — the profit-and-loss leaders. They define the strategy, manage overall performance, and ultimately decide what prices to charge.
- IT professionals – These are the teams that maintain the systems that power daily operations, including the rating engines that calculate premiums.
- Analytics teams – These include the actuaries and data scientists who extract insights from data to recommend appropriate, risk-based rates.
Each of these teams plays a vital role — but each also operates with different mandates, tools, and timelines. Without thoughtful coordination, they can easily work at cross-purposes.
The Real Challenge: Process, Not Prediction
Here’s the crux: Insurance pricing doesn’t fail because teams don’t understand risk. It fails because the process is fragmented. Business, IT, and analytics often work in silos, with different goals, technical languages, and workflows. As a result, it’s not uncommon for companies to struggle with:
- Long delays in updating rates, despite having accurate models.
- Miscommunications that lead to rejected or misapplied pricing recommendations.
- Outdated or incompatible systems that slow down analysis or rate deployment.
Even the most brilliant actuarial model is worthless if it can’t be understood, approved, and implemented quickly.
The Disconnect
Part of the disconnect stems from literal differences in “language.” IT teams think in terms of system performance and uptime. Analytics teams speak in terms of models and coefficients. Business owners focus on strategy, competitive position, and outcomes.
What’s needed is not just better systems, but better translation — professionals who can bridge these worlds. An IT analyst who understands the data needs of actuaries. A data scientist who can explain their findings in plain business terms. A product owner who can ask sharp questions and translate strategic goals into actionable pricing changes.
A Way Forward: Integrated, Cross-Functional Applications
To fix this, insurers must shift their focus from individual functions to the intersections between them. That means investing in applications and platforms (1) that connect analytics, IT, and business review; (2) allow for the seamless translation of model outputs into production-ready rates; (3) enable quick iteration and decision-making based on current data; and (4) support direct collaboration between teams rather than relying on siloed workflows.
There’s no fundamental technological barrier to building the optimal pricing system. What’s needed is a clear appreciation for how deep the disconnects run — and a commitment to addressing them head-on.
Most pricing functions don’t falter or fail because they lack talent or tools, but because those assets are fragmented across disconnected systems and processes. When pricing is treated as a continuous, cross-functional effort — rather than a handoff between departments — insurers gain the speed and adaptability needed to compete in dynamic markets.
This shift isn’t just about efficiency. It’s about building a pricing function that is strategic, scalable, and adaptable. One that can respond to changing market conditions, maintain competitiveness, and empower every stakeholder — from actuary to underwriter to executive — to play their role without friction.
That’s the vision we should be working toward: a modern, aligned, and forward-looking pricing operation.
Coming Up Next
In the next installment (Part 2), we’ll take the first step toward transformation by diagnosing where your pricing function may be falling short — and how to start charting a path forward. We’ll introduce a practical framework to help you identify what’s working, what’s lagging, and where targeted improvements can make the biggest impact.
Then in Part 3, we’ll shift from diagnosis to solution — exploring the applications, teams, and technologies that can close the gaps between business, IT, and analytics, and help build a more responsive, integrated pricing operation.
Stay tuned!