When Did Rate Management Get So Complicated to Manage?
It did not happen overnight. For decades, rating processes were simpler by necessity: fewer variables were available, no telematics or aerial imagery, no vast array of vended data. Spreadsheets were the right tool for the job.
Then the job changed.
Data sources multiplied, multivariate models allowed actuaries to incorporate a huge amount of information, and the complexity of rating algorithms scaled faster than the infrastructure used to manage them. But rather than modernizing their systems, most carriers patched what they had.
Time to market for insurance product development remains "slow and unwieldy" due to legacy infrastructure, functional silos, and long-entrenched processes that were never designed for today's pace of change. A joint PwC and Ignatica report puts a concrete number to it: on legacy systems, developing and testing a new product takes on average 6 to 9 months and costs between US$400,000 and US$900,000. Meanwhile, 70% of IT budgets are consumed by maintaining existing legacy infrastructure, leaving little room to invest in what comes next.
The result is a rate management process built on layers of workarounds: spreadsheets for analysis, separate rating engines for production, IT teams for implementation, and shared drives for documentation. The connections between those tools are where errors accumulate, decisions slow down, and risk quietly builds.
3 Signs Your Insurance Rate Management Process Is Working Against You
Pain Point 1: Rates Live Everywhere, Which Means They Live Nowhere
Ask three people in your organization what the current rate is for a given state, coverage tier, or peril. You will likely get three different answers, each pointing to a different file, a different version, or a different system.
This is the single source of truth problem, and it is more costly than it appears.
Without a centralized, versioned rate management system, pricing teams face:
- Version chaos: Multiple copies of rating algorithms circulating across teams, with no clear record of which is live, which is filed, and which is outdated
- Reconciliation overhead: Before any rate review, hours or days are spent just assembling a coherent picture of where rates currently stand
- Shadow systems: Teams build local workarounds to adjust for state specific changes, making fragmentation worse over time
- Stakeholder misalignment: When finance, underwriting, and pricing pull different numbers, decisions stall
Rate changes are cascaded from countrywide models to states, but then each state may deviate. A change in one factor is likely not adopted across all states and tiers - only most of them. Without a centralized source of truth, there is no safe way to confirm what changed, when it changed, and who it affected.
Pain Point 2: Running a Rate Scenario Takes Days, Not Hours
When pricing teams need to assess the portfolio impact of a rate change, they should be able to answer this question quickly: what happens to our book if we change three factors and take an overall indication of 5%?
In most organizations today, that question triggers a multi-day process of pulling data and feeding current and proposed rating algorithms into an Excel or Python rater built by actuaries to replicate the rating engine as closely as possible. Debugging and troubleshooting these tools and the process takes days. At least one of your actuaries knows someone who put a sticky note on a laptop saying “DO NOT CLOSE” as the VBA macro ran one re-rating scenario for 12-48 hours.
The data confirms how deep this problem runs. According to PwC's Global Actuarial Modernization Survey 2025, actuaries currently spend more than half of their time on data preparation, far from the target of under 25%, and more on high-value analysis. The same survey found that 94% of insurers cite process efficiency as their primary driver for modernization, yet the average self-assessed automation maturity score across the industry sits at just 2.5 out of 5.
The challenge is not only preparing the data. Each scenario also requires the portfolio to be rerated with varying changes to highly complex rating algorithms. These rerated results then feed analyses of premium impact, retention, portfolio mix, and profitability. Every pricing change can therefore create a new chain of work: rerating the portfolio, validating the results, rerunning the analyses, and tracking which version of the rates was used. When this process takes hours or days, pricing teams cannot test enough scenarios to respond quickly to market changes.
The business consequence is direct: pricing teams cannot react to market shifts in real time. Rate reviews happen less often than they should. And when they do happen, they are based on a picture of the portfolio that is already out of date.
Pain Point 3: You’re Constantly Putting Out Spreadsheet Fires
In most insurance organizations today, rates are still managed through spreadsheets and hard-coded logic that was never designed for the scale or complexity of modern ratemaking. The problem is not that teams are careless. The problem is that spreadsheets are structurally prone to error at scale.
The research on this is unambiguous. According to the European Spreadsheet Risk Interest Group (EuSpRIG), which coordinates and publishes the largest body of academic research on spreadsheet risk:
- More than 90% of spreadsheets in active business use contain errors
- Approximately 50% of spreadsheet models used operationally in large businesses contain material defects, meaning errors significant enough to affect decisions
- 50% of executives surveyed reported encountering spreadsheet-related problems serious enough to result in staff dismissal
In insurance pricing, where a single miscalculated factor can cascade across thousands of policies, multiple states, and multiple distribution channels, a 50% rate of material defects is not an abstract statistic. It is a live risk sitting inside your rating process.
Beyond accuracy, there is a competitive cost. Every manual correction, every reconciliation cycle, and every version mismatch slows down the rate review process, delays filings, and pulls pricing talent away from the strategic work that actually moves the needle.
“It’s Complicated” Is Not a Rate Management Strategy
Three pain points. One diagnosis: a rate management process built on tools never designed for the job. "It's complicated" should describe your pricing algorithm. Not your ability to manage them.
Fixing rate management does not mean rebuilding your entire technology stack. It means replacing the weakest link in your process: the absence of a structured, centralized system where your rate logic actually lives.
In practice, that means three things. First, a single, versioned repository where every rate structure is documented, traceable, and accessible to the teams that need it, eliminating the version chaos and shadow systems that slow every decision downstream. Second, the ability to run re-rating and scenario analysis directly against that repository, so assessing the portfolio impact of a rate change takes hours, not days. Third, a built-in audit trail that records every change, every version, and every decision, so that compliance and filing preparation are a function of good process rather than a last-minute scramble. Find out how Akur8 Rate Repo helps make this possible.
