The commercial insurance market posted its best underwriting results in over a decade in 2024. According to S&P Global Market Intelligence, the industry’s aggregated commercial lines net combined ratio, a measure that combines claims paid out and operating costs as a percentage of premiums collected, came in at 96.3% in 2024. By most measures, this should be a moment of confidence.
And yet, the gap between top-performing carriers and the rest of the market continues to widen. The difference rarely comes down to which lines a carrier writes. According to McKinsey’s Global Insurance Report, while 40% of an insurer’s performance is driven by the lines of business it participates in, 60% is driven by how it operates.
That finding has real implications for insurance leadership across commercial lines. Portfolio selection matters, but execution is where the performance gap actually opens up.
McKinsey’s analysis of top-performing commercial insurers identified four areas of distinctiveness that drive superior performance:
The operational lever that shows up most consistently is speed and quality of intake handling. Whether submissions come through brokers, benefits consultants, or directly from employers and corporate buyers, the dynamic is the same: the carriers that respond fastest with relevant, well-reasoned terms earn preferred placement. With consolidation among brokerages, brokers are looking to coordinate segments of their book to place with a select panel of insurers, which requires carriers to be able to analyze large volumes of data at pace. Being on that select panel is not just a relationship outcome. It is an operational one.
Leading carriers build data-driven analytics to inform their broker and consultant relationships, including where to shift volumes and how to optimize the quality of business they are pursuing. How well a carrier manages those relationships determines the quality of the submission flow coming in the door.
In other words, the carriers that brokers and consultants call first are the ones that respond fastest with the most relevant terms. That is not a coincidence. It is a capability.
Most underwriting and case management teams are not slow because their people are slow. They are slow because the information they need to make a decision is spread across systems that do not talk to each other. A submission arrives. A team member manually pulls relevant data, cross-references guidelines, and rebuilds context that should already exist in one place.
This is not a people problem. It is an infrastructure problem. And it is one of the primary reasons AI initiatives in insurance stall before they deliver results: the underlying data is too fragmented to act on quickly, and consolidating it first requires a migration project that takes years.
According to McKinsey, early AI use cases are already improving efficiency and conversion across the broker-carrier relationship, including automated submission ingestion and intake processing. The value of AI in this context is not in replacing judgment. It is in giving experienced teams better information, faster, so their judgment can be applied where it matters.
There is also a customer experience dimension that goes beyond broker relationships. Faster response times and smoother intake directly affect renewal retention and how policyholders, employers, and plan members experience working with a carrier. Speed is not just a competitive advantage at the point of sale. It compounds over the life of the relationship.
Kamiwaza connects to data where it already lives, whether structured or unstructured, without requiring migration or consolidation. For underwriting and case management teams, that means incoming submissions are read, structured, and scored against guidelines automatically. High-priority accounts route to the right people. Lower-priority work is triaged accordingly.
Kamiwaza was built to address exactly this kind of bottleneck. Healthbus, an integrated healthcare benefits platform serving small and mid-size employers, came to Kamiwaza with a familiar problem: their manual quote generation process required 3 to 4 days per case and an average of five separate client interactions to gather correct documentation, a constraint that limited their ability to pursue smaller market opportunities and raised customer acquisition costs. After implementing Kamiwaza, quote generation moved to real-time processing, enabling immediate response to prospect inquiries, eliminating the documentation back-and-forth, and creating measurable competitive differentiation in their market.
The goal is not to automate judgment. It is to make sure that judgment is applied to the right submissions and cases, at the right moment, with the right information already assembled.
That is the operational difference that separates the carriers brokers call first from the ones they call fifth.
Ready to see how Kamiwaza enables this in your environment? Let’s talk.