The real reinsurance shift isn’t rates, it’s pricing infrastructure: Hiscox Re

Across a typical renewal season, tens of thousands of submission emails land in a reinsurer’s inbox. That operational reality, rather than headline rate movements, is where much of the industry’s recent transformation is taking place.

That is according to Minesh Shah (pictured), director of underwriting risk at Hiscox Re, who told Bermuda:Re+ILS  ahead of the Bermuda Risk Summit 2026, hosted by the Business Development Agency Bermuda on 9-11 March, that the evolution of pricing over the past five years is as much about workflow and data architecture as about market cycles.

“We have seen pricing shift as the market absorbed the impacts of multiple factors, including geopolitical tension, inflation and elevated catastrophe activity,” he said. Those drivers are well understood in Bermuda. “But the quieter story is the evolution of pricing models and infrastructure.”

For decades, property catastrophe modelling has been the analytical backbone of the market. But Shah believes the gap between cat and non-cat sophistication is narrowing: “Property cat modelling has long been sophisticated, but in the past five years, non-cat pricing has been quickly catching up.”

The shift is structural. “New platforms are replacing spreadsheets, allowing reinsurers to analyse entire portfolios, stress test assumptions and spot market outliers in ways that simply weren’t possible before.” That evolution moves pricing from a treaty-by-treaty exercise toward something more dynamic and portfolio-aware. It also changes internal decision-making, enabling underwriters, actuaries and modelling teams to interrogate risk across cedants, geographies and product lines with greater speed.

The continued rise of cyber

Nowhere is this evolution clearer than in cyber reinsurance, Shah pointed out: “Cyber is a product line characterised by fast growth, limited historical data, systemic exposure and a rapidly changing claims environment.” He noted that “industry-wide data sets remain relatively sparse at the cedant level”, making benchmarking and loss trend analysis challenging for individual carriers.

Market-wide visibility, however, is altering that picture. “At Hiscox Re, we see granular submission data covering more than 70% of the market. That gives us a far broader view of market dynamics than any single cedant would typically have.” The ability to interrogate that data by cedant, geography, industry segment or portfolio characteristics enables a more nuanced pricing approach. Shah explained that this allows Hiscox Re “to benchmark cedants against the wider market, identify where loss experience is shifting and price individual deals with much greater insight than would ever be possible using a standalone data set”.

These implications extend beyond cyber. As portfolio-level data becomes richer and more structured, reinsurers can better understand correlations, emerging patterns and concentrations that would otherwise remain opaque. The maturation of data infrastructure builds efficiency and confidence in risk selection.

That confidence becomes particularly important as rate pressure builds. Shah was quick to assert that Hiscox Re responds to rate pressure by maintaining discipline in cedant selection and reinforcing relationships where there is strong alignment. At the same time, the firm has reduced exposure in areas where pricing no longer reflects the risk while reviewing and pricing more deals across the market. His strategy is “casting the net wider to identify well-rated treaties and opportunities”.

Discipline, in this context, is not about shrinking appetite; it is about sharper filtration. Portfolio analytics and broader submission visibility make it possible to differentiate more precisely between risk that merits support and risk that does not.

The role of AI

Alongside pricing evolution sits another theme dominating industry discussion: artificial intelligence. Here, Shah offered a pragmatic assessment.

Across a typical renewal season, Shah explained that Hiscox Re’s submissions inbox receives tens of thousands of emails, “which include new submissions, firm order terms, signed lines and general updates. Historically, operations teams spent significant time sorting and routing these to the right underwriters or pricing teams”.

Shah explained: “At Hiscox Re, we have a strong foundation of technical underwriting and are in the first stages of a multi-phase upgrade of our underwriting workflow, which uses AI to streamline the more time-consuming operational tasks. One area where we’ve seen early success is in managing incoming submissions.”

Now, AI tools automate much of that administrative triage. The result is “faster responses and more time for our teams to focus on the work that requires shrewd judgment – such as underwriting decisions and portfolio analysis”, Shah said.

Shah made a deliberate distinction: “Crucially, AI is not making underwriting decisions, rather it is helping us process the volume of information more efficiently. We are not positioning AI as a tool to influence decision-making or strategy.” Instead, it is being deployed to “speed up workflows, improve consistency and free people to focus on the judgment-based work our cedants rely on”.

Hiscox is experiencing measurable operational impact as a result: “Our property cat team modelled and priced 20% more deals than the prior year, and we expanded our cedant list by over 50% in our property per risk portfolio.” Efficiency gains have allowed the team to review more opportunities without diluting analytical scrutiny.

Addressing data gaps

Yet even with stronger data and enhanced workflow, uncertainty remains a defining feature of reinsurance – particularly in areas where historical information is thin.

“When data is limited, we lean on disciplined underwriting principles that are well established across the reinsurance market,” Shah says. That includes stress-testing assumptions, assessing a wide range of plausible outcomes and structuring deals “in a way that naturally limits downside – whether through capacity limits, attachment points, or ensuring appropriate risk sharing.”

Hiscox Re has also “developed internal tools that quantify how sensitive the technical price is to parameter uncertainty. A capability that is particularly valuable for per-risk and aggregate treaties where data sets can be thinner or more variable”. Rather than relying solely on point estimates, this approach acknowledges and quantifies uncertainty itself.

Balancing analytics with experience remains central. Shah explained that: “Our underwriters, pricing actuaries and catastrophe modelling analysts work side-by-side to ensure that every underwriting decision benefits from a blend of technical analysis and frontline expertise. When the data is compelling, it meaningfully shapes the outcome, but it is always part of a collaborative process that brings experience, judgment and quantitative insight together.”

Looking ahead, the next phase of impact will come from deeper interrogation of complex data sets rather than headline automation. As a reinsurer with visibility across multiple lines and geographies, Shah believes the opportunity lies in “extracting deeper insight, particularly across portfolio interactions and emerging loss patterns”. Investments in new platforms and high-quality external data will enhance “the speed and depth of our insight, rather than simply automating workflows”.

Sophisticated systems, disciplined underwriting

Taken together, these themes point to an industry that is evolving beneath the surface. Pricing levels may fluctuate with the cycle, but the mechanisms that produce those prices are becoming more sophisticated and more integrated.

The next phase might be defined more quietly by how effectively reinsurers translate data into disciplined, defensible underwriting decisions.

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