From tracking Verisk’s quarterly disclosures across four consecutive earnings cycles, the governance friction language on the April 29, 2026 call was new. CEO Lee Shavel explicitly flagged that intellectual property, privacy, and compliance negotiations are extending the contracting timeline for Verisk’s most advanced data and analytics products. This is not a demand problem. Verisk beat estimates on both the top and bottom line, subscription revenues grew 7%, and the company won a competitive RFP to co-develop a digitally native underwriting entity for a global insurer. The friction is structural: as AI products move from proof-of-concept demonstrations to production-grade deployments, the legal and governance infrastructure required to close deals has not kept pace with the technology itself. For actuaries and insurance technologists watching the vendor ecosystem, this is a leading indicator that the insurer AI deployment timeline may extend well into 2027, even as the underlying demand accelerates.

Q1 2026 financial results: the numbers behind the beat

Verisk reported consolidated revenue of $782.6 million for Q1 2026, up 3.9% year-over-year from $753.0 million in Q1 2025. On an organic constant currency (OCC) basis, revenue growth was 4.7%. Adjusted earnings per share came in at $1.82, beating the consensus estimate of $1.74 by 4.6%. Net income rose 1% to $234 million, while diluted GAAP EPS grew 5% to $1.73.

The headline growth story is subscription revenue. Subscription revenues now comprise 84% of total revenue and grew 7% on an OCC basis in Q1 2026. This mix shift has been deliberate: Verisk has spent years migrating clients from transactional, usage-based pricing to recurring subscription contracts that produce more predictable revenue streams and higher customer lifetime value. For actuaries evaluating Verisk as a counterparty or vendor, the 84% subscription mix signals durable revenue that is unlikely to fluctuate with catastrophe event volumes or claim count variability.

Transactional revenues, which made up the remaining 16% of the revenue base, declined 6.1% on an OCC basis. Management attributed this to lower volumes in property and restoration solutions, driven by unusually low weather activity in Q1 2026 compared to Q1 2025, which benefited from claims activity associated with Hurricanes Helene and Milton. The transactional decline was anticipated and does not reflect a competitive loss.

Metric Q1 2026 Q1 2025 Change
Total Revenue $782.6M $753.0M +3.9%
OCC Revenue Growth 4.7% – –
Subscription Revenue Growth (OCC) 7.0% – –
Transactional Revenue Growth (OCC) −6.1% – –
Adjusted EPS $1.82 $1.73 +5.2%
Adjusted EBITDA $436.0M – +5.9% OCC
Adjusted EBITDA Margin 55.9% 55.3% +60 bps

Adjusted EBITDA grew 5.9% on an OCC basis, with the adjusted EBITDA margin expanding 60 basis points to 55.9%. This margin expansion reflects cost discipline and operational leverage, partially offset by continued investment in AI and technology development. The company reaffirmed full-year 2026 guidance: revenue of $3.19 billion to $3.24 billion, adjusted EBITDA of $1.79 billion to $1.83 billion, EBITDA margins of 56% to 56.5%, and adjusted EPS of $7.45 to $7.75.

Segment performance: underwriting leads, claims recovers

Verisk operates through two primary business segments: Underwriting Solutions and Claims Solutions. In Q1 2026, the underwriting segment grew 5.3% on an OCC basis, demonstrating broad-based expansion across forms, rules, loss costs, and advanced analytics. The claims segment grew 3.4% on an OCC basis, recovering from the transactional drag that weighed on property and restoration volumes.

The underwriting segment’s growth is particularly notable because it reflects the ongoing benefit of the Core Lines Reimagine initiative. Verisk shipped seven new client-facing modules in Q1 2026, bringing digitized data, enhanced analytics, and AI-powered productivity tools to the forms, rules, and loss costs business that has long been the company’s core franchise. Management targets 25 total module releases for full-year 2026. From a retention standpoint, Core Lines Reimagine is driving longer contract terms and improved pricing within the base business, a structural tailwind that compounds subscription revenue growth.

The initiative is architecturally significant for actuaries. Core Lines Reimagine digitizes the underlying regulatory and actuarial data that carriers consume through ISO products, transforming static reference materials into machine-readable, API-accessible data assets. When an actuary building a pricing model can pull ISO loss costs, classification codes, and endorsement definitions through an API rather than manual lookups, the productivity gain compounds across every renewal cycle.

The AI governance friction: what Shavel actually said

The most consequential disclosure on the Q1 2026 call was not about the financial results themselves. It was about what is happening in the contracting process for Verisk’s advanced AI products. CEO Lee Shavel described an “additional complexity in negotiating and adapting our contracts” related to intellectual property, privacy, and AI governance provisions. He emphasized that the extended sales cycles are not a signal of weakening demand but rather a reflection of the growing scope and strategic importance of the products being negotiated.

Shavel noted that Verisk is “having to spend some more time working our way through these issues” and expects the friction to improve as industry standards for AI governance contracting mature. This is a critical distinction: the bottleneck is in the legal and compliance review process, not in the technology evaluation or business case approval stages of the sales cycle.

To understand why this matters beyond Verisk’s own P&L, consider the mechanics of how an insurer procures an AI-powered analytics product in 2026. The technical evaluation (does the model work, does it integrate with our systems, does it improve our loss ratio) is often the fastest stage of the process. What follows is a multi-party review involving:

  • Legal: Intellectual property ownership of model outputs, data rights, indemnification for algorithmic errors, and liability allocation for AI-generated decisions
  • Compliance: Alignment with state-level AI regulations (Colorado AI Act, the NAIC model bulletin, emerging model law provisions), particularly unfair discrimination testing and documentation requirements
  • Privacy: Data usage rights, cross-carrier data sharing restrictions, GDPR-equivalent domestic requirements, and consumer consent frameworks for AI-processed personal data
  • Risk management: Model risk governance under ASOP No. 56, explainability requirements, audit trail provisions, and the carrier’s own AI governance framework
  • Procurement: Contract terms that were boilerplate for traditional data subscriptions now require bespoke negotiation for AI products

Each of these review functions operates on its own timeline with its own approval chain. When Shavel describes extended sales cycles, he is describing the cascading effect of five or more independent governance functions evaluating AI-specific contract provisions that did not exist two years ago. This is a systemic phenomenon, not a Verisk-specific commercial challenge.

AM Best data: the readiness gap that amplifies the friction

The governance friction Verisk described does not exist in a vacuum. It intersects with a broader insurer readiness problem documented by AM Best in a segment report published in early 2026. The report, titled “Artificial Intelligence Appears to Be Ready, But Most Insurers Are Not,” surveyed more than 150 rated insurers and managing general agents holding a Best’s Performance Assessment.

The findings are stark. While nearly 60% of respondents expect AI to significantly transform their business models within one to three years, only 41% reported that their organizations are actively using AI across core business areas. Fewer than 20% agreed that their organizations have reached an advanced implementation stage. Two-thirds plan to increase AI investment over the next 12 to 24 months, but the gap between investment intent and operational maturity remains wide.

The report identified the top obstacles to AI implementation: data readiness and quality, security and privacy concerns (43%), and legacy system integration (41%). Legacy systems present “significant barriers” because they “simply were not built for this type of data integration” and “store data in inconsistent formats lacking standardization,” according to the report.

This data readiness deficit directly amplifies the governance friction Verisk described. Carriers with poorly governed data environments face longer AI contract negotiations because every data-sharing provision requires additional diligence. If the insurer cannot document exactly what data feeds into the vendor’s model, how that data is governed, and what consent frameworks apply, the compliance review stalls. Verisk’s structured-data moat, built over decades of industry data collection and standardization, positions it to navigate this better than most vendors. But even Verisk cannot compress a carrier’s internal compliance review timeline.

The agentic co-development win: Verisk as underwriting co-builder

Against this governance headwind, Verisk disclosed one of its most strategically significant wins. The company was selected through a competitive RFP process as the strategic partner for a global insurer building a “next-generation digitally native underwriting entity.” This is not a software license deal or a data subscription renewal. Verisk will contribute its data, actuarial capabilities, and AI-driven platforms to co-develop the operating model for an entirely new underwriting operation.

Management described this as a reflection of Verisk’s multiyear investment in “agentic technologies,” defined on the call as AI systems that can act autonomously or semi-autonomously to perform tasks traditionally reserved for human decision-makers in underwriting processes. The co-development model represents a fundamental shift in Verisk’s commercial relationship with carriers, moving from data provider to embedded technology partner.

For actuaries, this matters in two ways. First, it signals that at least one major global insurer has decided to build its next underwriting platform with vendor-embedded AI rather than developing proprietary systems in-house. The build-versus-buy calculus is tipping toward “co-build” as the preferred model for carriers that lack the internal AI engineering talent to build from scratch but have the actuarial domain expertise to shape the product design. Second, it raises questions about model governance when the actuary signing the opinion sits inside a carrier whose underwriting model was co-developed with an external vendor. ASOP No. 56 places responsibility on the actuary for understanding the model, but co-development arrangements can blur the line between vendor-provided and internally developed components.

The augmented underwriting pipeline is also growing. Verisk reported over 20 follow-up meetings scheduled related to augmented underwriting solutions, indicating robust client interest in AI-assisted risk selection and pricing tools. This is the demand signal that makes the governance friction noteworthy: carriers want these products, are actively evaluating them, and are held up in the contracting stage rather than the evaluation stage.

Digital Media Forensics: the AI product that sells through fraud pressure

While governance negotiations extend timelines for Verisk’s underwriting AI products, one AI-powered solution is experiencing rapid adoption without the same friction: Digital Media Forensics. In Q1 2026, Verisk onboarded its sixth top-10 carrier onto the platform, which uses AI algorithms to detect manipulated images, deepfakes, reused photos, and tampered PDFs submitted with insurance claims.

The urgency behind this adoption is quantifiable. Verisk’s own 2026 State of Insurance Fraud report found that 98% of insurers agree AI-powered editing tools are fueling an increase in digital insurance fraud. Nearly all surveyed carriers (99%) have encountered manipulated or AI-altered documentation, and 76% said AI-altered claim submissions have become more sophisticated over the past year. The platform cross-references customer-submitted loss photos against a database of more than 150 million images, searching for duplicates, matches from other claims, and internet-sourced images.

Digital Media Forensics illustrates an important distinction in the AI governance dynamic. Fraud detection tools typically face less governance friction than underwriting AI because the regulatory framework is different. Fraud detection is a loss mitigation function with well-established legal precedent. Carriers are not making coverage or pricing decisions based on the output; they are identifying potentially fraudulent claims for investigation. The IP, privacy, and compliance review is simpler because the use case is narrower and the regulatory risk is lower. This contrast helps explain why Verisk can report rapid fraud detection adoption alongside extended sales cycles for underwriting analytics.

Core Lines Reimagine: the subscription revenue engine

The seven modules shipped in Q1 2026 bring the Core Lines Reimagine initiative into its execution phase. Under the leadership of Saurabh Khemka, who was promoted to President of Underwriting Solutions in September 2025 after architecting the initiative, Core Lines Reimagine is transforming Verisk’s forms, rules, and loss costs business from a static reference service into a digitized, AI-enhanced analytics platform.

The initiative uses digitized data and AI to improve client productivity and risk segmentation accuracy. For actuaries at carriers that consume ISO products, the practical impact is a transition from periodic reference data deliveries to continuous, machine-readable data access. This enables more granular pricing segmentation, faster regulatory compliance checks, and more responsive rate change implementations.

The retention and pricing benefits are already visible. Management noted that the forms, rules, and loss costs business is seeing stronger retention rates, extended contract terms, and improved pricing directly attributable to the value delivered through Core Lines Reimagine. When Verisk targets 25 module releases for the full year, it is building a compounding value proposition that raises switching costs for carriers that have integrated these tools into their actuarial workflows.

Capital allocation: the $1.5 billion buyback signal

Verisk initiated a $1.5 billion accelerated share repurchase (ASR) program in February 2026, executed through HSBC Bank USA and Wells Fargo Bank. An additional $126.1 million in open-market buybacks supplemented the ASR. For a company with $3.2 billion in guided revenue, the $1.6 billion in total buyback activity signals management confidence in the durability of the subscription revenue model and the margin trajectory.

The buyback is funded by the combination of strong free cash flow generation and proceeds from the 2023 sale of the Financial Services segment to TransUnion. For insurance company investors and actuaries analyzing Verisk’s counterparty risk profile, the aggressive capital return program confirms that management views its current revenue trajectory as sustainable even through the near-term AI governance headwind on deal timing.

Systemic implications: why governance friction is a leading indicator

Verisk’s disclosure has implications that extend beyond its own commercial pipeline. If the insurance industry’s largest data and analytics vendor is experiencing extended contracting timelines because of AI governance complexity, every vendor in the insurer technology ecosystem is likely facing the same dynamic. The friction compounds across the supply chain:

  • Cat modeling vendors deploying AI-enhanced hazard models face the same IP and data-sharing review processes
  • Claims technology providers using machine learning for reserving or settlement recommendations encounter similar compliance reviews
  • Insurtech startups offering embedded AI products face disproportionate governance friction because they lack the established vendor relationships and contracting precedent that incumbents like Verisk have developed over decades
  • Consulting firms building custom AI solutions for carriers must navigate governance provisions for each engagement rather than amortizing them across a product customer base

The Grant Thornton insurance survey, published on April 30, 2026, provides additional context. The survey found that 44% of insurance executives say governance or compliance challenges have contributed to AI project failure or underperformance. Only 24% are “very confident” they could pass an independent AI governance review within 90 days. These data points suggest that the governance friction is not merely extending sales cycles; it is actively causing project failures at carriers that cannot navigate the compliance requirements.

For actuaries, this translates directly into deployment timelines. If the carrier expected an AI-powered pricing model to be operational by January 2027, and the vendor contract alone takes an additional three to six months to negotiate, the actuarial team’s implementation calendar shifts accordingly. Reserve and pricing assumptions that anticipated AI-driven efficiency gains in specific fiscal years may need to be adjusted to reflect more conservative deployment schedules.

Competitive positioning: Verisk versus the field

Verisk occupies a distinctive position in the insurer vendor ecosystem. Its closest competitors in specific verticals include Guidewire (policy administration and claims), Duck Creek (P&C core systems), RMS/Moody’s (catastrophe modeling), and various insurtech providers targeting narrow use cases. But no competitor matches Verisk’s combination of structured data assets, regulatory data franchise (ISO), and now agentic AI co-development capability.

The AI governance friction may actually strengthen Verisk’s competitive moat over time. Carriers that complete the complex governance negotiations with Verisk are unlikely to repeat that process with a competing vendor for similar functionality. The governance review itself creates switching costs. A carrier that has negotiated AI-specific IP, privacy, and compliance terms with Verisk has a template that extends naturally to additional Verisk products but requires renegotiation for a new vendor relationship.

This dynamic partially explains Verisk’s confidence in reaffirming full-year guidance despite the near-term governance headwind. The deals are not lost; they are delayed. And once the governance framework is established with a carrier, subsequent product additions move through a streamlined process. Shavel explicitly noted this expectation: as industry standards for AI governance mature, he anticipates that process standardization will reduce contracting delays over time.

What this means for actuaries

The practical implications for actuarial professionals span several dimensions:

Vendor management. Actuaries involved in technology procurement should expect AI governance review to add three to six months to contracting timelines for advanced analytics products. Build this into project plans and communicate the timeline reality to senior leadership and regulators who expect rapid AI deployment.

Model governance. Co-development arrangements like the agentic underwriting partnership blur traditional vendor-versus-internal model classification. Actuaries signing opinions on pricing or reserving models that incorporate co-developed components need clear documentation of which model elements were developed by the vendor, which were developed internally, and how model risk governance applies to each component. ASOP No. 56 does not distinguish between vendor and internal models; the actuary’s responsibility is the same regardless of provenance.

Expense assumptions. If AI deployment timelines are extending across the vendor ecosystem, expense ratio improvement projections built into pricing and reserving models may need recalibration. The Morgan Stanley projection of 200 basis points of expense ratio improvement from AI by 2030 assumes a deployment cadence that governance friction is now visibly slowing.

Data quality investment. The AM Best findings that data readiness is the top obstacle to AI implementation reinforce the case for actuarial departments to invest in data governance before, not after, AI procurement. Carriers with clean, well-documented data environments will complete vendor contracting faster because the data provisions in AI contracts are more straightforward to negotiate.

Competitive intelligence. Verisk’s Q1 disclosures provide a window into which AI products are gaining traction. Subscription growth of 7%, the agentic co-development win, six top-10 carriers on Digital Media Forensics, and 20-plus augmented underwriting follow-up meetings collectively signal that the insurer demand curve for AI-powered analytics is steep, even if the delivery timeline is flattening.

Sources

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