Verisk Analytics (VRSK) investor relations material

Business model and core strengths

• Generates over $3.1 billion in annual revenue, with 83% recurring revenue and 95%+ client retention, focused exclusively on insurance.

• Serves all major risk and functional areas for the top 100 US P&C insurers, integrating deeply into underwriting, claims, property repair estimating, and regulatory processes.

• Over 90% of revenue is derived from unique, proprietary data sets and analytics, much of which is contributed directly by clients and not publicly available.

• Collects unique engineering, fire suppression, and building code data, and rates every U.S. fire department, providing critical insights for insurers.

• Offers a broad suite of solutions across property, casualty, auto, life, and specialty insurance segments.

Growth drivers and market trends

• Organic revenue growth has consistently ranged from 6%-8%, with a five-year CAGR of 7.9% and resilience during financial crises and the pandemic.

• The US P&C insurance market is projected to grow at a 5% CAGR, with net written premiums rising from $456B to $935B over five years.

• Demand for data and analytics is driven by workflow automation, AI enablement, risk optimization, and regulatory needs.

• Expansion into adjacent markets, such as excess and surplus lines, and new data-driven products are fueling additional growth.

• Macro trends like affordability, climate change, and increased risks are increasing the need for advanced data and analytics.

Competitive advantages and innovation

• Trusted, mission-critical partner with unmatched breadth and quality of data, supporting regulatory filings and underwriting.

• Acts as an innovation hub, enabling industry-wide technology adoption and delivering measurable benefits like faster growth and pricing uplift.

• Integrated AI into over 60 products, with ongoing development of agentic and neuro-symbolic AI platforms in collaboration with clients and a focus on ethical AI and regulatory compliance.

• Data sets are essential for both generative and neuro-symbolic AI, ensuring continued relevance as technology evolves.

• Four structural differentiators: industry centrality, innovation, clear AI strategy, and unique value proposition.