VRSK Verisk Analytics
Toll booth on U.S. P&C insurance data; wonderful business, but the price already implies its ~8% growth.
The business
Verisk collects and curates decades of proprietary insurance data (ISO policy forms, loss costs, claims databases, catastrophe models, Xactimate repair estimating) and sells it to P&C insurers mostly on recurring subscriptions. Insurers use it to price, underwrite, file rates with regulators, and settle claims. After selling energy, financial, and marketing units, it is now a pure-play insurance data and analytics company.
Quality gate · 90/100
Moat & management
| Moat | wide moat |
| Source | intangible |
| Trajectory | stable |
| Management | adequate |
ISO forms and loss costs are built into state regulatory filings and insurer workflows, and Xactimate is the industry's shared standard for pricing claims. Both rest on contributory data that gets better as more insurers contribute, so switching costs and data network effects reinforce each other. AI-native challengers and insurer insourcing are worth watching, but replicating 50+ years of pooled statistical data is extremely hard.
Management did well to divest non-core units and return the cash through heavy buybacks (about 3.6%/yr share shrink), and incremental margins are strong. However, the Wood Mackenzie era showed a past taste for empire-building, and the abandoned AccuLynx deal plus buybacks at premium multiples are reasons not to rate them excellent.
Owner-earnings inputs
| Owner earnings (TTM) | 944.90M |
| Owner-earnings yield | 4.3% |
| Free-cash-flow yield | 5.6% |
| Growth used (normalized) | 8.0% |
| Market-implied growth (reverse DCF) | 8.2% |
| Terminal growth | 3.0% |
| Discount rate (hurdle) | 9.0% |
Projected owner earnings
| Yr | Owner earnings | Growth | PV |
|---|---|---|---|
| 1 | 1.02B | 8.0% | 936.23M |
| 2 | 1.10B | 7.6% | 924.57M |
| 3 | 1.18B | 7.3% | 910.03M |
| 4 | 1.26B | 6.9% | 892.74M |
| 5 | 1.34B | 6.6% | 872.85M |
| 6 | 1.43B | 6.2% | 850.54M |
| 7 | 1.51B | 5.9% | 826.02M |
| 8 | 1.59B | 5.5% | 799.49M |
| 9 | 1.67B | 5.1% | 771.20M |
| 10 | 1.76B | 4.8% | 741.38M |
| 11 | 1.83B | 4.4% | 710.29M |
| 12 | 1.91B | 4.1% | 678.17M |
| 13 | 1.98B | 3.7% | 645.29M |
| 14 | 2.04B | 3.4% | 611.88M |
| 15 | 2.11B | 3.0% | 578.20M |
Key risks
- AI and generative tools lowering the cost of building rival analytics or claims-estimating products
- Large-carrier consolidation or insourcing creating pricing pushback on a concentrated customer base
- Regulatory or antitrust scrutiny of ISO's advisory role and pricing power
- Leverage creep from debt-funded buybacks or a return to large acquisitions
Catalysts
- Rising catastrophe losses and severity driving more demand for cat models and claims analytics
- Continued pricing power plus margin expansion and buybacks compounding per-share owner earnings
⚠ maintenance capex ≈ min(capex, D&A), capped at FCF · Price pays for ~8%/yr owner-earnings growth over 15y (reverse DCF); model credits 8%.