Verisk Analytics (VRSK) Capital Expenditures (2009 - 2026)
Verisk Analytics (VRSK) recorded Capital Expenditures of $68.1 million in Q2 2026, up 22.0% from $55.8 million a year earlier and up 6.4% from the prior quarter.
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Analysis
Verisk Analytics (VRSK) Capital Expenditures (2009 - 2026) Analysis & Trends
On a TTM basis, Verisk Analytics' Capital Expenditures came in at $266.7 million as of Jun 30, 2026, up 21.0% year-over-year; for FY2025, it was $244.1 million, up 9.0% from FY2024.
- Annual Capital Expenditures has a five-year compound annual growth rate of -0.2% (FY2020 to FY2025).
- Across earlier years, Capital Expenditures came in at $223.9 million in FY2024 (-2.7%), $230 million in FY2023 (-16.3%), $274.7 million in FY2022 (+2.3%) and $268.4 million in FY2021 (+8.8%).
- The Q2 2026 figure is the highest quarterly Capital Expenditures since Q4 2022.
- On a year-over-year basis, Capital Expenditures has increased for four consecutive quarters, with growth averaging 9.8% over the last eight quarters.
- Peak year-over-year performance for Capital Expenditures in the last five years was growth of 22.0% in Q2 2026, against a decline of 29.4% in Q4 2023 at the low end.
- Per Business Quant, the preceding three quarters came in at $64 million (Q1 2026), $67.2 million (Q4 2025) and $67.4 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Capex (Qtr) |
|---|---|---|---|---|---|
| 1 | Msci | 235.55 Bn | 234.03 Bn | 739.80 Mn | 13.40 Mn |
| 2 | S&P Global | 137.22 Bn | 132.42 Bn | 2.64 Bn | 28.00 Mn |
| 3 | Moodys | 88.04 Bn | 81.11 Bn | 1.50 Bn | 85.00 Mn |
| 4 | Verisk Analytics | 26.17 Bn | 22.36 Bn | 567.00 Mn | 67.20 Mn |
| 5 | Equifax | 22.05 Bn | 21.44 Bn | 940.10 Mn | 123.50 Mn |
| 6 | TransUnion | 15.64 Bn | 12.48 Bn | - | 66.90 Mn |
| 7 | Factset Research Systems | 11.49 Bn | 10.35 Bn | 308.40 Mn | 27.40 Mn |
| 8 | Morningstar | 9.15 Bn | 7.04 Bn | 431.40 Mn | 35.30 Mn |
| 9 | Mastercard | 570.55 Bn | 530.63 Bn | - | 222.00 Mn |
| 10 | Cme | 110.48 Bn | 98.81 Bn | 359.20 Mn | 15.80 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 67.20 Mn |
| Jun 30, 2026 | 68.10 Mn |
| Mar 31, 2026 | 64.00 Mn |
| Dec 31, 2025 | 67.20 Mn |
| Sep 30, 2025 | 67.40 Mn |
| Jun 30, 2025 | 55.80 Mn |
| Mar 31, 2025 | 53.70 Mn |
| Dec 31, 2024 | 55.40 Mn |
| Sep 30, 2024 | 55.50 Mn |
| Jun 30, 2024 | 57.80 Mn |
| Mar 31, 2024 | 55.20 Mn |
| Dec 31, 2023 | 56.30 Mn |
| Sep 30, 2023 | 54.30 Mn |
| Jun 30, 2023 | 58.20 Mn |
| Mar 31, 2023 | 61.20 Mn |
| Dec 31, 2022 | 79.70 Mn |
| Sep 30, 2022 | 65.80 Mn |
| Jun 30, 2022 | 69.20 Mn |
| Mar 31, 2022 | 60.00 Mn |
| Dec 31, 2021 | 85.30 Mn |
API Access
Verisk Analytics Capital Expenditures API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=capital-expenditures&ticker=VRSK&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "capital-expenditures", "ticker": "VRSK", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=capital-expenditures&ticker=VRSK&period=max&api_key=YOUR_API_KEY");
const data = await res.json();