Verisk Analytics (VRSK) Return on Sales [ROS] (2010 - 2026)
Verisk Analytics (VRSK) recorded Return on Sales [ROS] of 45.11% in Q2 2026, down 0.75 percentage points from 45.86% a year earlier but up 0.10 percentage points from the prior quarter.
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Analysis
Verisk Analytics (VRSK) Return on Sales [ROS] (2010 - 2026) Analysis & Trends
On a TTM basis, Verisk Analytics' Return on Sales [ROS] came in at 43.86% as of Jun 30, 2026, down 0.08 percentage points year-over-year; for FY2025, it came in at 43.74%, up 0.22 percentage points from FY2024.
- Annual Return on Sales [ROS] has a five-year change of +1.60 percentage points (FY2020 to FY2025).
- Across earlier years, Return on Sales [ROS] came in at 43.51% in FY2024 (+1.31 pp), 42.21% in FY2023 (-14.12 pp), 56.33% in FY2022 (+19.32 pp) and 37.01% in FY2021 (-5.13 pp).
- Quarterly Return on Sales [ROS] has ranged from 36.99% in Q4 2023 to 96.77% in Q1 2022 over the past five years.
- On a year-over-year basis, Return on Sales [ROS] rose in six of the last eight quarters, with an average year-over-year change of +1.10 percentage points.
- Peak year-over-year performance for Return on Sales [ROS] in the last five years was a gain of 62.28 percentage points in Q1 2022, against a drop of 51.63 percentage points in Q1 2023 at the low end.
- Per Business Quant, the preceding three quarters came in at 45.00% (Q1 2026), 40.27% (Q4 2025) and 45.02% (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | ROS (Qtr) |
|---|---|---|---|---|---|
| 1 | S&P Global | 113.90 Bn | 109.50 Bn | 2.98 Bn | 43.70% |
| 2 | Moodys | 76.48 Bn | 68.91 Bn | 1.67 Bn | 47.87% |
| 3 | Msci | 38.99 Bn | 37.33 Bn | 717.10 Mn | 56.23% |
| 4 | Verisk Analytics | 21.33 Bn | 15.96 Bn | 572.90 Mn | 45.11% |
| 5 | Equifax | 16.47 Bn | 15.87 Bn | 926.40 Mn | 18.48% |
| 6 | TransUnion | 12.16 Bn | 9.14 Bn | - | 19.70% |
| 7 | Factset Research Systems | 9.52 Bn | 8.28 Bn | 310.73 Mn | 26.70% |
| 8 | Morningstar | 6.89 Bn | 4.79 Bn | 423.90 Mn | 24.22% |
| 9 | Mastercard | 480.84 Bn | 440.75 Bn | - | 60.22% |
| 10 | Cme | 94.54 Bn | 94.54 Bn | - | 64.89% |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 45.11% |
| Mar 31, 2026 | 45.00% |
| Dec 31, 2025 | 40.27% |
| Sep 30, 2025 | 45.02% |
| Jun 30, 2025 | 45.86% |
| Mar 31, 2025 | 43.84% |
| Dec 31, 2024 | 43.00% |
| Sep 30, 2024 | 42.95% |
| Jun 30, 2024 | 44.46% |
| Mar 31, 2024 | 43.66% |
| Dec 31, 2023 | 36.99% |
| Sep 30, 2023 | 41.48% |
| Jun 30, 2023 | 45.33% |
| Mar 31, 2023 | 45.14% |
| Dec 31, 2022 | 44.81% |
| Sep 30, 2022 | 41.57% |
| Jun 30, 2022 | 40.40% |
| Mar 31, 2022 | 96.77% |
| Dec 31, 2021 | 45.54% |
| Sep 30, 2021 | 38.06% |
API Access
Verisk Analytics Return on Sales [ROS] 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=return-on-sales-%5Bros%5D&ticker=VRSK&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "return-on-sales-[ros]", "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=return-on-sales-%5Bros%5D&ticker=VRSK&period=max&api_key=YOUR_API_KEY");
const data = await res.json();