Moodys (MCO) Cost of Revenue (2009 - 2026)
Moodys (MCO) posted Cost of Revenue of $518 million for Q2 2026, up 5.9% from $489 million a year earlier but down 2.4% from the prior quarter.
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Analysis
Moodys (MCO) Cost of Revenue (2009 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Cost of Revenue at Moodys was $2.04 billion, up 2.7% year-over-year; for FY2025, it was $1.97 billion, up 1.4% from FY2024.
- Annual Cost of Revenue has increased for three consecutive years, with a five-year compound annual growth rate of 6.0% (FY2020 to FY2025).
- In prior years, Moodys' Cost of Revenue was $1.95 billion in FY2024 (+15.3%), $1.69 billion in FY2023 (+4.6%), $1.61 billion in FY2022 (-1.5%) and $1.64 billion in FY2021 (+11.0%).
- Quarterly Cost of Revenue has run from a low of $393 million in Q2 2022 to a high of $531 million in Q1 2026 over five years.
- On a year-over-year basis, Cost of Revenue has increased in each of the last three quarters, with growth averaging 7.8% over the last eight quarters.
- The strongest year-over-year quarter for Cost of Revenue in the past five years was Q3 2024, with growth of 24.3%; the weakest was Q4 2022, with a decline of 15.5%.
- According to Business Quant data, Cost of Revenue for the three prior quarters was $531 million (Q1 2026), $501 million (Q4 2025) and $492 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Cost of Rev (Qtr) |
|---|---|---|---|---|---|
| 1 | S&P Global | 113.90 Bn | 109.50 Bn | 2.98 Bn | 1.17 Bn |
| 2 | Moodys | 76.48 Bn | 68.91 Bn | 1.67 Bn | 518.00 Mn |
| 3 | Msci | 38.99 Bn | 37.33 Bn | 717.10 Mn | 149.90 Mn |
| 4 | Verisk Analytics | 21.33 Bn | 15.96 Bn | 572.90 Mn | 233.40 Mn |
| 5 | Equifax | 16.47 Bn | 15.87 Bn | 926.40 Mn | 773.70 Mn |
| 6 | TransUnion | 12.16 Bn | 9.14 Bn | - | - |
| 7 | Factset Research Systems | 9.52 Bn | 8.28 Bn | 310.73 Mn | 312.19 Mn |
| 8 | Morningstar | 6.89 Bn | 4.79 Bn | 423.90 Mn | 239.30 Mn |
| 9 | Mastercard | 480.84 Bn | 440.75 Bn | - | - |
| 10 | Cme | 94.54 Bn | 94.54 Bn | - | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 518.00 Mn |
| Mar 31, 2026 | 531.00 Mn |
| Dec 31, 2025 | 501.00 Mn |
| Sep 30, 2025 | 492.00 Mn |
| Jun 30, 2025 | 489.00 Mn |
| Mar 31, 2025 | 491.00 Mn |
| Dec 31, 2024 | 497.00 Mn |
| Sep 30, 2024 | 512.00 Mn |
| Jun 30, 2024 | 469.00 Mn |
| Mar 31, 2024 | 467.00 Mn |
| Dec 31, 2023 | 421.00 Mn |
| Sep 30, 2023 | 412.00 Mn |
| Jun 30, 2023 | 426.00 Mn |
| Mar 31, 2023 | 428.00 Mn |
| Dec 31, 2022 | 410.00 Mn |
| Sep 30, 2022 | 393.00 Mn |
| Jun 30, 2022 | 393.00 Mn |
| Mar 31, 2022 | 417.00 Mn |
| Dec 31, 2021 | 485.00 Mn |
| Sep 30, 2021 | 394.00 Mn |
API Access
Moodys Cost of Revenue 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=cost-of-revenue&ticker=MCO&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "cost-of-revenue", "ticker": "MCO", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=cost-of-revenue&ticker=MCO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();