S&P Global (SPGI) Operating Expenses (2009 - 2026)
S&P Global's Operating Expenses was $2.35 billion in Q2 2026, up 5.7% from $2.22 billion a year earlier and unchanged from the prior quarter.
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Analysis
S&P Global (SPGI) Operating Expenses (2009 - 2026) Analysis & Trends
On a trailing twelve-month basis, S&P Global's Operating Expenses was $9.42 billion through Jun 30, 2026, up 5.5% year-over-year; for FY2025, it came in at $9.16 billion, up 4.9% from FY2024.
- Operating Expenses has now increased for seven consecutive years, with a five-year compound annual growth rate of 19.0% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $8.73 billion in FY2024 (+3.4%), $8.44 billion in FY2023 (+3.4%), $8.16 billion in FY2022 (+99.7%) and $4.09 billion in FY2021 (+6.4%).
- Quarterly Operating Expenses has moved between $1.01 billion (Q3 2021) and $2.51 billion (Q4 2025) over five years.
- Compared with a year earlier, Operating Expenses has increased for 18 straight quarters, with growth averaging 5.3% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was Q2 2022 (growth of 118.3%); the worst was Q4 2021 (a decline of 1.7%).
- Per Business Quant data, SPGI's Operating Expenses in the three quarters before Q2 2026 was $2.34 billion (Q1 2026), $2.51 billion (Q4 2025) and $2.22 billion (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | S&P Global | 116.38 Bn | 111.98 Bn | 2.98 Bn | 2.35 Bn |
| 2 | Moodys | 78.67 Bn | 71.10 Bn | 1.67 Bn | 1.14 Bn |
| 3 | Msci | 39.16 Bn | 37.50 Bn | 717.10 Mn | 379.50 Mn |
| 4 | Verisk Analytics | 21.84 Bn | 16.48 Bn | 572.90 Mn | 442.60 Mn |
| 5 | Equifax | 16.14 Bn | 15.54 Bn | 926.40 Mn | 1.39 Bn |
| 6 | TransUnion | 11.72 Bn | 8.70 Bn | - | 1.05 Bn |
| 7 | Factset Research Systems | 9.66 Bn | 8.43 Bn | 310.73 Mn | 456.62 Mn |
| 8 | Morningstar | 7.13 Bn | 5.03 Bn | 423.90 Mn | 509.40 Mn |
| 9 | Mastercard | 480.27 Bn | 440.19 Bn | - | 3.69 Bn |
| 10 | Cme | 94.12 Bn | 94.12 Bn | - | 599.10 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 2.35 Bn |
| Mar 31, 2026 | 2.34 Bn |
| Dec 31, 2025 | 2.51 Bn |
| Sep 30, 2025 | 2.22 Bn |
| Jun 30, 2025 | 2.22 Bn |
| Mar 31, 2025 | 2.21 Bn |
| Dec 31, 2024 | 2.33 Bn |
| Sep 30, 2024 | 2.17 Bn |
| Jun 30, 2024 | 2.11 Bn |
| Mar 31, 2024 | 2.11 Bn |
| Dec 31, 2023 | 2.26 Bn |
| Sep 30, 2023 | 2.02 Bn |
| Jun 30, 2023 | 2.08 Bn |
| Mar 31, 2023 | 2.08 Bn |
| Dec 31, 2022 | 2.23 Bn |
| Sep 30, 2022 | 2.01 Bn |
| Jun 30, 2022 | 2.08 Bn |
| Mar 31, 2022 | 1.84 Bn |
| Dec 31, 2021 | 1.19 Bn |
| Sep 30, 2021 | 1.01 Bn |
API Access
S&P Global Operating Expenses 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=operating-expenses&ticker=SPGI&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "SPGI", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=SPGI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();