S&P Global (SPGI) Change in Accrued Expenses (2009 - 2026)
S&P Global (SPGI) reported Change in Accrued Expenses of $243 million for Q2 2026, up 57.8% from $154 million a year earlier.
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Analysis
S&P Global (SPGI) Change in Accrued Expenses (2009 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, S&P Global's Change in Accrued Expenses came in at $66 million, up 34.7% year-over-year; for FY2025, it came in at -$55 million.
- By year, Change in Accrued Expenses came in at $245 million in FY2024 (-25.3%), $328 million in FY2023 (+662.8%), $43 million in FY2022 (+13.2%) and $38 million in FY2021 (-71.2%).
- Five-year quarterly Change in Accrued Expenses spans a low of -$678 million in Q1 2025 and a high of $448 million in Q4 2023.
- Year over year, Change in Accrued Expenses gained in two of the last five quarters, with an average decline of 14.0%.
- The high point for year-over-year Change in Accrued Expenses in five years was Q2 2023 (growth of 657.6%); the low point was Q3 2025 (a decline of 84.3%).
- Per Business Quant data, the three quarters before Q2 2026 came in at -$646 million (Q1 2026), $438 million (Q4 2025) and $31 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accrued Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | S&P Global | 136.60 Bn | 126.45 Bn | 2.64 Bn | 117.00 Mn |
| 2 | Moodys | 87.36 Bn | 80.29 Bn | 1.50 Bn | 70.00 Mn |
| 3 | Msci | 46.52 Bn | 45.00 Bn | 739.80 Mn | 61.60 Mn |
| 4 | Verisk Analytics | 26.51 Bn | 21.15 Bn | 572.90 Mn | 59.70 Mn |
| 5 | Equifax | 22.26 Bn | 21.54 Bn | 940.10 Mn | 78.00 Mn |
| 6 | TransUnion | 15.70 Bn | 12.39 Bn | - | - |
| 7 | Factset Research Systems | 11.87 Bn | 10.72 Bn | 308.40 Mn | 39.76 Mn |
| 8 | Morningstar | 9.12 Bn | 7.01 Bn | 431.40 Mn | 52.00 Mn |
| 9 | Mastercard | 579.47 Bn | 539.56 Bn | - | 872.00 Mn |
| 10 | Cme | 108.68 Bn | 97.01 Bn | - | 306.80 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 117.00 Mn |
| Jun 30, 2026 | 243.00 Mn |
| Mar 31, 2026 | -646.00 Mn |
| Dec 31, 2025 | 432.00 Mn |
| Sep 30, 2025 | 37.00 Mn |
| Jun 30, 2025 | 154.00 Mn |
| Mar 31, 2025 | -678.00 Mn |
| Dec 31, 2024 | 376.00 Mn |
| Sep 30, 2024 | 197.00 Mn |
| Jun 30, 2024 | 274.00 Mn |
| Mar 31, 2024 | -602.00 Mn |
| Dec 31, 2023 | 448.00 Mn |
| Sep 30, 2023 | -27.00 Mn |
| Jun 30, 2023 | 250.00 Mn |
| Mar 31, 2023 | -343.00 Mn |
| Dec 31, 2022 | 425.00 Mn |
| Sep 30, 2022 | -97.00 Mn |
| Jun 30, 2022 | 33.00 Mn |
| Mar 31, 2022 | -318.00 Mn |
| Dec 31, 2021 | 123.00 Mn |
API Access
S&P Global Change in Accrued 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=change-in-accured-expenses&ticker=SPGI&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-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=change-in-accured-expenses&ticker=SPGI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();