S&P Global (SPGI) Interest Expenses (2009 - 2026)
S&P Global (SPGI) recorded Interest Expenses of $87 million in Q2 2026, up 13.0% from $77 million a year earlier but down 9.4% from the prior quarter.
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Analysis
S&P Global (SPGI) Interest Expenses (2009 - 2026) Analysis & Trends
On a TTM basis, S&P Global's Interest Expenses came in at $316 million as of Jun 30, 2026, up 6.4% year-over-year; for FY2025, it was $287 million, down 3.4% from FY2024.
- Annual Interest Expenses has a five-year compound annual growth rate of 15.3% (FY2020 to FY2025).
- Across earlier years, Interest Expenses came in at $297 million in FY2024 (-11.1%), $334 million in FY2023 (+9.9%), $304 million in FY2022 (+155.5%) and $119 million in FY2021 (-15.6%).
- Quarterly Interest Expenses has ranged from $54 million in Q4 2025 to $96 million in Q1 2026 over the past five years.
- On a year-over-year basis, Interest Expenses rose in three of the last eight quarters, with growth averaging 0.1%.
- Peak year-over-year performance for Interest Expenses in the last five years was growth of 49.1% in Q1 2023, against a decline of 22.9% in Q4 2025 at the low end.
- Per Business Quant, the preceding three quarters came in at $96 million (Q1 2026), $54 million (Q4 2025) and $79 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Int Expense (Qtr) |
|---|---|---|---|---|---|
| 1 | S&P Global | 132.92 Bn | 123.50 Bn | 2.98 Bn | 87.00 Mn |
| 2 | Moodys | 83.17 Bn | 76.10 Bn | 1.50 Bn | - |
| 3 | Msci | 44.28 Bn | 42.77 Bn | 739.80 Mn | 74.80 Mn |
| 4 | Verisk Analytics | 26.25 Bn | 20.89 Bn | 572.90 Mn | 52.80 Mn |
| 5 | Equifax | 21.37 Bn | 20.65 Bn | 940.10 Mn | 62.30 Mn |
| 6 | TransUnion | 15.74 Bn | 12.56 Bn | - | 65.90 Mn |
| 7 | Factset Research Systems | 12.14 Bn | 10.99 Bn | 308.40 Mn | 14.40 Mn |
| 8 | Morningstar | 8.41 Bn | 6.31 Bn | 423.90 Mn | - |
| 9 | Mastercard | 549.82 Bn | 509.75 Bn | - | 218.00 Mn |
| 10 | Cme | 110.07 Bn | 98.17 Bn | - | 43.60 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 87.00 Mn |
| Mar 31, 2026 | 96.00 Mn |
| Dec 31, 2025 | 54.00 Mn |
| Sep 30, 2025 | 79.00 Mn |
| Jun 30, 2025 | 77.00 Mn |
| Mar 31, 2025 | 78.00 Mn |
| Dec 31, 2024 | 70.00 Mn |
| Sep 30, 2024 | 72.00 Mn |
| Jun 30, 2024 | 77.00 Mn |
| Mar 31, 2024 | 78.00 Mn |
| Dec 31, 2023 | 76.00 Mn |
| Sep 30, 2023 | 84.00 Mn |
| Jun 30, 2023 | 88.00 Mn |
| Mar 31, 2023 | 85.00 Mn |
| Dec 31, 2022 | 86.00 Mn |
| Sep 30, 2022 | 71.00 Mn |
| Jun 30, 2022 | 90.00 Mn |
| Mar 31, 2022 | 57.00 Mn |
| Mar 31, 2018 | 34.00 Mn |
| Dec 31, 2017 | 39.00 Mn |
API Access
S&P Global Interest 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=interest-expenses&ticker=SPGI&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "interest-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=interest-expenses&ticker=SPGI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();