Moodys (MCO) Total Current Liabilities (2009 - 2026)
Moodys (MCO) posted Total Current Liabilities of $3.28 billion for Q3 2026, up 31.3% from $2.5 billion a year earlier but down 1.9% from the prior quarter.
Moodys (MCO) Total Current Liabilities (2009 - 2026) Analysis & Trends
At the end of FY2025, Moodys' Total Current Liabilities came in at $2.98 billion, down 17.1% from FY2024.
- Annual Total Current Liabilities shows a five-year compound annual growth rate of 6.1% (FY2020 to FY2025).
- In prior years, Moodys' Total Current Liabilities was $3.6 billion in FY2024 (+43.9%), $2.5 billion in FY2023 (+5.3%), $2.38 billion in FY2022 (-4.8%) and $2.5 billion in FY2021 (+12.3%).
- Quarterly Total Current Liabilities has run from a low of $2.07 billion in Q3 2022 to a high of $3.64 billion in Q1 2026 over five years.
- On a year-over-year basis, Total Current Liabilities has increased in each of the last three quarters, with growth averaging 6.9% over the last eight quarters.
- The strongest year-over-year quarter for Total Current Liabilities in the past five years was Q4 2024, with growth of 43.9%; the weakest was Q3 2022, with a decline of 26.0%.
- According to Business Quant data, Total Current Liabilities for the three prior quarters was $3.35 billion (Q2 2026), $3.64 billion (Q1 2026) and $2.98 billion (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | S&P Global | 136.14 Bn | 125.99 Bn | 2.64 Bn | 8.72 Bn |
| 2 | Moodys | 87.37 Bn | 80.29 Bn | 1.50 Bn | 3.28 Bn |
| 3 | Msci | 46.53 Bn | 45.01 Bn | 739.80 Mn | 1.57 Bn |
| 4 | Verisk Analytics | 25.76 Bn | 20.40 Bn | 572.90 Mn | 1.12 Bn |
| 5 | Equifax | 21.57 Bn | 20.84 Bn | 940.10 Mn | 1.46 Bn |
| 6 | TransUnion | 15.42 Bn | 12.11 Bn | - | 1.08 Bn |
| 7 | Factset Research Systems | 11.51 Bn | 10.36 Bn | 308.40 Mn | 1.09 Bn |
| 8 | Morningstar | 9.02 Bn | 6.91 Bn | 431.40 Mn | 1.02 Bn |
| 9 | Mastercard | 571.76 Bn | 531.85 Bn | - | 24.20 Bn |
| 10 | Cme | 109.34 Bn | 97.67 Bn | - | 156.11 Bn |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 3.28 Bn |
| Jun 30, 2026 | 3.35 Bn |
| Mar 31, 2026 | 3.64 Bn |
| Dec 31, 2025 | 2.98 Bn |
| Sep 30, 2025 | 2.50 Bn |
| Jun 30, 2025 | 2.65 Bn |
| Mar 31, 2025 | 2.92 Bn |
| Dec 31, 2024 | 3.60 Bn |
| Sep 30, 2024 | 3.24 Bn |
| Jun 30, 2024 | 3.22 Bn |
| Mar 31, 2024 | 3.38 Bn |
| Dec 31, 2023 | 2.50 Bn |
| Sep 30, 2023 | 2.27 Bn |
| Jun 30, 2023 | 2.67 Bn |
| Mar 31, 2023 | 2.99 Bn |
| Dec 31, 2022 | 2.38 Bn |
| Sep 30, 2022 | 2.07 Bn |
| Jun 30, 2022 | 2.76 Bn |
| Mar 31, 2022 | 2.99 Bn |
| Dec 31, 2021 | 2.50 Bn |
Moodys Total Current Liabilities 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=total-current-liabilities&ticker=MCO&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-current-liabilities", "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=total-current-liabilities&ticker=MCO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();