Morningstar (MORN) Change in Accrued Expenses (2009 - 2026)
Morningstar (MORN) reported Change in Accrued Expenses of $52 million for Q3 2026, down 2.6% from $53.4 million a year earlier but up 28.1% from the prior quarter.
Morningstar (MORN) Change in Accrued Expenses (2009 - 2026) Analysis & Trends
Over the twelve months ended Sep 30, 2026, Morningstar's Change in Accrued Expenses came in at $16.2 million, down 55.2% year-over-year; for FY2025, it was $37.7 million, down 51.0% from FY2024.
- Change in Accrued Expenses has a five-year compound annual growth rate of 15.7% (FY2020 to FY2025).
- By year, Change in Accrued Expenses came in at $76.9 million in FY2024 (+416.1%), $14.9 million in FY2023, -$37.5 million in FY2022 and $58 million in FY2021 (+218.7%).
- Five-year quarterly Change in Accrued Expenses spans a low of -$138.7 million in Q1 2026 and a high of $62.3 million in Q4 2025.
- Year over year, Change in Accrued Expenses gained in three of the last six quarters, with growth averaging 12.8%.
- The high point for year-over-year Change in Accrued Expenses in five years was Q2 2023 (growth of 594.9%); the low point was Q2 2022 (a decline of 82.4%).
- Per Business Quant data, the three quarters before Q3 2026 came in at $40.6 million (Q2 2026), -$138.7 million (Q1 2026) and $62.3 million (Q4 2025).
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
| Date | Value |
|---|---|
| Sep 30, 2026 | 52.00 Mn |
| Jun 30, 2026 | 40.60 Mn |
| Mar 31, 2026 | -138.70 Mn |
| Dec 31, 2025 | 62.30 Mn |
| Sep 30, 2025 | 53.40 Mn |
| Jun 30, 2025 | 42.50 Mn |
| Mar 31, 2025 | -120.50 Mn |
| Dec 31, 2024 | 60.80 Mn |
| Sep 30, 2024 | 47.70 Mn |
| Jun 30, 2024 | 47.60 Mn |
| Mar 31, 2024 | -79.20 Mn |
| Dec 31, 2023 | 33.70 Mn |
| Sep 30, 2023 | 15.40 Mn |
| Jun 30, 2023 | 41.00 Mn |
| Mar 31, 2023 | -75.20 Mn |
| Dec 31, 2022 | 18.10 Mn |
| Sep 30, 2022 | 47.20 Mn |
| Jun 30, 2022 | 5.90 Mn |
| Mar 31, 2022 | -108.70 Mn |
| Dec 31, 2021 | 49.50 Mn |
Morningstar 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=MORN&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "ticker": "MORN", "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=MORN&period=max&api_key=YOUR_API_KEY");
const data = await res.json();