Msci (MSCI) Other Accumulated Expenses (2011 - 2026)
Msci (MSCI) posted Other Accumulated Expenses of $254.1 million for Q2 2026, up 35.1% from $188.14 million a year earlier but down 5.1% from the prior quarter.
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Analysis
Msci (MSCI) Other Accumulated Expenses (2011 - 2026) Analysis & Trends
At the end of FY2025, Msci's Other Accumulated Expenses came in at $265.4 million, up 38.1% from FY2024.
- Annual Other Accumulated Expenses has increased for 14 consecutive years, with a five-year compound annual growth rate of 13.0% (FY2020 to FY2025).
- In prior years, Msci's Other Accumulated Expenses was $192.23 million in FY2024 (+14.2%), $168.28 million in FY2023 (+9.7%), $153.46 million in FY2022 (+5.6%) and $145.3 million in FY2021 (+1.0%).
- Quarterly Other Accumulated Expenses has run from a low of $145.3 million in Q4 2021 to a high of $267.7 million in Q1 2026 over five years.
- On a year-over-year basis, Other Accumulated Expenses has increased in each of the last four quarters, with growth averaging 20.4% over the last eight quarters.
- The strongest year-over-year quarter for Other Accumulated Expenses in the past five years was Q4 2025, with growth of 38.1%; the weakest was Q2 2025, with a decline of 1.3%.
- According to Business Quant data, Other Accumulated Expenses for the three prior quarters was $267.7 million (Q1 2026), $265.4 million (Q4 2025) and $222.58 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | S&P Global | 113.90 Bn | 109.50 Bn | 2.98 Bn |
| 2 | Moodys | 76.48 Bn | 68.91 Bn | 1.67 Bn |
| 3 | Msci | 38.99 Bn | 37.33 Bn | 717.10 Mn |
| 4 | Verisk Analytics | 21.33 Bn | 15.96 Bn | 572.90 Mn |
| 5 | Equifax | 16.47 Bn | 15.87 Bn | 926.40 Mn |
| 6 | TransUnion | 12.16 Bn | 9.14 Bn | - |
| 7 | Factset Research Systems | 9.52 Bn | 8.28 Bn | 310.73 Mn |
| 8 | Morningstar | 6.89 Bn | 4.79 Bn | 423.90 Mn |
| 9 | Mastercard | 480.84 Bn | 440.75 Bn | - |
| 10 | Cme | 94.54 Bn | 94.54 Bn | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 254.10 Mn |
| Mar 31, 2026 | 267.70 Mn |
| Dec 31, 2025 | 265.40 Mn |
| Sep 30, 2025 | 222.58 Mn |
| Jun 30, 2025 | 188.14 Mn |
| Mar 31, 2025 | 208.22 Mn |
| Dec 31, 2024 | 192.23 Mn |
| Sep 30, 2024 | 208.54 Mn |
| Jun 30, 2024 | 190.63 Mn |
| Mar 31, 2024 | 173.63 Mn |
| Dec 31, 2023 | 168.28 Mn |
| Sep 30, 2023 | 171.46 Mn |
| Jun 30, 2023 | 161.00 Mn |
| Mar 31, 2023 | 165.84 Mn |
| Dec 31, 2022 | 153.46 Mn |
| Sep 30, 2022 | 171.48 Mn |
| Jun 30, 2022 | 151.02 Mn |
| Mar 31, 2022 | 160.93 Mn |
| Dec 31, 2021 | 145.30 Mn |
| Sep 30, 2021 | 162.88 Mn |
API Access
Msci Other Accumulated 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=other-accumulated-expenses&ticker=MSCI&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "other-accumulated-expenses", "ticker": "MSCI", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=other-accumulated-expenses&ticker=MSCI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();