Factset Research Systems (FDS) Change in Receivables (2009 - 2026)
Factset Research Systems (FDS) reported Change in Receivables of -$26.64 million for fiscal Q3 2026 (quarter ended May 31, 2026), compared with -$4.73 million a year earlier.
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Analysis
Factset Research Systems (FDS) Change in Receivables (2009 - 2026) Analysis & Trends
Over the twelve months ended May 31, 2026, Factset Research Systems' Change in Receivables came in at $25.42 million, down 20.8% year-over-year; for FY2025 (ended Aug 31, 2025), it was $42.54 million.
- Change in Receivables has a five-year compound annual growth rate of 37.7% (FY2020 to FY2025).
- By fiscal year, Change in Receivables came in at -$2.2 million in FY2024, $40.1 million in FY2023 (+21.6%), $32.98 million in FY2022 and -$3.65 million in FY2021.
- The fiscal Q3 2026 figure ranks as the lowest quarterly Change in Receivables since fiscal Q3 2024.
- Year over year, Change in Receivables gained in two of the last four quarters, with growth averaging 34.5%.
- The high point for year-over-year Change in Receivables in five years was fiscal Q1 2023 (growth of 348.9%); the low point was fiscal Q1 2024 (a decline of 58.7%).
- Per Business Quant data, the three fiscal quarters before Q3 2026 came in at $31.78 million (Q2 2026), $19.23 million (Q1 2026) and $1.05 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Receivables (Qtr) |
|---|---|---|---|---|---|
| 1 | S&P Global | 116.38 Bn | 111.98 Bn | 2.98 Bn | -39.00 Mn |
| 2 | Moodys | 78.67 Bn | 71.10 Bn | 1.67 Bn | -127.00 Mn |
| 3 | Msci | 39.16 Bn | 37.50 Bn | 717.10 Mn | 2.40 Mn |
| 4 | Verisk Analytics | 21.84 Bn | 16.48 Bn | 572.90 Mn | -151.40 Mn |
| 5 | Equifax | 16.14 Bn | 15.54 Bn | 926.40 Mn | 32.90 Mn |
| 6 | TransUnion | 11.72 Bn | 8.70 Bn | - | 4.90 Mn |
| 7 | Factset Research Systems | 9.66 Bn | 8.43 Bn | 310.73 Mn | -26.64 Mn |
| 8 | Morningstar | 7.13 Bn | 5.03 Bn | 423.90 Mn | -18.60 Mn |
| 9 | Mastercard | 480.27 Bn | 440.19 Bn | - | 338.00 Mn |
| 10 | Cme | 94.12 Bn | 94.12 Bn | - | -182.90 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| May 31, 2026 | -26.64 Mn |
| Feb 28, 2026 | 31.78 Mn |
| Nov 30, 2025 | 19.23 Mn |
| Aug 31, 2025 | 1.05 Mn |
| May 31, 2025 | -4.73 Mn |
| Feb 28, 2025 | 22.85 Mn |
| Nov 30, 2024 | 23.38 Mn |
| Aug 31, 2024 | -9.37 Mn |
| May 31, 2024 | -32.29 Mn |
| Feb 29, 2024 | 29.71 Mn |
| Nov 30, 2023 | 9.76 Mn |
| Aug 31, 2023 | 2.22 Mn |
| May 31, 2023 | -16.42 Mn |
| Feb 28, 2023 | 30.65 Mn |
| Nov 30, 2022 | 23.65 Mn |
| Aug 31, 2022 | -6.03 Mn |
| May 31, 2022 | 1.30 Mn |
| Feb 28, 2022 | 32.44 Mn |
| Nov 30, 2021 | 5.27 Mn |
| Aug 31, 2021 | -10.44 Mn |
API Access
Factset Research Systems Change in Receivables 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-receivables&ticker=FDS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-receivables", "ticker": "FDS", "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-receivables&ticker=FDS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();