Automatic Data Processing (ADP) Cash & Equivalents (2009 - 2026)
Automatic Data Processing (ADP) reported Cash & Equivalents of $3.28 billion for fiscal Q1 2027 (quarter ended Sep 30, 2026), up 32.2% from $2.48 billion a year earlier but down 22.5% from the prior quarter.
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Analysis
Automatic Data Processing (ADP) Cash & Equivalents (2009 - 2026) Analysis & Trends
At the end of FY2026 (ended Jun 30, 2026), Automatic Data Processing posted Cash & Equivalents of $4.23 billion, up 26.4% from FY2025.
- Cash & Equivalents has increased for four consecutive fiscal years, with a five-year compound annual growth rate of 10.4% (FY2021 to FY2026).
- By fiscal year, Cash & Equivalents came in at $3.35 billion in FY2025 (+14.9%), $2.91 billion in FY2024 (+39.8%), $2.08 billion in FY2023 (+45.1%) and $1.44 billion in FY2022 (-44.2%).
- Five-year quarterly Cash & Equivalents spans a low of $1.21 billion in fiscal Q1 2023 and a high of $4.23 billion in fiscal Q4 2026.
- Year over year, Cash & Equivalents has now increased in each of the last six quarters, with growth averaging 17.2% over the last eight quarters.
- The high point for year-over-year Cash & Equivalents in five years was fiscal Q3 2024 (growth of 80.0%); the low point was fiscal Q4 2022 (a decline of 44.2%).
- Per Business Quant data, the three fiscal quarters before Q1 2027 came in at $4.23 billion (Q4 2026), $3.23 billion (Q3 2026) and $2.42 billion (Q2 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Cash & Equiv. (Qtr) |
|---|---|---|---|---|---|
| 1 | Palantir Technologies | 386.60 Bn | 351.42 Bn | 1.93 Bn | 3.62 Bn |
| 2 | Oracle | 343.94 Bn | 216.07 Bn | - | 36.37 Bn |
| 3 | Sap Se | 272.35 Bn | 199.75 Bn | 8.64 Bn | 10.62 Bn |
| 4 | Salesforce | 175.46 Bn | 131.33 Bn | 8.70 Bn | 8.31 Bn |
| 5 | Automatic Data Processing | 122.07 Bn | 108.86 Bn | 2.53 Bn | 3.28 Bn |
| 6 | ServiceNow | 105.47 Bn | 84.73 Bn | 2.90 Bn | 2.39 Bn |
| 7 | Intuit | 94.25 Bn | 73.60 Bn | 3.44 Bn | 4.71 Bn |
| 8 | Relx | 73.66 Bn | 72.75 Bn | - | 291.59 Mn |
| 9 | Strategy | 51.78 Bn | 38.91 Bn | 89.63 Mn | 2.50 Bn |
| 10 | Thomson Reuters | 50.52 Bn | 46.49 Bn | - | 1.39 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 3.28 Bn |
| Jun 30, 2026 | 4.23 Bn |
| Mar 31, 2026 | 3.23 Bn |
| Dec 31, 2025 | 2.42 Bn |
| Sep 30, 2025 | 2.48 Bn |
| Jun 30, 2025 | 3.35 Bn |
| Mar 31, 2025 | 2.68 Bn |
| Dec 31, 2024 | 2.22 Bn |
| Sep 30, 2024 | 2.10 Bn |
| Jun 30, 2024 | 2.91 Bn |
| Mar 31, 2024 | 3.29 Bn |
| Dec 31, 2023 | 1.64 Bn |
| Sep 30, 2023 | 1.44 Bn |
| Jun 30, 2023 | 2.08 Bn |
| Mar 31, 2023 | 1.83 Bn |
| Dec 31, 2022 | 1.35 Bn |
| Sep 30, 2022 | 1.21 Bn |
| Jun 30, 2022 | 1.44 Bn |
| Mar 31, 2022 | 1.63 Bn |
| Dec 31, 2021 | 1.75 Bn |
API Access
Automatic Data Processing Cash & Equivalents 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=cash-and-equivalents&ticker=ADP&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "cash-and-equivalents", "ticker": "ADP", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=cash-and-equivalents&ticker=ADP&period=max&api_key=YOUR_API_KEY");
const data = await res.json();