Donnelley Financial Solutions (DFIN) Cash & Equivalents (2015 - 2026)
Donnelley Financial Solutions (DFIN) reported Cash & Equivalents of $25.3 million for Q2 2026, down 25.1% from $33.8 million a year earlier and down 3.1% from the prior quarter.
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Analysis
Donnelley Financial Solutions (DFIN) Cash & Equivalents (2015 - 2026) Analysis & Trends
At the end of FY2025, Donnelley Financial Solutions posted Cash & Equivalents of $24.5 million, down 57.2% from FY2024.
- Cash & Equivalents has a five-year compound annual growth rate of -19.7% (FY2020 to FY2025).
- By year, Cash & Equivalents came in at $57.3 million in FY2024 (+148.1%), $23.1 million in FY2023 (-32.5%), $34.2 million in FY2022 (-37.2%) and $54.5 million in FY2021 (-26.0%).
- Five-year quarterly Cash & Equivalents spans a low of $10.4 million in Q1 2022 and a high of $122.9 million in Q3 2021.
- Year over year, Cash & Equivalents gained in three of the last eight quarters, with growth averaging 26.9%.
- The high point for year-over-year Cash & Equivalents in five years was Q3 2021 (growth of 200.5%); the low point was Q3 2022 (a decline of 91.2%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $26.1 million (Q1 2026), $24.5 million (Q4 2025) and $22.7 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Cash & Equiv. (Qtr) |
|---|---|---|---|---|---|
| 1 | Palantir Technologies | 456.65 Bn | 425.71 Bn | 1.64 Bn | 2.03 Bn |
| 2 | Oracle | 417.55 Bn | 290.11 Bn | - | 36.37 Bn |
| 3 | Sap Se | 259.04 Bn | 180.13 Bn | 8.40 Bn | 12.22 Bn |
| 4 | Salesforce | 194.78 Bn | 150.65 Bn | 8.70 Bn | 8.31 Bn |
| 5 | ServiceNow | 142.47 Bn | 120.93 Bn | 2.82 Bn | 2.50 Bn |
| 6 | Automatic Data Processing | 105.00 Bn | 87.13 Bn | 2.51 Bn | 4.23 Bn |
| 7 | Intuit | 75.89 Bn | 55.24 Bn | 3.44 Bn | 4.71 Bn |
| 8 | Relx | 60.92 Bn | 57.89 Bn | - | 295.17 Mn |
| 9 | Strategy | 56.49 Bn | 49.48 Bn | 81.55 Mn | 1.71 Bn |
| 10 | Donnelley Financial Solutions | 1.17 Bn | 1.07 Bn | 148.00 Mn | 25.30 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 25.30 Mn |
| Mar 31, 2026 | 26.10 Mn |
| Dec 31, 2025 | 24.50 Mn |
| Sep 30, 2025 | 22.70 Mn |
| Jun 30, 2025 | 33.80 Mn |
| Mar 31, 2025 | 16.20 Mn |
| Dec 31, 2024 | 57.30 Mn |
| Sep 30, 2024 | 33.60 Mn |
| Jun 30, 2024 | 35.00 Mn |
| Mar 31, 2024 | 43.70 Mn |
| Dec 31, 2023 | 23.10 Mn |
| Sep 30, 2023 | 11.70 Mn |
| Jun 30, 2023 | 19.40 Mn |
| Mar 31, 2023 | 28.80 Mn |
| Dec 31, 2022 | 34.20 Mn |
| Sep 30, 2022 | 10.80 Mn |
| Jun 30, 2022 | 17.80 Mn |
| Mar 31, 2022 | 10.40 Mn |
| Dec 31, 2021 | 54.50 Mn |
| Sep 30, 2021 | 122.90 Mn |
API Access
Donnelley Financial Solutions 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=DFIN&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "cash-and-equivalents", "ticker": "DFIN", "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=DFIN&period=max&api_key=YOUR_API_KEY");
const data = await res.json();