Donnelley Financial Solutions (DFIN) Operating Expenses (2015 - 2026)
Donnelley Financial Solutions (DFIN) recorded Operating Expenses of $78.1 million in Q2 2026, up 8.0% from $72.3 million a year earlier and up 12.7% from the prior quarter.
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Analysis
Donnelley Financial Solutions (DFIN) Operating Expenses (2015 - 2026) Analysis & Trends
On a TTM basis, Donnelley Financial Solutions' Operating Expenses came in at $298.4 million as of Jun 30, 2026, up 2.6% year-over-year; for FY2025, it was $293.2 million, down 3.5% from FY2024.
- Annual Operating Expenses has a five-year compound annual growth rate of -3.6% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $303.9 million in FY2024 (+1.2%), $300.3 million in FY2023 (+7.7%), $278.8 million in FY2022 (-14.9%) and $327.7 million in FY2021 (-6.9%).
- Quarterly Operating Expenses has ranged from $63.9 million in Q4 2022 to $90.6 million in Q4 2021 over the past five years.
- On a year-over-year basis, Operating Expenses rose in three of the last eight quarters, with growth averaging 0.8%.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 23.0% in Q1 2023, against a decline of 29.5% in Q4 2022 at the low end.
- Per Business Quant, the preceding three quarters came in at $69.3 million (Q1 2026), $81.5 million (Q4 2025) and $69.5 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Palantir Technologies | 450.50 Bn | 419.56 Bn | 1.64 Bn | 726.59 Mn |
| 2 | Oracle | 401.01 Bn | 273.57 Bn | - | 12.62 Bn |
| 3 | Sap Se | 257.03 Bn | 178.11 Bn | 8.40 Bn | -8.41 Bn |
| 4 | Salesforce | 187.04 Bn | 142.92 Bn | 8.70 Bn | 6.37 Bn |
| 5 | ServiceNow | 135.91 Bn | 114.37 Bn | 2.82 Bn | 2.66 Bn |
| 6 | Automatic Data Processing | 104.14 Bn | 86.27 Bn | 2.51 Bn | 4.34 Bn |
| 7 | Intuit | 72.30 Bn | 51.65 Bn | 3.44 Bn | 3.88 Bn |
| 8 | Relx | 60.17 Bn | 57.14 Bn | - | - |
| 9 | Strategy | 55.31 Bn | 48.30 Bn | 81.55 Mn | 8.41 Bn |
| 10 | Donnelley Financial Solutions | 1.18 Bn | 1.08 Bn | 148.00 Mn | 78.10 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 78.10 Mn |
| Mar 31, 2026 | 69.30 Mn |
| Dec 31, 2025 | 81.50 Mn |
| Sep 30, 2025 | 69.50 Mn |
| Jun 30, 2025 | 72.30 Mn |
| Mar 31, 2025 | 69.90 Mn |
| Dec 31, 2024 | 71.60 Mn |
| Sep 30, 2024 | 77.00 Mn |
| Jun 30, 2024 | 78.90 Mn |
| Mar 31, 2024 | 76.40 Mn |
| Dec 31, 2023 | 74.00 Mn |
| Sep 30, 2023 | 66.80 Mn |
| Jun 30, 2023 | 75.80 Mn |
| Mar 31, 2023 | 83.30 Mn |
| Dec 31, 2022 | 63.90 Mn |
| Sep 30, 2022 | 68.10 Mn |
| Jun 30, 2022 | 79.10 Mn |
| Mar 31, 2022 | 67.70 Mn |
| Dec 31, 2021 | 90.60 Mn |
| Sep 30, 2021 | 81.80 Mn |
API Access
Donnelley Financial Solutions Operating 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=operating-expenses&ticker=DFIN&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "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=operating-expenses&ticker=DFIN&period=max&api_key=YOUR_API_KEY");
const data = await res.json();