Donnelley Financial Solutions (DFIN) Receivables (2015 - 2026)
Donnelley Financial Solutions (DFIN) posted Receivables of $235.4 million for Q2 2026, down 3.7% from $244.5 million a year earlier and down 4.4% from the prior quarter.
Donnelley Financial Solutions (DFIN) Receivables (2015 - 2026) Analysis & Trends
At the end of FY2025, Donnelley Financial Solutions' Receivables came in at $167.1 million, up 3.1% from FY2024.
- Annual Receivables shows a five-year compound annual growth rate of -4.7% (FY2020 to FY2025).
- In prior years, Donnelley Financial Solutions' Receivables was $162.1 million in FY2024 (-6.5%), $173.4 million in FY2023 (-11.8%), $196.7 million in FY2022 (-20.0%) and $245.8 million in FY2021 (+15.6%).
- Quarterly Receivables has run from a low of $162.1 million in Q4 2024 to a high of $365.8 million in Q2 2022 over five years.
- On a year-over-year basis, Receivables increased in two of the last eight quarters, with an average decline of 3.9%.
- The strongest year-over-year quarter for Receivables in the past five years was Q3 2021, with growth of 15.7%; the weakest was Q4 2022, with a decline of 20.0%.
- According to Business Quant data, Receivables for the three prior quarters was $246.3 million (Q1 2026), $167.1 million (Q4 2025) and $187.8 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Receivables (Qtr) |
|---|---|---|---|---|---|
| 1 | Palantir Technologies | 450.50 Bn | 419.56 Bn | 1.64 Bn | 1.50 Bn |
| 2 | Oracle | 401.01 Bn | 273.57 Bn | - | 11.39 Bn |
| 3 | Sap Se | 257.03 Bn | 178.11 Bn | 8.40 Bn | 8.22 Bn |
| 4 | Salesforce | 187.04 Bn | 142.92 Bn | 8.70 Bn | 6.32 Bn |
| 5 | ServiceNow | 135.91 Bn | 114.37 Bn | 2.82 Bn | 2.80 Bn |
| 6 | Automatic Data Processing | 104.14 Bn | 86.27 Bn | 2.51 Bn | 3.52 Bn |
| 7 | Intuit | 72.30 Bn | 51.65 Bn | 3.44 Bn | 625.00 Mn |
| 8 | Relx | 60.17 Bn | 57.14 Bn | - | 3.14 Bn |
| 9 | Strategy | 55.31 Bn | 48.30 Bn | 81.55 Mn | 137.09 Mn |
| 10 | Donnelley Financial Solutions | 1.18 Bn | 1.08 Bn | 148.00 Mn | 235.40 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 235.40 Mn |
| Mar 31, 2026 | 246.30 Mn |
| Dec 31, 2025 | 167.10 Mn |
| Sep 30, 2025 | 187.80 Mn |
| Jun 30, 2025 | 244.50 Mn |
| Mar 31, 2025 | 251.30 Mn |
| Dec 31, 2024 | 162.10 Mn |
| Sep 30, 2024 | 211.40 Mn |
| Jun 30, 2024 | 264.40 Mn |
| Mar 31, 2024 | 244.70 Mn |
| Dec 31, 2023 | 173.40 Mn |
| Sep 30, 2023 | 225.70 Mn |
| Jun 30, 2023 | 302.90 Mn |
| Mar 31, 2023 | 251.90 Mn |
| Dec 31, 2022 | 196.70 Mn |
| Sep 30, 2022 | 266.40 Mn |
| Jun 30, 2022 | 365.80 Mn |
| Mar 31, 2022 | 290.50 Mn |
| Dec 31, 2021 | 245.80 Mn |
| Sep 30, 2021 | 323.20 Mn |
Donnelley Financial Solutions 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=receivables&ticker=DFIN&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "receivables", "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=receivables&ticker=DFIN&period=max&api_key=YOUR_API_KEY");
const data = await res.json();