Deluxe (DLX) Operating Expenses (2009 - 2026)
Deluxe's Operating Expenses was $203.9 million in Q2 2026, down 6.7% from $218.5 million a year earlier and down 4.1% from the prior quarter.
Deluxe (DLX) Operating Expenses (2009 - 2026) Analysis & Trends
On a trailing twelve-month basis, Deluxe's Operating Expenses was $857.75 million through Jun 30, 2026, down 6.4% year-over-year; for FY2025, it was $892.6 million, down 6.8% from FY2024.
- Operating Expenses has now declined for three consecutive years, with a five-year compound annual growth rate of -0.5% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $957.8 million in FY2024 (-7.4%), $1.03 billion in FY2023 (-2.0%), $1.06 billion in FY2022 (+6.0%) and $995.77 million in FY2021 (+8.7%).
- The Q2 2026 figure marks the lowest quarterly Operating Expenses since Q3 2016.
- Compared with a year earlier, Operating Expenses has declined for 12 straight quarters, with an average decline of 7.2% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was Q1 2022 (growth of 21.7%); the worst was Q2 2025 (a decline of 10.8%).
- Per Business Quant data, DLX's Operating Expenses in the three quarters before Q2 2026 was $212.7 million (Q1 2026), $225.87 million (Q4 2025) and $215.27 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Block | 51.56 Bn | 23.34 Bn | 3.24 Bn | 2.81 Bn |
| 2 | PayPal Holdings | 50.29 Bn | 8.99 Bn | - | 7.18 Bn |
| 3 | Coinbase Global | 35.53 Bn | -4.11 Bn | - | 1.15 Bn |
| 4 | Fiserv | 33.43 Bn | 30.64 Bn | 2.76 Bn | 10.69 Bn |
| 5 | Corpay | 29.86 Bn | 18.68 Bn | - | 241.27 Mn |
| 6 | Global Payments | 25.78 Bn | 604.58 Mn | 2.01 Bn | 3.06 Bn |
| 7 | Guidewire Software | 13.57 Bn | 10.14 Bn | 269.68 Mn | 207.36 Mn |
| 8 | Jack Henry & Associates | 12.44 Bn | 12.35 Bn | 273.85 Mn | 507.25 Mn |
| 9 | Chime Financial | 11.95 Bn | 7.64 Bn | 646.07 Mn | 611.74 Mn |
| 10 | Deluxe | 1.22 Bn | 1.05 Bn | 287.60 Mn | 234.90 Mn |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 234.90 Mn |
| Jun 30, 2026 | 203.90 Mn |
| Mar 31, 2026 | 212.70 Mn |
| Dec 31, 2025 | 225.87 Mn |
| Sep 30, 2025 | 215.27 Mn |
| Jun 30, 2025 | 218.50 Mn |
| Mar 31, 2025 | 232.90 Mn |
| Dec 31, 2024 | 226.22 Mn |
| Sep 30, 2024 | 238.80 Mn |
| Jun 30, 2024 | 244.88 Mn |
| Mar 31, 2024 | 247.90 Mn |
| Dec 31, 2023 | 247.35 Mn |
| Sep 30, 2023 | 256.83 Mn |
| Jun 30, 2023 | 269.55 Mn |
| Mar 31, 2023 | 260.57 Mn |
| Dec 31, 2022 | 256.03 Mn |
| Sep 30, 2022 | 259.00 Mn |
| Jun 30, 2022 | 264.81 Mn |
| Mar 31, 2022 | 275.94 Mn |
| Dec 31, 2021 | 272.17 Mn |
Deluxe 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=DLX&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "DLX", "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=DLX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();