Brinks (BCO) Operating Expenses (2009 - 2026)
Brinks (BCO) recorded Operating Expenses of $1.26 billion in Q2 2026, up 8.4% from $1.16 billion a year earlier but down 0.9% from the prior quarter.
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Analysis
Brinks (BCO) Operating Expenses (2009 - 2026) Analysis & Trends
On a TTM basis, Brinks' Operating Expenses came in at $4.92 billion as of Jun 30, 2026, up 6.9% year-over-year; for FY2025, it came in at $4.68 billion, up 2.3% from FY2024.
- Annual Operating Expenses has increased for nine straight years, with a five-year compound annual growth rate of 6.2% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $4.58 billion in FY2024 (+4.1%), $4.4 billion in FY2023 (+5.9%), $4.15 billion in FY2022 (+7.3%) and $3.87 billion in FY2021 (+11.7%).
- Quarterly Operating Expenses has ranged from $977.9 million in Q4 2021 to $1.27 billion in Q1 2026 over the past five years.
- On a year-over-year basis, Operating Expenses has increased for five consecutive quarters, with growth averaging 5.3% over the last eight quarters.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 13.0% in Q3 2021, against a decline of 0.2% in Q1 2025 at the low end.
- Per Business Quant, the preceding three quarters came in at $1.27 billion (Q1 2026), $1.2 billion (Q4 2025) and $1.19 billion (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Accenture | 145.07 Bn | 104.35 Bn | 6.13 Bn | 15.54 Bn |
| 2 | Cintas | 84.93 Bn | 84.01 Bn | 1.55 Bn | 841.66 Mn |
| 3 | Iron Mountain | 33.24 Bn | 32.43 Bn | 1.07 Bn | 1.66 Bn |
| 4 | APi | 17.33 Bn | 14.36 Bn | 703.00 Mn | 528.00 Mn |
| 5 | Rollins | 15.77 Bn | 15.32 Bn | 569.95 Mn | 877.22 Mn |
| 6 | UL Solutions | 14.77 Bn | 13.53 Bn | 417.00 Mn | 267.00 Mn |
| 7 | Aramark | 14.70 Bn | 12.64 Bn | 430.34 Mn | 4.84 Bn |
| 8 | Gartner | 13.80 Bn | 7.49 Bn | 1.19 Bn | 1.30 Bn |
| 9 | Rentokil Initial | 10.70 Bn | 4.22 Bn | - | - |
| 10 | Brinks | 4.26 Bn | -2.01 Bn | 366.10 Mn | 1.26 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 1.26 Bn |
| Mar 31, 2026 | 1.27 Bn |
| Dec 31, 2025 | 1.20 Bn |
| Sep 30, 2025 | 1.19 Bn |
| Jun 30, 2025 | 1.16 Bn |
| Mar 31, 2025 | 1.13 Bn |
| Dec 31, 2024 | 1.17 Bn |
| Sep 30, 2024 | 1.15 Bn |
| Jun 30, 2024 | 1.13 Bn |
| Mar 31, 2024 | 1.13 Bn |
| Dec 31, 2023 | 1.09 Bn |
| Sep 30, 2023 | 1.09 Bn |
| Jun 30, 2023 | 1.11 Bn |
| Mar 31, 2023 | 1.10 Bn |
| Dec 31, 2022 | 1.04 Bn |
| Sep 30, 2022 | 1.06 Bn |
| Jun 30, 2022 | 1.04 Bn |
| Mar 31, 2022 | 1.01 Bn |
| Dec 31, 2021 | 977.90 Mn |
| Sep 30, 2021 | 999.50 Mn |
API Access
Brinks 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=BCO&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "BCO", "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=BCO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();