Geo (GEO) Interest Expenses (2009 - 2026)
Geo (GEO) recorded Interest Expenses of $38.56 million in Q2 2026, down 8.0% from $41.91 million a year earlier but up 0.7% from the prior quarter.
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Analysis
Geo (GEO) Interest Expenses (2009 - 2026) Analysis & Trends
On a TTM basis, Geo's Interest Expenses came in at $153.03 million as of Jun 30, 2026, down 11.6% year-over-year; for FY2025, it came in at $160.52 million, down 15.8% from FY2024.
- Annual Interest Expenses has a five-year compound annual growth rate of 4.8% (FY2020 to FY2025).
- Across earlier years, Interest Expenses came in at $190.62 million in FY2024 (-12.7%), $218.29 million in FY2023 (+32.7%), $164.55 million in FY2022 (+27.1%) and $129.46 million in FY2021 (+2.1%).
- Quarterly Interest Expenses has ranged from $31.62 million in Q1 2022 to $55.78 million in Q3 2023 over the past five years.
- On a year-over-year basis, Interest Expenses has declined for ten consecutive quarters, with an average decline of 14.7% over the last eight quarters.
- Peak year-over-year performance for Interest Expenses in the last five years was growth of 71.6% in Q1 2023, against a decline of 18.8% in Q4 2024 at the low end.
- Per Business Quant, the preceding three quarters came in at $38.3 million (Q1 2026), $37.94 million (Q4 2025) and $38.23 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Int Expense (Qtr) |
|---|---|---|---|---|---|
| 1 | Accenture | 172.71 Bn | 133.12 Bn | 6.13 Bn | 70.65 Mn |
| 2 | Cintas | 89.51 Bn | 88.59 Bn | 1.55 Bn | 24.71 Mn |
| 3 | Iron Mountain | 32.96 Bn | 32.48 Bn | 1.07 Bn | - |
| 4 | Rollins | 16.86 Bn | 16.41 Bn | 582.90 Mn | 10.67 Mn |
| 5 | APi | 16.77 Bn | 13.80 Bn | 703.00 Mn | 36.00 Mn |
| 6 | UL Solutions | 14.87 Bn | 13.66 Bn | 417.00 Mn | 5.00 Mn |
| 7 | Gartner | 14.80 Bn | 8.50 Bn | 1.19 Bn | 22.27 Mn |
| 8 | Aramark | 13.84 Bn | 11.86 Bn | 430.34 Mn | - |
| 9 | Rentokil Initial | 11.56 Bn | 5.07 Bn | - | - |
| 10 | Geo | 3.56 Bn | 3.17 Bn | - | 38.56 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 38.56 Mn |
| Mar 31, 2026 | 38.30 Mn |
| Dec 31, 2025 | 37.94 Mn |
| Sep 30, 2025 | 38.23 Mn |
| Jun 30, 2025 | 41.91 Mn |
| Mar 31, 2025 | 42.44 Mn |
| Dec 31, 2024 | 43.19 Mn |
| Sep 30, 2024 | 45.50 Mn |
| Jun 30, 2024 | 50.64 Mn |
| Mar 31, 2024 | 51.30 Mn |
| Dec 31, 2023 | 53.21 Mn |
| Sep 30, 2023 | 55.78 Mn |
| Jun 30, 2023 | 55.05 Mn |
| Mar 31, 2023 | 54.26 Mn |
| Dec 31, 2022 | 53.17 Mn |
| Sep 30, 2022 | 46.54 Mn |
| Jun 30, 2022 | 33.23 Mn |
| Mar 31, 2022 | 31.62 Mn |
| Dec 31, 2021 | 33.04 Mn |
| Sep 30, 2021 | 32.53 Mn |
API Access
Geo Interest 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=interest-expenses&ticker=GEO&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "interest-expenses", "ticker": "GEO", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=interest-expenses&ticker=GEO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();