Information Services (III) Total Liabilities (2010 - 2026)
Information Services' Total Liabilities came in at $108.77 million for Q2 2026, up 2.1% from $106.58 million a year earlier and up 0.2% from the prior quarter.
Information Services (III) Total Liabilities (2010 - 2026) Analysis & Trends
At the end of FY2025, Information Services' Total Liabilities was $116.33 million, up 7.5% from FY2024.
- Total Liabilities carries a five-year compound annual growth rate of -3.7% (FY2020 to FY2025).
- Going back by year, Total Liabilities was $108.23 million in FY2024 (-25.5%), $145.26 million in FY2023 (+1.9%), $142.6 million in FY2022 (+3.0%) and $138.4 million in FY2021 (-1.4%).
- The five-year range for quarterly Total Liabilities is $106.58 million (Q2 2025) to $145.26 million (Q4 2023).
- Year-over-year, Total Liabilities has increased for three consecutive quarters, with an average decline of 9.4% over the last eight quarters.
- The fastest year-over-year change in Total Liabilities over five years came in Q3 2023 (growth of 14.5%), and the weakest in Q4 2024 (a decline of 25.5%).
- Business Quant data shows III's Total Liabilities at $108.6 million (Q1 2026), $116.33 million (Q4 2025) and $118.56 million (Q3 2025) in the three quarters before Q2 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Accenture | 116.45 Bn | 76.86 Bn | 6.13 Bn | 35.79 Bn |
| 2 | Cintas | 80.26 Bn | 79.45 Bn | 1.48 Bn | 5.39 Bn |
| 3 | Iron Mountain | 33.05 Bn | 32.57 Bn | 1.07 Bn | 23.24 Bn |
| 4 | APi | 16.57 Bn | 13.61 Bn | 703.00 Mn | 6.43 Bn |
| 5 | Rollins | 14.72 Bn | 14.26 Bn | 569.95 Mn | 1.93 Bn |
| 6 | Aramark | 14.30 Bn | 12.32 Bn | 430.34 Mn | 10.58 Bn |
| 7 | UL Solutions | 13.09 Bn | 11.87 Bn | 417.00 Mn | 1.50 Bn |
| 8 | Gartner | 11.73 Bn | 5.42 Bn | 1.19 Bn | 7.36 Bn |
| 9 | Rentokil Initial | 10.36 Bn | 3.71 Bn | - | - |
| 10 | Information Services | 259.74 Mn | 155.97 Mn | 31.97 Mn | 108.77 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 108.77 Mn |
| Mar 31, 2026 | 108.60 Mn |
| Dec 31, 2025 | 116.33 Mn |
| Sep 30, 2025 | 118.56 Mn |
| Jun 30, 2025 | 106.58 Mn |
| Mar 31, 2025 | 107.33 Mn |
| Dec 31, 2024 | 108.23 Mn |
| Sep 30, 2024 | 130.59 Mn |
| Jun 30, 2024 | 139.80 Mn |
| Mar 31, 2024 | 138.59 Mn |
| Dec 31, 2023 | 145.26 Mn |
| Sep 30, 2023 | 137.86 Mn |
| Jun 30, 2023 | 135.27 Mn |
| Mar 31, 2023 | 139.87 Mn |
| Dec 31, 2022 | 142.60 Mn |
| Sep 30, 2022 | 120.37 Mn |
| Jun 30, 2022 | 127.08 Mn |
| Mar 31, 2022 | 137.15 Mn |
| Dec 31, 2021 | 138.40 Mn |
| Sep 30, 2021 | 145.24 Mn |
Information Services Total Liabilities 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=total-liabilities&ticker=III&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "III", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=total-liabilities&ticker=III&period=max&api_key=YOUR_API_KEY");
const data = await res.json();