Information Services (III) Long-Term Debt Repayments (2011 - 2022)
Information Services' Long-Term Debt Repayments came in at $1.08 million for Q4 2022, unchanged from $1.08 million a year earlier and unchanged from the prior quarter.
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Analysis
Information Services (III) Long-Term Debt Repayments (2011 - 2022) Analysis & Trends
For FY2022, Information Services' Long-Term Debt Repayments was $4.3 million, unchanged from FY2021.
- Long-Term Debt Repayments carries a five-year compound annual growth rate of -12.8% (FY2017 to FY2022).
- Going back by year, Long-Term Debt Repayments was $4.3 million in FY2021 (-46.8%), $8.09 million in FY2020 (-34.0%), $12.25 million in FY2019 (+15.2%) and $10.64 million in FY2018 (+24.6%).
- The five-year range for quarterly Long-Term Debt Repayments is -$1.44 million (Q2 2019) to $9.56 million (Q4 2019).
- The fastest year-over-year change in Long-Term Debt Repayments over five years came in Q4 2019 (growth of 363.5%), and the weakest in Q4 2020 (a decline of 88.8%).
- Business Quant data shows III's Long-Term Debt Repayments at $1.08 million (Q3 2022), $1.08 million (Q2 2022) and $1.08 million (Q1 2022) in the three quarters before Q4 2022.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | LT Debt Repayment (Qtr) |
|---|---|---|---|---|---|
| 1 | Accenture | 147.80 Bn | 107.08 Bn | 6.13 Bn | - |
| 2 | Cintas | 88.17 Bn | 87.25 Bn | 1.55 Bn | - |
| 3 | Iron Mountain | 34.25 Bn | 33.44 Bn | 1.07 Bn | 6.75 Bn |
| 4 | APi | 17.39 Bn | 14.43 Bn | 703.00 Mn | 302.00 Mn |
| 5 | Rollins | 16.15 Bn | 15.70 Bn | 569.95 Mn | - |
| 6 | UL Solutions | 14.99 Bn | 13.75 Bn | 417.00 Mn | 57.00 Mn |
| 7 | Aramark | 14.70 Bn | 12.64 Bn | 430.34 Mn | 11.63 Mn |
| 8 | Gartner | 14.61 Bn | 8.30 Bn | 1.19 Bn | - |
| 9 | Rentokil Initial | 10.62 Bn | 4.14 Bn | - | - |
| 10 | Information Services | 290.03 Mn | 186.26 Mn | 31.97 Mn | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Dec 31, 2022 | 1.08 Mn |
| Sep 30, 2022 | 1.08 Mn |
| Jun 30, 2022 | 1.08 Mn |
| Mar 31, 2022 | 1.08 Mn |
| Dec 31, 2021 | 1.08 Mn |
| Sep 30, 2021 | 1.08 Mn |
| Jun 30, 2021 | 1.08 Mn |
| Mar 31, 2021 | 1.08 Mn |
| Dec 31, 2020 | 1.08 Mn |
| Sep 30, 2020 | 1.08 Mn |
| Dec 31, 2019 | 9.56 Mn |
| Sep 30, 2019 | 563,000.00 |
| Jun 30, 2019 | -1.44 Mn |
| Mar 31, 2019 | 3.56 Mn |
| Dec 31, 2018 | 2.06 Mn |
| Sep 30, 2018 | 2.06 Mn |
| Jun 30, 2018 | 4.20 Mn |
| Mar 31, 2018 | 2.31 Mn |
| Dec 31, 2017 | 1.39 Mn |
| Sep 30, 2017 | 4.38 Mn |
API Access
Information Services Long-Term Debt Repayments 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=long-term-debt-repayments&ticker=III&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "long-term-debt-repayments", "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=long-term-debt-repayments&ticker=III&period=max&api_key=YOUR_API_KEY");
const data = await res.json();