Diebold Nixdorf (DBD) Short-Term Debt repayments (2019 - 2024)
Diebold Nixdorf (DBD) posted Short-Term Debt repayments of -$80 million for Q2 2024.
Diebold Nixdorf (DBD) Short-Term Debt repayments (2019 - 2024) Analysis & Trends
For the trailing twelve months through Jun 30, 2024, Short-Term Debt repayments at Diebold Nixdorf was $150 million; for FY2020, it was $705.1 million, down 18.8% from FY2019.
- In prior years, Diebold Nixdorf's Short-Term Debt repayments was $868.5 million in FY2019.
- The Q2 2024 figure stands as the lowest quarterly Short-Term Debt repayments since Q4 2022.
- The strongest year-over-year quarter for Short-Term Debt repayments in the past five years was Q2 2021, with growth of 541.0%; the weakest was Q3 2022, with a decline of 65.7%.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | ST Debt Repayment (Qtr) |
|---|---|---|---|---|---|
| 1 | Bryn | 945.00 Bn | 945.00 Bn | - | - |
| 2 | Veeva Systems | 51.57 Bn | 23.82 Bn | 695.95 Mn | - |
| 3 | Samsara | 23.54 Bn | 20.31 Bn | 392.58 Mn | - |
| 4 | Ptc | 22.16 Bn | 20.97 Bn | 490.47 Mn | 12.50 Mn |
| 5 | Toast | 18.20 Bn | 10.87 Bn | 516.00 Mn | - |
| 6 | Trimble | 13.96 Bn | 13.03 Bn | 674.90 Mn | - |
| 7 | Manhattan Associates | 13.22 Bn | 12.21 Bn | 168.33 Mn | - |
| 8 | Costar | 12.85 Bn | 6.80 Bn | 728.00 Mn | - |
| 9 | Bentley Systems | 11.44 Bn | 10.90 Bn | 336.74 Mn | - |
| 10 | Diebold Nixdorf | 2.32 Bn | 987.65 Mn | 239.60 Mn | - |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2024 | -80.00 Mn |
| Mar 31, 2024 | 150.00 Mn |
| Mar 31, 2023 | 80.00 Mn |
| Dec 31, 2022 | -272.00 Mn |
| Sep 30, 2022 | 57.00 Mn |
| Jun 30, 2022 | 102.00 Mn |
| Mar 31, 2022 | 113.00 Mn |
| Dec 31, 2021 | -280.10 Mn |
| Sep 30, 2021 | 166.00 Mn |
| Jun 30, 2021 | 64.10 Mn |
| Mar 31, 2021 | 50.00 Mn |
| Dec 31, 2020 | 244.10 Mn |
| Sep 30, 2020 | 385.90 Mn |
| Jun 30, 2020 | 10.00 Mn |
| Mar 31, 2020 | 65.10 Mn |
| Dec 31, 2019 | 40.10 Mn |
| Sep 30, 2019 | 282.20 Mn |
Diebold Nixdorf Short-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=short-term-debt-repayments&ticker=DBD&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "short-term-debt-repayments", "ticker": "DBD", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=short-term-debt-repayments&ticker=DBD&period=max&api_key=YOUR_API_KEY");
const data = await res.json();