MBody AI (MBAI) Interest Expenses (2014 - 2023)
MBody AI's Interest Expenses came in at -$12,000 for the year ended Dec 31, 2025.
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Analysis
MBody AI (MBAI) Interest Expenses (2014 - 2023) Analysis & Trends
Going back to the year ended Dec 31, 2012, MBody AI's Interest Expenses data covers 12 years.
- The figure for the year ended Dec 31, 2025 represents the highest annual Interest Expenses since the year ended Dec 31, 2020.
- Per Business Quant, earlier years put Interest Expenses at -$2.53 million in the year ended Dec 31, 2022 and -$2.05 million in the year ended Dec 31, 2021.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Int Expense (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 249.71 Bn | 228.86 Bn | 4.88 Bn | 401.00 Mn |
| 2 | Abbott Laboratories | 171.00 Bn | 142.08 Bn | 7.27 Bn | 351.00 Mn |
| 3 | Danaher | 155.79 Bn | 139.61 Bn | 3.61 Bn | 107.00 Mn |
| 4 | Intuitive Surgical | 143.91 Bn | 123.46 Bn | 1.96 Bn | - |
| 5 | Medtronic | 110.42 Bn | 76.29 Bn | 6.34 Bn | 186.00 Mn |
| 6 | Stryker | 105.71 Bn | 91.82 Bn | 4.50 Bn | 141.00 Mn |
| 7 | Boston Scientific | 63.26 Bn | 58.27 Bn | 3.85 Bn | 96.00 Mn |
| 8 | Edwards Lifesciences | 49.80 Bn | 33.91 Bn | 1.35 Bn | - |
| 9 | Becton Dickinson | 48.78 Bn | 45.93 Bn | 2.32 Bn | 132.00 Mn |
| 10 | MBody AI | 3.55 Mn | 3.33 Mn | - | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2023 | -1.38 Mn |
| Jun 30, 2022 | -591,000.00 |
| Mar 31, 2021 | 9,000.00 |
| Dec 31, 2020 | 34,000.00 |
| Mar 31, 2020 | -14,000.00 |
| Dec 31, 2019 | 85,000.00 |
| Dec 31, 2018 | 110,000.00 |
| Dec 31, 2017 | -10,000.00 |
| Dec 31, 2016 | 68,000.00 |
| Dec 31, 2015 | -3,000.00 |
| Sep 30, 2015 | 208,000.00 |
| Jun 30, 2015 | 1.56 Mn |
| Mar 31, 2015 | 258,000.00 |
| Dec 31, 2014 | -1,000.00 |
API Access
MBody AI 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=MBAI&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "interest-expenses", "ticker": "MBAI", "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=MBAI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();