Modular Medical (MODD) Total Liabilities (2011 - 2026)
Modular Medical (MODD) posted Total Liabilities of $1.49 million for fiscal Q1 2027 (quarter ended Jun 30, 2026), down 36.0% from $2.33 million a year earlier and down 20.5% from the prior quarter.
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Analysis
Modular Medical (MODD) Total Liabilities (2011 - 2026) Analysis & Trends
At the end of FY2026 (ended Mar 31, 2026), Modular Medical's Total Liabilities came in at $1.87 million, up 13.0% from FY2025.
- Annual Total Liabilities shows a five-year compound annual growth rate of -11.9% (FY2021 to FY2026).
- In prior fiscal years, Modular Medical's Total Liabilities was $1.66 million in FY2025 (-27.0%), $2.27 million in FY2024 (+4.7%), $2.17 million in FY2023 (+114.9%) and $1.01 million in FY2022 (-71.3%).
- The fiscal Q1 2027 figure stands as the lowest quarterly Total Liabilities since fiscal Q3 2023.
- On a year-over-year basis, Total Liabilities increased in four of the last eight quarters, with growth averaging 23.7%.
- The strongest year-over-year quarter for Total Liabilities in the past five years was fiscal Q3 2024, with growth of 229.3%; the weakest was fiscal Q3 2023, with a decline of 92.1%.
- According to Business Quant data, Total Liabilities for the three prior fiscal quarters was $1.87 million (Q4 2026), $4.38 million (Q3 2026) and $4.21 million (Q2 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 251.30 Bn | 230.45 Bn | 4.88 Bn | 60.49 Bn |
| 2 | Abbott Laboratories | 174.70 Bn | 145.78 Bn | 7.27 Bn | 57.45 Bn |
| 3 | Danaher | 158.94 Bn | 142.76 Bn | 3.61 Bn | 39.78 Bn |
| 4 | Intuitive Surgical | 145.87 Bn | 125.42 Bn | 1.96 Bn | 2.58 Bn |
| 5 | Medtronic | 111.49 Bn | 77.36 Bn | 6.34 Bn | 42.46 Bn |
| 6 | Stryker | 106.96 Bn | 93.08 Bn | 4.50 Bn | 23.94 Bn |
| 7 | Boston Scientific | 63.62 Bn | 58.63 Bn | 3.85 Bn | 20.04 Bn |
| 8 | Edwards Lifesciences | 50.80 Bn | 34.92 Bn | 1.35 Bn | 3.14 Bn |
| 9 | Becton Dickinson | 49.59 Bn | 46.74 Bn | 2.32 Bn | 26.32 Bn |
| 10 | Modular Medical | 10.86 Mn | -8.25 Mn | - | 1.49 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 1.49 Mn |
| Mar 31, 2026 | 1.87 Mn |
| Dec 31, 2025 | 4.38 Mn |
| Sep 30, 2025 | 4.21 Mn |
| Jun 30, 2025 | 2.33 Mn |
| Mar 31, 2025 | 1.66 Mn |
| Dec 31, 2024 | 1.89 Mn |
| Sep 30, 2024 | 1.86 Mn |
| Jun 30, 2024 | 2.06 Mn |
| Mar 31, 2024 | 2.27 Mn |
| Dec 31, 2023 | 2.35 Mn |
| Sep 30, 2023 | 2.12 Mn |
| Jun 30, 2023 | 2.11 Mn |
| Mar 31, 2023 | 2.17 Mn |
| Dec 31, 2022 | 714,842.00 |
| Sep 30, 2022 | 694,637.00 |
| Jun 30, 2022 | 991,401.00 |
| Mar 31, 2022 | 1.01 Mn |
| Dec 31, 2021 | 9.00 Mn |
| Sep 30, 2021 | 6.48 Mn |
API Access
Modular Medical 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=MODD&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "MODD", "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=MODD&period=max&api_key=YOUR_API_KEY");
const data = await res.json();