Wm Technology (MAPS) Total Liabilities (2019 - 2026)
Wm Technology's Total Liabilities came in at $51.75 million for Q2 2026, down 13.8% from $60.06 million a year earlier but up 0.3% from the prior quarter.
Wm Technology (MAPS) Total Liabilities (2019 - 2026) Analysis & Trends
At the end of FY2025, Wm Technology's Total Liabilities was $58.87 million, down 4.7% from FY2024.
- Total Liabilities has declined in each of the last four years, though with a five-year compound annual growth rate of 19.0% (FY2020 to FY2025).
- Going back by year, Total Liabilities was $61.8 million in FY2024 (-3.2%), $63.87 million in FY2023 (-24.2%), $84.26 million in FY2022 (-63.9%) and $233.2 million in FY2021 (+847.1%).
- The five-year range for quarterly Total Liabilities is $51.58 million (Q1 2026) to $315.21 million (Q3 2021).
- Year-over-year, Total Liabilities has declined for four consecutive quarters, with an average decline of 5.3% over the last eight quarters.
- The fastest year-over-year change in Total Liabilities over five years came in Q4 2021 (growth of 847.1%), and the weakest in Q3 2023 (a decline of 71.6%).
- Business Quant data shows MAPS's Total Liabilities at $51.58 million (Q1 2026), $58.87 million (Q4 2025) and $57.55 million (Q3 2025) in the three quarters before Q2 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Alphabet | 4,164.76 Bn | 3,922.28 Bn | 73.85 Bn | 281.50 Bn |
| 2 | Meta Platforms | 1,823.40 Bn | 1,525.92 Bn | 49.47 Bn | 188.74 Bn |
| 3 | Netflix | 288.27 Bn | 248.47 Bn | 6.52 Bn | 28.30 Bn |
| 4 | Alibaba Group Holding | 252.72 Bn | 70.58 Bn | 15.11 Bn | 125.68 Bn |
| 5 | Shopify | 186.52 Bn | 163.71 Bn | 1.71 Bn | 1.79 Bn |
| 6 | Uber Technologies | 139.11 Bn | 111.09 Bn | 6.38 Bn | 37.58 Bn |
| 7 | Booking Holdings | 123.13 Bn | 56.18 Bn | - | 40.47 Bn |
| 8 | PDD Holdings | 111.72 Bn | -140.21 Bn | 9.45 Bn | 31.67 Bn |
| 9 | AppLovin | 103.35 Bn | 93.38 Bn | 1.70 Bn | 5.11 Bn |
| 10 | Wm Technology | 57.49 Mn | -98.37 Mn | 39.92 Mn | 51.75 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 51.75 Mn |
| Mar 31, 2026 | 51.58 Mn |
| Dec 31, 2025 | 58.87 Mn |
| Sep 30, 2025 | 57.55 Mn |
| Jun 30, 2025 | 60.06 Mn |
| Mar 31, 2025 | 60.11 Mn |
| Dec 31, 2024 | 61.80 Mn |
| Sep 30, 2024 | 58.58 Mn |
| Jun 30, 2024 | 58.78 Mn |
| Mar 31, 2024 | 59.02 Mn |
| Dec 31, 2023 | 63.87 Mn |
| Sep 30, 2023 | 63.91 Mn |
| Jun 30, 2023 | 68.27 Mn |
| Mar 31, 2023 | 75.39 Mn |
| Dec 31, 2022 | 84.26 Mn |
| Sep 30, 2022 | 224.90 Mn |
| Jun 30, 2022 | 239.79 Mn |
| Mar 31, 2022 | 256.24 Mn |
| Dec 31, 2021 | 233.20 Mn |
| Sep 30, 2021 | 315.21 Mn |
Wm Technology 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=MAPS&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "MAPS", "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=MAPS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();