Lyft (LYFT) Change in Accured Expenses (2018 - 2026)
Lyft's Change in Accured Expenses was $160.83 million in Q2 2026, up 124.0% from $71.79 million a year earlier and up 243.5% from the prior quarter.
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Analysis
Lyft (LYFT) Change in Accured Expenses (2018 - 2026) Analysis & Trends
On a trailing twelve-month basis, Lyft's Change in Accured Expenses was $454.05 million through Jun 30, 2026, up 97.3% year-over-year; for FY2025, it was $385.56 million, up 132.2% from FY2024.
- In earlier years, Change in Accured Expenses was $166.01 million in FY2024, -$73.51 million in FY2023, $262.36 million in FY2022 (+12.0%) and $234.21 million in FY2021.
- Quarterly Change in Accured Expenses has moved between -$62.7 million (Q2 2022) and $206.36 million (Q4 2025) over five years.
- Compared with a year earlier, Change in Accured Expenses was higher in three of the last five quarters, with growth averaging 146.0%.
- The best year-over-year quarter for Change in Accured Expenses over five years was Q1 2025 (growth of 694.0%); the worst was Q4 2023 (a decline of 97.6%).
- Per Business Quant data, LYFT's Change in Accured Expenses in the three quarters before Q2 2026 was $46.82 million (Q1 2026), $206.36 million (Q4 2025) and $40.04 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accured Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Alphabet | 4,173.87 Bn | 3,931.39 Bn | 73.85 Bn | 6.31 Bn |
| 2 | Meta Platforms | 1,849.67 Bn | 1,552.19 Bn | 49.47 Bn | 5.93 Bn |
| 3 | Netflix | 279.23 Bn | 239.43 Bn | 6.52 Bn | -1.25 Bn |
| 4 | Alibaba Group Holding | 245.86 Bn | 63.73 Bn | 15.11 Bn | - |
| 5 | Shopify | 196.08 Bn | 173.27 Bn | 1.71 Bn | - |
| 6 | Uber Technologies | 138.90 Bn | 110.88 Bn | 6.38 Bn | 447.00 Mn |
| 7 | Booking Holdings | 119.48 Bn | 52.53 Bn | - | 2.38 Bn |
| 8 | PDD Holdings | 107.30 Bn | -144.64 Bn | 9.45 Bn | - |
| 9 | Spotify Technology | 97.33 Bn | 54.56 Bn | 1.86 Bn | - |
| 10 | Lyft | 5.85 Bn | -1.49 Bn | 917.12 Mn | 160.83 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 160.83 Mn |
| Mar 31, 2026 | 46.82 Mn |
| Dec 31, 2025 | 206.36 Mn |
| Sep 30, 2025 | 40.04 Mn |
| Jun 30, 2025 | 71.79 Mn |
| Mar 31, 2025 | 67.38 Mn |
| Dec 31, 2024 | -23.89 Mn |
| Sep 30, 2024 | 114.86 Mn |
| Jun 30, 2024 | 66.56 Mn |
| Mar 31, 2024 | 8.49 Mn |
| Dec 31, 2023 | 4.41 Mn |
| Sep 30, 2023 | -58.83 Mn |
| Jun 30, 2023 | -3.79 Mn |
| Mar 31, 2023 | -15.31 Mn |
| Dec 31, 2022 | 182.85 Mn |
| Sep 30, 2022 | 45.96 Mn |
| Jun 30, 2022 | -62.70 Mn |
| Mar 31, 2022 | 96.24 Mn |
| Dec 31, 2021 | 15.98 Mn |
| Sep 30, 2021 | 146.31 Mn |
API Access
Lyft Change in Accured 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=change-in-accured-expenses&ticker=LYFT&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "ticker": "LYFT", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=change-in-accured-expenses&ticker=LYFT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();