Mitek Systems (MITK) Operating Expenses (2010 - 2026)
Mitek Systems (MITK) recorded Operating Expenses of $42.49 million in fiscal Q3 2026 (quarter ended Jun 30, 2026), up 1.4% from $41.92 million a year earlier and up 2.9% from the prior quarter.
Mitek Systems (MITK) Operating Expenses (2010 - 2026) Analysis & Trends
On a TTM basis, Mitek Systems' Operating Expenses came in at $162.68 million as of Jun 30, 2026, up 2.8% year-over-year; for FY2025 (ended Sep 30, 2025), it was $162.9 million, down 4.1% from FY2024.
- Annual Operating Expenses has a five-year compound annual growth rate of 12.0% (FY2020 to FY2025).
- Across earlier fiscal years, Operating Expenses came in at $169.85 million in FY2024 (+8.2%), $156.99 million in FY2023 (+18.4%), $132.6 million in FY2022 (+24.5%) and $106.52 million in FY2021 (+15.2%).
- The fiscal Q3 2026 figure is the highest quarterly Operating Expenses since fiscal Q3 2024.
- On a year-over-year basis, Operating Expenses rose in three of the last eight quarters, with an average decline of 3.3%.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 45.4% in fiscal Q3 2022, against a decline of 13.3% in fiscal Q4 2024 at the low end.
- Per Business Quant, the preceding three fiscal quarters came in at $41.29 million (Q2 2026), $38.8 million (Q1 2026) and $40.09 million (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 319.55 Bn | 304.63 Bn | 2.30 Bn | 2.13 Bn |
| 2 | CrowdStrike Holdings | 265.46 Bn | 245.90 Bn | 1.10 Bn | 1.13 Bn |
| 3 | Fortinet | 129.36 Bn | 115.29 Bn | 1.64 Bn | 953.90 Mn |
| 4 | Snowflake | 115.65 Bn | 102.97 Bn | 1.04 Bn | 1.30 Bn |
| 5 | Datadog | 96.45 Bn | 78.09 Bn | 881.34 Mn | 875.89 Mn |
| 6 | Axon Enterprise | 34.50 Bn | 29.03 Bn | 546.45 Mn | 499.67 Mn |
| 7 | Okta | 33.79 Bn | 23.89 Bn | 641.00 Mn | 534.00 Mn |
| 8 | Zscaler | 32.51 Bn | 18.63 Bn | - | - |
| 9 | Baidu | 29.59 Bn | -44.04 Bn | 1.47 Mn | 4.17 Bn |
| 10 | Mitek Systems | 776.80 Mn | 216.42 Mn | 45.86 Mn | 42.49 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 42.49 Mn |
| Mar 31, 2026 | 41.29 Mn |
| Dec 31, 2025 | 38.80 Mn |
| Sep 30, 2025 | 40.09 Mn |
| Jun 30, 2025 | 41.92 Mn |
| Mar 31, 2025 | 40.56 Mn |
| Dec 31, 2024 | 40.33 Mn |
| Sep 30, 2024 | 35.51 Mn |
| Jun 30, 2024 | 44.24 Mn |
| Mar 31, 2024 | 46.27 Mn |
| Dec 31, 2023 | 43.83 Mn |
| Sep 30, 2023 | 40.94 Mn |
| Jun 30, 2023 | 41.28 Mn |
| Mar 31, 2023 | 37.44 Mn |
| Dec 31, 2022 | 37.33 Mn |
| Sep 30, 2022 | 35.83 Mn |
| Jun 30, 2022 | 38.30 Mn |
| Mar 31, 2022 | 30.83 Mn |
| Dec 31, 2021 | 27.64 Mn |
| Sep 30, 2021 | 29.35 Mn |
Mitek Systems Operating 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=operating-expenses&ticker=MITK&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "MITK", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=MITK&period=max&api_key=YOUR_API_KEY");
const data = await res.json();