Fair Isaac (FICO) Operating Expenses (2009 - 2026)
Fair Isaac's Operating Expenses came in at $311.56 million for fiscal Q3 2026 (quarter ended Jun 30, 2026), up 13.8% from $273.9 million a year earlier and up 7.7% from the prior quarter.
Fair Isaac (FICO) Operating Expenses (2009 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Fair Isaac reported Operating Expenses of $1.16 billion, up 10.8% year-over-year; for FY2025 (ended Sep 30, 2025), it came in at $1.07 billion, up 8.3% from FY2024.
- Operating Expenses has increased in each of the last four fiscal years, with a five-year compound annual growth rate of 1.3% (FY2020 to FY2025).
- Going back by fiscal year, Operating Expenses was $983.9 million in FY2024 (+13.0%), $870.73 million in FY2023 (+4.3%), $834.86 million in FY2022 (+2.9%) and $811.05 million in FY2021 (-18.8%).
- The fiscal Q3 2026 figure represents the highest quarterly Operating Expenses in data going back to fiscal Q3 2009.
- Year-over-year, Operating Expenses has increased for 14 consecutive quarters, with growth averaging 10.4% over the last eight quarters.
- The fastest year-over-year change in Operating Expenses over five years came in fiscal Q3 2022 (growth of 44.9%), and the weakest in fiscal Q4 2021 (a decline of 24.1%).
- Business Quant data shows FICO's Operating Expenses at $289.21 million (Q2 2026), $277.91 million (Q1 2026) and $278.6 million (Q4 2025) in the three fiscal quarters before Q3 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Palantir Technologies | 450.50 Bn | 419.56 Bn | 1.64 Bn | 726.59 Mn |
| 2 | Oracle | 401.01 Bn | 273.57 Bn | - | 12.62 Bn |
| 3 | Sap Se | 257.03 Bn | 178.11 Bn | 8.40 Bn | -8.41 Bn |
| 4 | Salesforce | 187.04 Bn | 142.92 Bn | 8.70 Bn | 6.37 Bn |
| 5 | ServiceNow | 135.91 Bn | 114.37 Bn | 2.82 Bn | 2.66 Bn |
| 6 | Automatic Data Processing | 104.14 Bn | 86.27 Bn | 2.51 Bn | 4.34 Bn |
| 7 | Intuit | 72.30 Bn | 51.65 Bn | 3.44 Bn | 3.88 Bn |
| 8 | Relx | 60.17 Bn | 57.14 Bn | - | - |
| 9 | Strategy | 55.31 Bn | 48.30 Bn | 81.55 Mn | 8.41 Bn |
| 10 | Fair Isaac | 18.16 Bn | 17.40 Bn | 587.17 Mn | 311.56 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 311.56 Mn |
| Mar 31, 2026 | 289.21 Mn |
| Dec 31, 2025 | 277.91 Mn |
| Sep 30, 2025 | 278.60 Mn |
| Jun 30, 2025 | 273.90 Mn |
| Mar 31, 2025 | 253.09 Mn |
| Dec 31, 2024 | 260.44 Mn |
| Sep 30, 2024 | 256.63 Mn |
| Jun 30, 2024 | 257.60 Mn |
| Mar 31, 2024 | 238.97 Mn |
| Dec 31, 2023 | 230.70 Mn |
| Sep 30, 2023 | 224.03 Mn |
| Jun 30, 2023 | 221.66 Mn |
| Mar 31, 2023 | 220.51 Mn |
| Dec 31, 2022 | 204.53 Mn |
| Sep 30, 2022 | 214.59 Mn |
| Jun 30, 2022 | 208.35 Mn |
| Mar 31, 2022 | 205.14 Mn |
| Dec 31, 2021 | 206.78 Mn |
| Sep 30, 2021 | 219.39 Mn |
Fair Isaac 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=FICO&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "FICO", "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=FICO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();