Fair Isaac (FICO) Operating Margin (2009 - 2026)
Fair Isaac (FICO) recorded Operating Margin of 53.79% in fiscal Q3 2026 (quarter ended Jun 30, 2026), up 4.85 percentage points from 48.94% a year earlier but down 4.40 percentage points from the prior quarter.
Fair Isaac (FICO) Operating Margin (2009 - 2026) Analysis & Trends
On a TTM basis, Fair Isaac's Operating Margin came in at 51.65% as of Jun 30, 2026, up 5.78 percentage points year-over-year; for FY2025 (ended Sep 30, 2025), it came in at 46.45%, up 3.74 percentage points from FY2024.
- Annual Operating Margin has increased for seven straight fiscal years, with a five-year change of +23.59 percentage points (FY2020 to FY2025).
- Across earlier fiscal years, Operating Margin came in at 42.71% in FY2024 (+0.24 pp), 42.47% in FY2023 (+3.09 pp), 39.38% in FY2022 (+0.99 pp) and 38.40% in FY2021 (+15.53 pp).
- Quarterly Operating Margin has ranged from 34.43% in fiscal Q4 2021 to 58.19% in fiscal Q2 2026 over the past five years.
- On a year-over-year basis, Operating Margin has increased for eight consecutive quarters, with an average year-over-year change of +4.27 percentage points over the last eight quarters.
- Peak year-over-year performance for Operating Margin in the last five years was a gain of 12.03 percentage points in fiscal Q2 2022, against a drop of 17.18 percentage points in fiscal Q3 2022 at the low end.
- Per Business Quant, the preceding three fiscal quarters came in at 58.19% (Q2 2026), 45.72% (Q1 2026) and 45.98% (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Operating Margin (Qtr) |
|---|---|---|---|---|---|
| 1 | Palantir Technologies | 450.50 Bn | 419.56 Bn | 1.64 Bn | 47.12% |
| 2 | Oracle | 401.01 Bn | 273.57 Bn | - | 34.78% |
| 3 | Sap Se | 257.03 Bn | 178.11 Bn | 8.40 Bn | 26.76% |
| 4 | Salesforce | 187.04 Bn | 142.92 Bn | 8.70 Bn | 20.55% |
| 5 | ServiceNow | 135.91 Bn | 114.37 Bn | 2.82 Bn | 4.06% |
| 6 | Automatic Data Processing | 104.14 Bn | 86.27 Bn | 2.51 Bn | -33.33% |
| 7 | Intuit | 72.30 Bn | 51.65 Bn | 3.44 Bn | 10.91% |
| 8 | Relx | 60.17 Bn | 57.14 Bn | - | - |
| 9 | Strategy | 55.31 Bn | 48.30 Bn | 81.55 Mn | -6,808.11% |
| 10 | Fair Isaac | 18.16 Bn | 17.40 Bn | 587.17 Mn | 53.79% |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 53.79% |
| Mar 31, 2026 | 58.19% |
| Dec 31, 2025 | 45.72% |
| Sep 30, 2025 | 45.98% |
| Jun 30, 2025 | 48.94% |
| Mar 31, 2025 | 49.25% |
| Dec 31, 2024 | 40.80% |
| Sep 30, 2024 | 43.45% |
| Jun 30, 2024 | 42.48% |
| Mar 31, 2024 | 44.91% |
| Dec 31, 2023 | 39.62% |
| Sep 30, 2023 | 42.52% |
| Jun 30, 2023 | 44.40% |
| Mar 31, 2023 | 42.01% |
| Dec 31, 2022 | 40.69% |
| Sep 30, 2022 | 38.47% |
| Jun 30, 2022 | 40.29% |
| Mar 31, 2022 | 42.57% |
| Dec 31, 2021 | 35.86% |
| Sep 30, 2021 | 34.43% |
Fair Isaac Operating Margin 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-margin&ticker=FICO&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-margin", "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-margin&ticker=FICO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();