Fair Isaac (FICO) Return on Sales [ROS] (2009 - 2026)
Fair Isaac's Return on Sales [ROS] came in at 53.79% for 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) Return on Sales [ROS] (2009 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Fair Isaac reported Return on Sales [ROS] of 51.65%, 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.
- Return on Sales [ROS] has increased in each of the last seven fiscal years, with a five-year change of +23.59 percentage points (FY2020 to FY2025).
- Going back by fiscal year, Return on Sales [ROS] was 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).
- The five-year range for quarterly Return on Sales [ROS] is 34.43% (fiscal Q4 2021) to 58.19% (fiscal Q2 2026).
- Year-over-year, Return on Sales [ROS] has increased for eight consecutive quarters, with an average year-over-year change of +4.27 percentage points over the last eight quarters.
- The fastest year-over-year change in Return on Sales [ROS] over five years came in fiscal Q2 2022 (a gain of 12.03 percentage points), and the weakest in fiscal Q3 2022 (a drop of 17.18 percentage points).
- Business Quant data shows FICO's Return on Sales [ROS] at 58.19% (Q2 2026), 45.72% (Q1 2026) and 45.98% (Q4 2025) in the three fiscal quarters before Q3 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | ROS (Qtr) |
|---|---|---|---|---|---|
| 1 | Palantir Technologies | 466.13 Bn | 435.08 Bn | 1.64 Bn | 47.12% |
| 2 | Oracle | 383.82 Bn | 255.95 Bn | - | 34.78% |
| 3 | Sap Se | 263.61 Bn | 191.39 Bn | 8.40 Bn | 26.76% |
| 4 | Salesforce | 198.89 Bn | 154.76 Bn | 8.70 Bn | 20.55% |
| 5 | ServiceNow | 149.64 Bn | 128.10 Bn | 2.82 Bn | 4.06% |
| 6 | Automatic Data Processing | 115.45 Bn | 97.58 Bn | 2.51 Bn | -33.33% |
| 7 | Intuit | 89.90 Bn | 69.25 Bn | 3.44 Bn | 10.91% |
| 8 | Relx | 71.97 Bn | 71.07 Bn | - | - |
| 9 | Thomson Reuters | 48.55 Bn | 45.33 Bn | - | 28.56% |
| 10 | Fair Isaac | 17.70 Bn | 16.94 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 Return on Sales [ROS] 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=return-on-sales-%5Bros%5D&ticker=FICO&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "return-on-sales-[ros]", "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=return-on-sales-%5Bros%5D&ticker=FICO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();