ExlService Holdings (EXLS) Operating Expenses (2010 - 2026)
ExlService Holdings (EXLS) recorded Operating Expenses of $138.67 million in Q2 2026, up 22.7% from $113.05 million a year earlier and up 6.5% from the prior quarter.
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Analysis
ExlService Holdings (EXLS) Operating Expenses (2010 - 2026) Analysis & Trends
On a TTM basis, ExlService Holdings' Operating Expenses came in at $528.3 million as of Jun 30, 2026, up 17.7% year-over-year; for FY2025, it was $487.33 million, up 14.0% from FY2024.
- Annual Operating Expenses has increased for five straight years, with a five-year compound annual growth rate of 16.8% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $427.39 million in FY2024 (+15.8%), $369.01 million in FY2023 (+14.1%), $323.29 million in FY2022 (+17.4%) and $275.48 million in FY2021 (+22.7%).
- The Q2 2026 figure is the highest quarterly Operating Expenses in data going back to Q2 2010.
- On a year-over-year basis, Operating Expenses has increased for 22 consecutive quarters, with growth averaging 15.2% over the last eight quarters.
- Across the past five years, year-over-year growth in Operating Expenses ran from 7.9% in Q2 2025 to 28.6% in Q3 2021.
- Per Business Quant, the preceding three quarters came in at $130.26 million (Q1 2026), $131.62 million (Q4 2025) and $127.76 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Infosys | 50.24 Bn | 36.74 Bn | 1.60 Bn | 528.00 Mn |
| 2 | Cognizant Technology Solutions | 31.12 Bn | 24.28 Bn | 1.83 Bn | 812.00 Mn |
| 3 | Wipro | 20.11 Bn | 14.81 Bn | 738.00 Mn | 2.23 Bn |
| 4 | Td Synnex | 19.66 Bn | 13.82 Bn | 1.43 Bn | 784.64 Mn |
| 5 | Cdw | 19.39 Bn | 17.38 Bn | 1.32 Bn | 891.20 Mn |
| 6 | Cgi | 16.87 Bn | 14.67 Bn | - | - |
| 7 | Arrow Electronics | 11.10 Bn | 10.05 Bn | 1.13 Bn | 747.88 Mn |
| 8 | Avnet | 7.54 Bn | 6.72 Bn | 865.03 Mn | 634.01 Mn |
| 9 | EPAM Systems | 6.64 Bn | 2.28 Bn | 429.57 Mn | 245.25 Mn |
| 10 | ExlService Holdings | 6.07 Bn | 4.81 Bn | 225.96 Mn | 138.67 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 138.67 Mn |
| Mar 31, 2026 | 130.26 Mn |
| Dec 31, 2025 | 131.62 Mn |
| Sep 30, 2025 | 127.76 Mn |
| Jun 30, 2025 | 113.05 Mn |
| Mar 31, 2025 | 114.90 Mn |
| Dec 31, 2024 | 112.16 Mn |
| Sep 30, 2024 | 108.86 Mn |
| Jun 30, 2024 | 104.81 Mn |
| Mar 31, 2024 | 101.56 Mn |
| Dec 31, 2023 | 97.58 Mn |
| Sep 30, 2023 | 94.74 Mn |
| Jun 30, 2023 | 86.97 Mn |
| Mar 31, 2023 | 89.73 Mn |
| Dec 31, 2022 | 86.30 Mn |
| Sep 30, 2022 | 80.78 Mn |
| Jun 30, 2022 | 78.49 Mn |
| Mar 31, 2022 | 77.72 Mn |
| Dec 31, 2021 | 75.76 Mn |
| Sep 30, 2021 | 70.14 Mn |
API Access
ExlService Holdings 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=EXLS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "EXLS", "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=EXLS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();