ExlService Holdings (EXLS) Operating Leases (2019 - 2026)
ExlService Holdings (EXLS) posted Operating Leases of $88.13 million for Q2 2026, up 41.2% from $62.4 million a year earlier and up 4.6% from the prior quarter.
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Analysis
ExlService Holdings (EXLS) Operating Leases (2019 - 2026) Analysis & Trends
At the end of FY2025, ExlService Holdings' Operating Leases came in at $88.17 million, up 47.3% from FY2024.
- Annual Operating Leases has increased for three consecutive years, with a five-year compound annual growth rate of 0.8% (FY2020 to FY2025).
- In prior years, ExlService Holdings' Operating Leases was $59.85 million in FY2024 (+2.9%), $58.18 million in FY2023 (+20.8%), $48.16 million in FY2022 (-29.7%) and $68.51 million in FY2021 (-19.3%).
- Quarterly Operating Leases has run from a low of $45.66 million in Q1 2023 to a high of $88.17 million in Q4 2025 over five years.
- On a year-over-year basis, Operating Leases has increased in each of the last three quarters, with growth averaging 19.2% over the last eight quarters.
- The strongest year-over-year quarter for Operating Leases in the past five years was Q4 2025, with growth of 47.3%; the weakest was Q1 2023, with a decline of 31.0%.
- According to Business Quant data, Operating Leases for the three prior quarters was $84.28 million (Q1 2026), $88.17 million (Q4 2025) and $60.46 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Infosys | 50.24 Bn | 36.74 Bn | 1.60 Bn |
| 2 | Cognizant Technology Solutions | 31.12 Bn | 24.28 Bn | 1.83 Bn |
| 3 | Wipro | 20.11 Bn | 14.81 Bn | 738.00 Mn |
| 4 | Td Synnex | 19.66 Bn | 13.82 Bn | 1.43 Bn |
| 5 | Cdw | 19.39 Bn | 17.38 Bn | 1.32 Bn |
| 6 | Cgi | 16.87 Bn | 14.67 Bn | - |
| 7 | Arrow Electronics | 11.10 Bn | 10.05 Bn | 1.13 Bn |
| 8 | Avnet | 7.54 Bn | 6.72 Bn | 865.03 Mn |
| 9 | EPAM Systems | 6.64 Bn | 2.28 Bn | 429.57 Mn |
| 10 | ExlService Holdings | 6.07 Bn | 4.81 Bn | 225.96 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 88.13 Mn |
| Mar 31, 2026 | 84.28 Mn |
| Dec 31, 2025 | 88.17 Mn |
| Sep 30, 2025 | 60.46 Mn |
| Jun 30, 2025 | 62.40 Mn |
| Mar 31, 2025 | 61.41 Mn |
| Dec 31, 2024 | 59.85 Mn |
| Sep 30, 2024 | 62.34 Mn |
| Jun 30, 2024 | 64.41 Mn |
| Mar 31, 2024 | 59.88 Mn |
| Dec 31, 2023 | 58.18 Mn |
| Sep 30, 2023 | 48.45 Mn |
| Jun 30, 2023 | 50.58 Mn |
| Mar 31, 2023 | 45.66 Mn |
| Dec 31, 2022 | 48.16 Mn |
| Sep 30, 2022 | 54.17 Mn |
| Jun 30, 2022 | 59.22 Mn |
| Mar 31, 2022 | 66.17 Mn |
| Dec 31, 2021 | 68.51 Mn |
| Sep 30, 2021 | 73.94 Mn |
API Access
ExlService Holdings Operating Leases 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-leases&ticker=EXLS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-leases", "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-leases&ticker=EXLS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();