Enterprise Financial Services (EFSC) Prepaid Assets (2010 - 2026)
Enterprise Financial Services (EFSC) posted Prepaid Assets of $731.5 million for Q3 2026, up 33.8% from $546.6 million a year earlier and up 14.5% from the prior quarter.
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Analysis
Enterprise Financial Services (EFSC) Prepaid Assets (2010 - 2026) Analysis & Trends
At the end of FY2025, Enterprise Financial Services' Prepaid Assets came in at $648.83 million, up 39.5% from FY2024.
- Annual Prepaid Assets shows a five-year compound annual growth rate of 15.3% (FY2020 to FY2025).
- In prior years, Enterprise Financial Services' Prepaid Assets was $465.22 million in FY2024 (-2.5%), $476.93 million in FY2023 (+13.9%), $418.77 million in FY2022 (+23.6%) and $338.74 million in FY2021 (+6.3%).
- The Q3 2026 figure stands as the highest quarterly Prepaid Assets in data going back to Q4 2010.
- On a year-over-year basis, Prepaid Assets has increased in each of the last seven quarters, with growth averaging 19.3% over the last eight quarters.
- The strongest year-over-year quarter for Prepaid Assets in the past five years was Q4 2025, with growth of 39.5%; the weakest was Q3 2024, with a decline of 5.3%.
- According to Business Quant data, Prepaid Assets for the three prior quarters was $638.63 million (Q2 2026), $635.77 million (Q1 2026) and $648.83 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Jpmorgan Chase | 909.02 Bn | 886.77 Bn | - |
| 2 | Banco Santander Chile | 406.67 Bn | -7,110.43 Bn | - |
| 3 | Bank Of America | 350.91 Bn | -2,025.20 Bn | - |
| 4 | Hsbc Holdings | 308.71 Bn | -2,966.46 Bn | - |
| 5 | Morgan Stanley | 293.66 Bn | -249.15 Bn | - |
| 6 | Royal Bank Of Canada | 283.56 Bn | -546.44 Bn | - |
| 7 | Goldman Sachs | 262.71 Bn | -3,480.74 Bn | - |
| 8 | Wells Fargo & Company | 257.44 Bn | 92.87 Bn | - |
| 9 | Mitsubishi Ufj Financial | 256.82 Bn | -75.42 Bn | 10.89 Bn |
| 10 | Enterprise Financial Services | 2.23 Bn | -4.32 Bn | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 731.50 Mn |
| Jun 30, 2026 | 638.63 Mn |
| Mar 31, 2026 | 635.77 Mn |
| Dec 31, 2025 | 648.83 Mn |
| Sep 30, 2025 | 546.60 Mn |
| Jun 30, 2025 | 514.56 Mn |
| Mar 31, 2025 | 508.08 Mn |
| Dec 31, 2024 | 465.22 Mn |
| Sep 30, 2024 | 450.68 Mn |
| Jun 30, 2024 | 477.61 Mn |
| Mar 31, 2024 | 481.29 Mn |
| Dec 31, 2023 | 476.93 Mn |
| Sep 30, 2023 | 475.66 Mn |
| Jun 30, 2023 | 408.75 Mn |
| Mar 31, 2023 | 398.11 Mn |
| Dec 31, 2022 | 418.77 Mn |
| Sep 30, 2022 | 426.48 Mn |
| Jun 30, 2022 | 396.12 Mn |
| Mar 31, 2022 | 370.38 Mn |
| Dec 31, 2021 | 338.74 Mn |
API Access
Enterprise Financial Services Prepaid Assets 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=prepaid-assets&ticker=EFSC&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "prepaid-assets", "ticker": "EFSC", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=prepaid-assets&ticker=EFSC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();