Intercorp Financial Services (IFS) Price to Earnings (2019 - 2026)
Intercorp Financial Services' (IFS) Price to Earnings stood at 3.02 in the quarter ended Jun 30, 2026, up 32.7% from 2.28 a year earlier and up 13.2% from the prior quarter.
Powered by 
Analysis
Intercorp Financial Services (IFS) Price to Earnings (2019 - 2026) Analysis & Trends
For the year ended Dec 31, 2025, Intercorp Financial Services' Price to Earnings came in at 2.42, down 4.7% from the prior year.
- Across earlier years, Price to Earnings came in at 2.54 in the year ended Dec 31, 2024 (+9.2%), 2.33 in the year ended Dec 31, 2023 (+762.3%), 0.27 in the year ended Dec 31, 2022 (-84.0%) and 1.69 in the year ended Dec 31, 2021 (-82.6%).
- The figure for the quarter ended Jun 30, 2026 is the highest quarterly Price to Earnings since the quarter ended Mar 31, 2021.
- On a year-over-year basis, Price to Earnings rose in six of the last eight quarters, with growth averaging 31.3%.
- Peak year-over-year performance for Price to Earnings in the last five years was growth of 89.5% in the quarter ended Dec 31, 2024, against a decline of 93.0% in the quarter ended Sep 30, 2021 at the low end.
- Per Business Quant, the preceding three quarters came in at 2.67 (quarter ended Mar 31, 2026), 2.43 (quarter ended Dec 31, 2025) and 2.33 (quarter ended Sep 30, 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Jpmorgan Chase | 883.45 Bn | 912.92 Bn | - |
| 2 | Banco Santander Chile | 401.52 Bn | 521.46 Bn | - |
| 3 | Bank Of America | 377.43 Bn | -1,998.64 Bn | - |
| 4 | Hsbc Holdings | 330.31 Bn | 330.37 Bn | - |
| 5 | Morgan Stanley | 299.17 Bn | -209.92 Bn | - |
| 6 | Royal Bank Of Canada | 274.08 Bn | 124.82 Bn | - |
| 7 | Mitsubishi Ufj Financial | 270.70 Bn | -1,317.79 Bn | 10.89 Bn |
| 8 | Goldman Sachs | 263.13 Bn | -3,293.98 Bn | - |
| 9 | Wells Fargo & Company | 243.64 Bn | 245.78 Bn | - |
| 10 | Intercorp Financial Services | 5.91 Bn | 5.98 Bn | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 3.02 |
| Mar 31, 2026 | 2.67 |
| Dec 31, 2025 | 2.43 |
| Sep 30, 2025 | 2.33 |
| Jun 30, 2025 | 2.28 |
| Mar 31, 2025 | 2.34 |
| Dec 31, 2024 | 2.56 |
| Sep 30, 2024 | 1.59 |
| Jun 30, 2024 | 1.52 |
| Mar 31, 2024 | 1.57 |
| Dec 31, 2023 | 1.35 |
| Sep 30, 2023 | 2.18 |
| Jun 30, 2023 | 1.78 |
| Mar 31, 2023 | 1.73 |
| Dec 31, 2022 | 1.63 |
| Sep 30, 2022 | 1.52 |
| Jun 30, 2022 | 1.85 |
| Mar 31, 2022 | 2.40 |
| Dec 31, 2021 | 1.70 |
| Sep 30, 2021 | 1.35 |
API Access
Intercorp Financial Services Price to Earnings 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=price-to-earnings&ticker=IFS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "price-to-earnings", "ticker": "IFS", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=price-to-earnings&ticker=IFS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();