Company: BCDRF
Filing Date: 2025-03-03
Form Type: 6-K
Source: 0000891478-25-000057
Chunk: 122

Company: Banco Santander, S.A.
Filing Date: 2025-03-03
Form: 6-K
Chunk 122
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 for measuring and managing market risks, in 2024 Grupo Santander regularly carried out the necessary analyses and tests, obtaining conclusions that confirm the reliability of the model.

#### Number of overshootings
Overshooting occurs whenever the losses or gains observed in a day exceed the VaR estimate. The number (or percentage) of overshootings recorded is one of the most intuitive indicators of a model's accuracy.

When the P&L exceeds the previous day's VaR it is considered to be an overshooting (or exception). The number (or percentage) of overshootings recorded is one of the most intuitive indicators of the models accuracy. A regulatory coefficient "K" is calculated on the basis of the number of overshootings in the regulatory backtesting. This affects the calculation of regulatory capital in accordance with the following table:

192 2024 Pillar 3 Disclosures Report

| Index |     | Introduction |     | Capital |     | Risks |     | Risk taker's remunerations |     | Appendices |

| Backtesting overshootings |     | KR value |
| 0                         |     |        — |
| 1                         |     |        — |
| 2                         |     |        — |
| 3                         |     |        — |
| 4                         |     |        — |
| 5                         |     |     0.40 |
| 6                         |     |     0.50 |
| 7                         |     |     0.65 |
| 8                         |     |     0.75 |
| 9                         |     |     0.85 |
| 10                        |     |     1.00 |

The confidence level for the VaR calculation is a measure of the number of overshootings expected to occur in a given time frame. For example, if the daily VaR is calculated with a confidence level of 99%, the percentiles of interest are the 1st and the 99th percentiles of the P&L distribution. The expectation would be 2% of overshootings during the days studied (1% due to excess profits and 1% due to excess losses). If there are significantly more (or fewer) overshootings, this might be a sign of problems in the VaR model employed. The observed P&L and estimated VaR data can be used to construct a hypothesis test to check the validity of the VaR/P&L relationship. Time between