Company: BCDRF
Filing Date: 2025-02-28
Form Type: 20-F
Source: 0000891478-25-000054
Chunk: 552

Company: Banco Santander, S.A.
Filing Date: 2025-02-28
Form: 20-F
Chunk 552
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 not the highest one based on exponential and uniform weightings.

We calculate ES as expected loss above VaR at a 99% confidence level. We also weight all observations the same. Unlike VaR, ES has the advantage of showing tail risk (i.e. the risk of loss due to a rare event) while being a subadditive metric. According to the Basel Committee, 97.5% ES is a risk level similar to 99% VaR.

c) Scenario analysis

Santander’s risk measures are based on normal market conditions, price stability, sufficient liquidity and other assumptions used in daily risk management and decision-making. However, some extreme movements and vast unforeseen changes might not be properly anticipated.

Scenario analysis enables us to recognize unexpected outcomes and estimate how much capital could be needed to absorb losses stemming from those outcomes.

We regularly calculate and review stress test scenarios for all the trading books of the Group and our subsidiaries, such as:

Historical scenarios

Historical scenarios consider trading portfolio performance during a crisis or significant past market events to estimate maximum losses based on existing positions.

Hypothetical scenarios

We use extreme scenarios based on market risk shocks that do not relate to past events (e.g. abrupt crisis with strong movements in all risk factors, worst-case scenarios, scenarios based on regulatory stress exercises, and forward-looking scenarios). Unlike generally ex post historical scenarios, hypothetical scenarios are ex ante.

Reverse stress test scenarios

Reverse stress test scenarios indicate loss-causing market variables that may compromise the bank’s survival. They supplement traditional stress test scenarios and point out potentially vulnerable business areas, hidden risks and correlations between risk factors.

Climate change scenarios

We use climate change scenarios to measure the potential impact of current exposure to climate-sensitive economic activities on trading portfolios resulting from climate and environmental risks. They include both exposure to physical risk and transition risk.

Other stress test scenarios

In addition to the above scenarios, we conduct other stress tests every quarter to identify potential losses or significant impacts on capital arising from extreme market movements (e.g. IRC scenarios, proxy stress scenarios in the VaR calculation stress scenarios in valuation adjustments).

d) Calibration and backtesting

According to regulation, the VaR model must accurately show material risks. Because VaR uses statistical techniques under normal conditions for a certain confidence level over a set time horizon, the estimate of maximum potential loss may differ from actual losses. We review and contrast the VaR calculation model on a regular basis to verify its accuracy.

We run internal backtesting, contrast VaR and review assumptions about