Banking Law and Physical Climate Risk Modeling in Spain

Physical climate risk modeling in Spanish banking concerns the methods banks use to estimate how floods, drought, heatwaves, wildfires, storms, water scarcity and other climate hazards could affect borrowers, collateral, cash flows, credit losses and ultimately bank capital.

This is becoming an important part of prudential banking supervision. Spanish banks operate within the EU Banking Union, so climate-risk expectations come from both Spanish law and European banking authorities.

A key point is that physical climate risk is different from transition risk:

• Physical risk: financial damage caused directly or indirectly by climate hazards.
• Transition risk: financial consequences of moving toward a lower-carbon economy, such as carbon pricing, regulation or technological change.

This explanation focuses on physical risk modeling.

1. Legal foundation in Spain

The main legal and regulatory sources include:

• Law 7/2021 of 20 May on Climate Change and Energy Transition;
• Law 10/2014 on the organisation, supervision and solvency of credit institutions;
• the EU Capital Requirements Regulation (CRR);
• the EU Capital Requirements Directive (CRD);
• ECB supervisory expectations concerning climate and environmental risks;
• EBA guidelines and supervisory standards;
• EU sustainability-disclosure and taxonomy legislation where relevant.

For Spanish banks, climate-risk modeling therefore forms part of a broader risk-management and prudential-supervision framework.

2. Law 7/2021 and the Spanish financial sector

Spanish Law 7/2021 on Climate Change and Energy Transition is particularly significant.

It recognises the importance of climate-related financial risks and establishes disclosure and reporting expectations for the financial sector.

The law requires relevant financial entities to provide information concerning, among other matters:

• the impact of climate risks on their financial activity;
• exposure to climate-related risks;
• strategies for addressing those risks;
• alignment with climate objectives.

This makes climate risk more than a voluntary ESG exercise.

For banks, climate-risk information can feed into:

risk management → credit assessment → provisioning → capital planning → disclosures.

3. Why physical-risk modeling matters to banks

Consider a Spanish bank with a €2 billion mortgage portfolio.

Suppose:

• 30% of collateral is in flood-prone areas;
• 20% is exposed to significant heat stress;
• agricultural borrowers face increasing drought exposure.

The bank cannot properly assess future credit risk simply by examining:

current income + current collateral value.

It also needs to consider:

How could physical climate hazards change the borrower's ability to repay and the value of the collateral?

That is the purpose of climate-risk modeling.

4. Main physical climate hazards in Spain

A Spanish bank may model exposure to:

Flooding

Particularly important for:

• mortgages;
• commercial property;
• industrial facilities;
• agricultural assets.

Drought

Potentially important for:

• agriculture;
• food production;
• water-intensive industries;
• utilities.

Extreme heat

Potential consequences include:

• lower labour productivity;
• increased cooling costs;
• infrastructure damage;
• agricultural losses.

Wildfires

Relevant to:

• residential property;
• tourism;
• forestry;
• agricultural borrowers;
• infrastructure.

Coastal risks

Relevant to:

• coastal real estate;
• tourism;
• ports;
• infrastructure.

Storms

Can cause:

• property damage;
• business interruption;
• insurance losses;
• supply-chain disruption.

5. Physical risk has two dimensions

Banks commonly distinguish between:

Acute physical risk

Sudden events.

Examples:

• flood;
• wildfire;
• storm;
• heatwave.

Chronic physical risk

Longer-term changes.

Examples:

• rising average temperature;
• chronic water scarcity;
• sea-level rise;
• long-term agricultural deterioration.

The two can affect the same borrower differently.

6. Hazard → exposure → vulnerability

A useful modeling framework is:

Hazard

What climate event could occur?

↓

Exposure

Which bank assets or borrowers are located there?

↓

Vulnerability

How severely would the borrower or collateral be affected?

↓

Financial impact

How could that affect:

• probability of default;
• loss given default;
• collateral value;
• expected loss?

This structure is important because climate data alone does not equal credit risk.

7. Probability of default

Physical climate risk can increase a borrower's Probability of Default (PD).

Example:

A Spanish agricultural company depends heavily on water-intensive crops.

A drought scenario causes:

• lower production;
• lower revenue;
• higher irrigation costs;
• weaker cash flow.

The bank's model may therefore estimate:

Normal PD: 2%

Severe drought scenario PD: 5%

The exact numerical impact must be supported by appropriate model methodology and evidence rather than simply assumed.

8. Loss given default

Climate risk can also affect Loss Given Default (LGD).

Suppose a bank has:

Loan: €500,000

Property collateral: €700,000

A severe flood damages the property.

Its recoverable market value may fall.

If the borrower subsequently defaults, the bank could recover less than originally expected.

Therefore:

Physical risk → collateral deterioration → higher LGD.

9. Expected credit loss

The basic credit-risk relationship can be expressed conceptually as:

Expected Loss = PD × LGD × Exposure at Default

Climate variables can influence all three components.

For example:

PD ↑ because business cash flow deteriorates.

LGD ↑ because collateral is damaged.

EAD may also change depending upon borrower behaviour and facility structure.

Therefore, physical climate risk can become directly relevant to expected credit losses.

10. Mortgage portfolios

Residential mortgages are a major area for physical-risk modeling.

A Spanish bank may combine:

• property coordinates;
• flood maps;
• wildfire maps;
• heat projections;
• building characteristics;
• loan-to-value ratios;
• insurance information.

Example:

Property A

Location: flood-prone area
LTV: 75%
Building age: high
Flood protection: limited

The bank may classify the exposure as having greater physical-risk sensitivity.

The model should not automatically conclude that the borrower will default. It estimates how the hazard could affect relevant financial variables.

11. Commercial real estate

Commercial property creates additional risks.

A shopping centre or office building can experience:

• physical damage;
• business interruption;
• higher cooling costs;
• insurance-cost increases;
• reduced rental demand.

These factors can affect the property's:

Net operating income → valuation → collateral value → borrower repayment capacity.

12. Agricultural lending

Agricultural finance is particularly sensitive to physical climate risks.

Spanish agricultural borrowers may face:

• drought;
• heat stress;
• changing rainfall;
• crop losses;
• water restrictions;
• wildfire.

Banks may therefore incorporate:

• crop type;
• irrigation dependence;
• geographical location;
• historical yields;
• water availability;
• insurance;
• borrower diversification.

A climate model that simply applies the same drought assumption to every agricultural borrower would be inadequate.

13. Corporate lending

Physical climate risk can also affect manufacturing and services.

For example:

A factory depends on a nearby river for water.

A severe drought reduces water availability.

Production falls.

Revenue declines.

Debt-service capacity deteriorates.

The bank's exposure to the company therefore carries a climate-related credit-risk channel.

14. Geographic data

Climate-risk modeling is heavily dependent on location.

Banks may use:

• latitude/longitude;
• cadastral information;
• flood maps;
• wildfire maps;
• satellite data;
• meteorological data;
• water-stress indicators.

The geographical granularity matters.

A province-level model can conceal significant differences between two properties located only a few kilometres apart.

15. Scenario analysis

Banks should not model only today's climate.

They can use scenarios such as:

Baseline scenario

Climate hazards continue broadly according to a specified reference pathway.

Moderate scenario

Physical risks increase moderately.

Severe scenario

Extreme climate hazards become materially more frequent or severe.

The bank can then assess:

2025 → 2030 → 2040 → 2050

rather than looking only at today's portfolio.

16. Stress testing

Climate stress testing asks:

What happens to the bank if a specified climate scenario occurs?

For example:

Severe drought

↓

Agricultural output falls

↓

Borrower income falls

↓

Defaults increase

↓

Collateral values decline

↓

Bank expected losses increase

↓

Capital ratios are affected.

This is a scenario analysis rather than a prediction that the scenario will definitely occur.

17. ECB climate-risk expectations

The European Central Bank has incorporated climate and environmental risks into its supervisory approach.

ECB expectations have focused on whether banks can:

• identify climate risks;
• measure material exposures;
• integrate them into risk management;
• incorporate them into governance;
• perform scenario analysis;
• reflect them in risk appetite.

Spanish significant banks supervised directly under the Single Supervisory Mechanism are therefore subject to this broader ECB supervisory framework.

18. EBA framework

The European Banking Authority (EBA) has also integrated ESG and climate-related risks into its prudential framework.

Relevant areas include:

• risk management;
• credit policies;
• governance;
• disclosure;
• supervisory reporting;
• scenario analysis.

For Spanish banks, EBA standards interact with national supervisory implementation and ECB supervision.

19. Climate risk and Pillar 2

Climate-related financial risks can become relevant to the Supervisory Review and Evaluation Process (SREP).

If a bank's exposure to physical climate risk is materially underestimated, supervisors may consider whether the bank's:

• governance;
• risk-management framework;
• capital planning;
• stress testing

adequately address the risk.

In serious cases, climate-risk weaknesses can therefore become relevant to supervisory capital expectations.

20. Model risk

Climate models create a special model-risk problem.

Traditional credit models often rely heavily on historical data.

But climate change creates a problem:

Past climate conditions may not reliably represent future conditions.

A flood model based entirely on historical flooding could underestimate future exposure.

Banks therefore need to understand:

• data limitations;
• scenario uncertainty;
• model assumptions;
• geographical resolution;
• parameter uncertainty.

21. Forward-looking modeling

Physical climate risk is inherently forward-looking.

A bank might model:

Historical period: 1990–2020

Near term: 2030

Medium term: 2040

Long term: 2050+

The further into the future the model goes, the greater the uncertainty.

Therefore, banks should generally avoid presenting long-term climate projections as precise forecasts.

22. Data-quality problem

Climate-risk models may combine:

Bank data

with

Climate data

and

Geospatial data.

Each can contain errors.

For example:

A bank's collateral database may show a property at the wrong location.

A climate dataset may operate at a coarse resolution.

The resulting model may produce a misleading risk classification.

Good governance therefore requires data validation and traceability.

23. Insurance interaction

Insurance is an important risk-mitigation factor.

Suppose a property has high flood exposure.

Without insurance:

Flood → borrower/collateral loss → bank exposure

With effective insurance:

Flood → insurance recovery → potentially lower net financial loss

However, banks should not automatically treat insurance as eliminating climate risk.

They should consider:

• coverage;
• exclusions;
• deductibles;
• policy limits;
• insurer solvency;
• renewal risk;
• increasing premiums.

24. Climate risk and collateral valuation

Property valuation is especially important.

A property may currently be worth:

€1 million

But if future flood exposure causes:

• higher insurance premiums;
• reduced buyer demand;
• additional adaptation costs;

its future market value may differ materially.

Banks therefore need to consider whether climate risks can create physical or economic obsolescence.

25. Adaptation

Physical-risk modeling should consider adaptation.

Two buildings in the same flood zone may have different risk profiles.

Building A

• elevated foundation;
• flood barriers;
• drainage improvements;
• effective insurance.

Building B

• no flood protection;
• vulnerable basement;
• limited insurance.

A model treating both properties identically could overstate or understate their relative risk.

Adaptation therefore belongs in the vulnerability analysis.

26. Spanish climate disclosure

Spanish Law 7/2021 contributes to the disclosure framework for climate-related financial risks.

Banks may need to explain matters such as:

• exposure to climate risks;
• management strategy;
• risk-management approach.

The objective is to make climate-related financial exposure more transparent to investors and stakeholders.

This creates an additional governance requirement:

If a bank reports climate risk publicly, its underlying data and methodology should be appropriately controlled.

27. Greenwashing and model integrity

Climate-risk disclosures can create legal and reputational risk if the bank makes unsupported claims.

For example:

"Our loan portfolio is protected against climate risk."

Such a statement could be misleading if the bank's own risk analysis shows substantial exposure.

Banks therefore need consistency between:

internal risk models → regulatory reporting → public disclosures.

28. Relevant case law

There is an important limitation in this field:

Spanish and EU courts have relatively little reported case law specifically deciding whether a bank's physical-climate-risk model complied with prudential banking requirements.

Most important climate litigation concerns government climate obligations, environmental rights, disclosure, or corporate responsibility, rather than the technical validation of a bank's PD/LGD climate model.

The following authorities are nevertheless relevant.

29. Verein Klimaseniorinnen Schweiz v Switzerland, ECtHR, Application No. 53600/20 (2024)

The European Court of Human Rights found that Switzerland had failed to fulfil certain positive obligations concerning protection against serious adverse effects of climate change.

The judgment concerned human rights and state obligations, not bank capital models.

Banking relevance

It demonstrates that climate risk has moved into legally enforceable areas beyond traditional environmental regulation.

For financial institutions, it strengthens the broader legal significance of climate-risk governance.

However, it should not be cited as establishing a specific Spanish banking-model requirement.

30. Urgenda Foundation v State of the Netherlands, Supreme Court of the Netherlands (2019)

The Dutch Supreme Court upheld obligations concerning the state's response to climate change.

This is a Dutch constitutional/human-rights climate case, not Spanish banking litigation.

Relevance

It illustrates the growing judicial recognition of climate risk as a legally significant issue.

For banking research, its importance is indirect: climate-related physical risk can have legally and economically material consequences that financial institutions increasingly need to incorporate into risk governance.

31. CJEU — People's Climate Case, Carvalho and Others v Parliament and Council

The General Court considered a climate-related action challenging aspects of EU climate policy.

The case was principally concerned with standing and EU climate measures rather than banking.

Banking relevance

It illustrates the developing European judicial environment around climate-related regulation, although it does not establish a methodology for bank physical-risk models.

32. AstraZeneca AB v European Commission, CJEU, C-457/10 P

This is not a climate case, but it demonstrates why regulatory and market risks can affect pharmaceutical/banking credit analysis.

It is therefore much less directly relevant than the climate cases above and should not be used as evidence of a specific climate-risk banking obligation.

For a focused legal paper, the stronger approach is to use climate judgments for the broader legal significance of climate risk and prudential legislation/regulatory guidance for the actual banking-model requirements.

33. Case-law table

The first three are comparative/public-law authorities, not Spanish banking cases. It is important not to describe them as establishing a specific legal formula for Spanish bank climate models.

34. Physical-risk modeling and credit governance

A Spanish bank's governance framework can be represented as:

Board

↓

Risk committee

↓

Climate/ESG risk function

↓

Credit-risk department

↓

Climate-risk model

↓

PD/LGD/collateral analysis

↓

Credit decision

This ensures that climate risk becomes part of mainstream risk management rather than remaining exclusively within a sustainability department.

35. Example: Spanish mortgage portfolio

Suppose a bank has:

100,000 mortgages

The bank maps each property against:

• flood exposure;
• wildfire exposure;
• heat exposure;
• coastal exposure.

It then estimates:

Hazard probability

×

Property vulnerability

×

Loan exposure

×

Borrower financial sensitivity

The resulting information can feed into portfolio-level stress testing.

The bank might discover that only 8% of mortgages are geographically exposed to severe flood risk, but those loans represent 15% of total mortgage exposure because properties are concentrated in higher-value locations.

That is much more informative than simply saying:

"8% of properties are climate exposed."

36. Example: agricultural portfolio

Suppose a Spanish bank has:

€1 billion agricultural lending

The bank maps borrowers against drought and water-stress indicators.

A scenario shows:

Severe drought → crop yield reduction → revenue decline → PD increase.

But another borrower has:

• diversified crops;
• irrigation;
• drought-resistant varieties;
• insurance;
• strong liquidity.

Its actual credit impact could be considerably lower.

Thus, a good model incorporates borrower-specific resilience, not merely hazard location.

37. Model validation

A climate-risk model should be independently challenged.

Validation should consider:

• data quality;
• assumptions;
• scenario selection;
• geographic resolution;
• statistical methodology;
• sensitivity;
• limitations;
• adaptation assumptions.

Banks should also document situations where climate data are too uncertain to support precise quantitative conclusions.

38. Legal consequences of poor modeling

If a bank materially fails to identify climate risks, consequences can potentially include:

• supervisory criticism;
• remediation requirements;
• enhanced reporting;
• governance concerns;
• capital-planning consequences;
• reputational damage;
• potential disclosure-related liability where legally applicable.

But an imperfect climate forecast is not automatically a legal violation.

Climate modeling inherently involves uncertainty.

The legal question is generally whether the bank has appropriate governance, methodology, controls and compliance with applicable requirements, rather than whether it predicted the exact future climate outcome.

39. Key compliance checklist

A Spanish bank developing a physical-climate-risk model should consider:

1. Identify material climate hazards
2. Map geographical exposures
3. Assess borrower vulnerability
4. Assess collateral vulnerability
5. Model PD effects
6. Model LGD effects
7. Consider insurance
8. Consider adaptation
9. Run multiple scenarios
10. Test model sensitivity
11. Document uncertainty
12. Validate data
13. Independently validate the model
14. Integrate results into credit risk
15. Reflect material findings in governance and disclosure

40. Overall legal structure

The Spanish framework can be visualised as:

Climate Change Law 7/2021
↓
EU banking legislation — CRR/CRD
↓
ECB supervisory expectations
↓
EBA standards/guidelines
↓
Banco de España supervision
↓
Bank climate-risk governance
↓
Physical-risk data and models
↓
PD / LGD / collateral / stress testing
↓
Credit and capital decisions

Conclusion

Physical climate-risk modeling in Spanish banking is increasingly a prudential risk-management requirement rather than merely an ESG exercise.

The fundamental modeling chain is:

Climate hazard → geographical exposure → vulnerability → borrower/collateral impact → PD/LGD → expected loss → capital and risk management.

Spanish Law 7/2021, EU prudential legislation, ECB supervisory expectations and EBA standards form the principal regulatory environment. The most important practical challenge is that climate risk is forward-looking and uncertain. Historical banking data alone may therefore be insufficient to measure future flood, drought, wildfire, heat and coastal risks.

Case law is still developing. Klimaseniorinnen v Switzerland, Urgenda and the EU People's Climate Case demonstrate the growing legal significance of climate risk, but they do not establish a specific formula for Spanish banks' physical-risk models. The more direct requirements for Spanish banks come from prudential legislation and supervisory standards.

For a Spanish bank, the strongest legal and risk-management approach is therefore to ensure that physical climate risk is incorporated into governance, credit underwriting, collateral valuation, stress testing, capital planning, disclosure and model-risk management, while clearly documenting the assumptions and uncertainty underlying long-term climate scenarios.