Climate Risk meets Credit Risk: What Module 7 and the EBA ESG Guidelines mean for Banks

The integration of ESG risks into the prudential framework through CRR3 and CRD VI has produced two distinct sets of obligations for institutions. On the one hand, ESG risk management has become part of the regulatory framework applicable to institutions, with supervisory expectations on how C&E (Climate & Environmental) factors should be reflected in credit processes, internal models and collateral valuation. On the other hand, the EBA has been mandated to develop ITS on supervisory reporting of ESG risks, to allow competent authorities to monitor and assess institutions’ compliance consistently across Member States.

Both components of the framework are usually discussed separately. The first belongs to risk management and is associated with the EBA Guidelines on the management of ESG risks, applicable since 11 January 2026, and from 11 January 2027 at the latest for small and non-complex institutions. The second belongs to supervisory reporting and has taken shape through the proposed Module 7 on ESG reporting: published for consultation in April 2026 and expected to apply from the 30 September 2027 reporting reference date.

Considered together, they describe a single regulatory objective observed from two distinct angles. C&E information is being introduced into credit risk processes, while credit risk parameters are being introduced into C&E reporting templates. The supervisor is therefore advancing on both risk measurement and disclosures, asking institutions to recognise C&E drivers within their assessment of borrower risk and, at the same time, asking them to report conventional risk parameters along C&E dimensions.

This article examines both components of the framework and the conditions under which C&E factors can currently be integrated into credit risk parameters.

3.1 The EBA Consultation and Module 7

Reporting credit risk along C&E dimensions is a recent component of the framework. In April 2026 the EBA launched a public consultation on a major revision of its Implementing Technical Standards (ITS), as part of its effort to create a supervisory reporting simplification package. A key element of the proposal is the introduction of Module 7, which establishes a dedicated supervisory reporting framework for ESG risks. The consultation closed in July 2026, and assuming a go-ahead, the new requirements are expected to be applied from the 30 September 2027 reporting reference date onwards.

Unlike existing ESG disclosures, which mainly focus on market transparency, Module 7 introduces ESG reporting into the prudential supervisory framework through a dedicated data collection process. 

3.2 What Changes in the Templates

The most significant aspect in the proposal is that the existing transition risk and physical risk templates have been expanded, instead of being replaced by a separate C&E reporting framework. Template D01.00 for transition risk and Template D05.00 for physical risk now include credit risk metrics, additional financial information and more granular C&E classifications. As a result, ESG reporting no longer focuses exclusively on C&E exposures but, instead, combines C&E and credit risk information within the same supervisory framework.

Under the previous framework, institutions primarily reported exposures most exposed to C&E risks, classified by sector, geography and other characteristics (hazard, emissions intensity, etc.). Module 7 retains these dimensions but complements them with credit risk indicators such as PD (both on a twelve month and on a lifetime basis), LGD and LTV.

The EBA proposes that template D 01.00 applies only to large institutions with total assets of at least EUR 30 billion, while template D 05.00 applies to all large institutions.

3.3 Transition Risk: Template D01.00

For transition risk, Template D01.00 extends the analysis beyond credit quality by introducing:

• gross interest income;

• gross fee and commission income;

• the Transition Rate (TR): that is, the probability of an exposure moving between stages during the year;

• the Lifetime Loss Rate (LRLT): the lifetime loss rate applied to stage 2 exposures. 

These additional details allow supervisors to assess not only the potential risk associated with transition sensitive portfolios, but also their economic relevance and their expected evolution over time.

3.4 Physical Risk: Template D05.00

For physical risk, the most significant enhancement is the increased granularity of exposure classification. Instead of distinguishing only between exposed and non-exposed assets, institutions must now differentiate between highly and moderately exposed assets. Combined with the new credit risk metrics, this provides a clearer picture of portfolio vulnerability. Supervisors can identify not only whether a property is in an area exposed to a physical hazard, but also whether the same exposure is associated with a high PD, an elevated LTV or other signs of weaker credit quality.

The added value of the revised framework therefore comes from combining C&E information with prudential metrics within the same reporting templates. This allows supervisors to identify areas of concentration, where C&E-related vulnerabilities coincide with weaker credit quality. This approach provides a richer understanding of portfolio risk compared to when both dimensions (C&E and credit risk) were assessed individually.

3.5 Implementation Challenges and Implications

In practice institutions face three main operational hurdles in producing this information:

• many required C&E data points are not yet systematically available across portfolios; 

• C&E data, financial reporting and prudential risk parameters are traditionally managed through separate legacy systems, each with its own methodology and validation rules; 

• unlike financial reporting, which is largely derived from established accounting systems, C&E data requires separate mapping and sourcing. Hence, reconciling these distinct data flows at exposure level becomes one of the main implementation challenges.

As C&E information becomes directly linked to prudential indicators, the quality of physical risk models, hazard maps and exposure classifications becomes increasingly relevant to supervisory reporting. Weak data or simplified modelling assumptions no longer affect only disclosures but also influence the overall risk profile presented to supervisors.

Supervisory reporting therefore becomes an indirect indicator of the robustness of an institution's C&E risk modelling framework. Weaknesses in hazard mapping, exposure classification or data quality are more likely to translate into visible concentrations within reported portfolios.

The consequence is that C&E data is no longer used solely for compliance purposes. It becomes part of prudential risk analysis, encouraging institutions to progressively embed C&E considerations into existing credit risk processes rather than treating them as a standalone ESG reporting exercise.

3.6 Segmentation, Not Measurement

C&E information, however, is used to segment exposures, not to measure the prudential parameters themselves. Module 7 does not require parameters recalibrated on C&E drivers. It requires conventional parameters, produced by existing models, grouped along C&E dimensions.

Indeed, as previously mentioned, a direct integration of C&E factors within credit risk modelling remains complex. Two conditions would have to be met to achieve robust modelling practices, and neither is generally met today. The first is historical depth: model performance is assessed against observed past defaults, which makes it difficult to validate factors that have not yet materialised or been measured. The second concerns information content: where a C&E factor has already affected a counterparty, its impact is typically visible in financial statements and collateral values before default, so a C&E variable tends to be correlated with drivers already in the model. Direct inclusion is justified where the factor captures a genuine residual relationship, not already explained by existing drivers.

Hence, upcoming reporting standard will apply C&E factors as a means of segmentation rather than measurement. The expectation is that, over successive reference dates, segmented reporting will build the observational base that is currently lacking for direct inclusion in prudential risk model estimation.