Case Study 3

The Need

The PRA consultation paper CP10/25 sets out enhanced supervisory expectations for banks on how to identify, assess, and manage climate-related risks, updating and expanding earlier guidance. In practice, this increases the need for decision-useful internal reporting and credible climate scenario analysis that can be refreshed as data and methodologies evolve. For mortgage lenders, the ability to link loans to property-level climate signals and energy-efficiencycharacteristics provides a practical foundation for producing climate reporting that is consistent, explainable, and repeatable.

The Challenge

The bank needed to strengthen its climate reporting capability without creating a parallel data
estate or a manual process that would be difficult to maintain.

1. Data readiness. Mortgage loan-level data needed to be mapped and structured consistently
   so it could be linked to external datasets and used for repeatable reporting.

2. Property-level enrichment. The bank required a way to overlay its portfolio with climate risk
   data from a leading provider and EPC data from a leading aggregator, so each property could
   be assessed and segmented consistently.

3. Repeatable reporting and scenario analysis. The bank needed to generate a climate report
   and scenario outputs without rebuilding bespoke extracts or reworking the methodology each
   reporting cycle.

What InCol Intelligence delivered

The bank implemented four connected capabilities within InCol Intelligence.

1. Data onboarding and validation. The bank ingested its mortgage loan-level dataset into the
   platform so loan and property fields were consistently mapped and validated ahead of
   enrichment and reporting.

2. Climate enrichment. The bank overlaid its mortgage and property datasets with third-party
   climate-risk data from a leading climate-data provider, enabling consistent property-level
   climate-risk assessment and scenario-based analysis.

3. EPC enrichment and automated Climate Report. The bank enriched each mortgaged
   property with EPC data from a leading data aggregator and used the enriched dataset to
   generate an automated climate report, including scenario analysis across RCP pathways.

Monthly Operating Rhythm

Refresh the mortgage loan-level dataset on the platform.

1. Refresh the mortgage loan-level dataset on the platform.

2. Run automated validation controls and resolve exceptions where required.

3. Refresh climate risk enrichment from the leading climate data provider.

4. Refresh EPC enrichment at property level.

5. Produce the automated climate report, including scenario analysis, and use the same dataset
   for ongoing interrogation of the mortgage book.

Results

The client established a single source of truth for mortgage loan-level data, materially improving confidence for both the originator and its investors. Investors gained transparent, investor-specific access to the mortgages originated for their programme and could interrogate their portfolio each month using consistent data and criteria logic. The same operating model supported multiple forward flow mortgage investors, including a European insurance company and an international investment bank, without creating a separate reporting process for each relationship.