Client
Climate Risk Report

Property counts, EAL, ECL, and average metrics broken down by portfolio segment. Avg EAL/m² = total EAL / total floor area; Avg ECL/m² = total capitalised-current ECL / total floor area. Both use properties with valid floor area ≤ 500 m². Total ECL is capitalised risk, current climate.

Share of properties at each risk level for each of the four climate hazards (current scenario).

Number of properties in each £/m² band, split by hazard and risk level. Bins are £0.50 wide from £0 to £5; properties above £5/m² are in the £5+ row. N/A = no EAL/m² value; Max £/m² = highest observed value per risk level. Cell shading reflects relative count within each hazard table (darker = more properties).

Floor area coverage and data source breakdown by portfolio. Properties above 500 m² are excluded from average calculations. Sources are grouped as Client provided (submitted directly) or SkenarioLabs (derived from OS MasterMap / defaults).

How precisely each property was geocoded. Rooftop matches are the most accurate and typically have EAL values available. Non-rooftop matches (street-level or postcode/city centroid) are less precise and EAL is generally not available for those properties.

Expected Annual Loss (EAL) is a property-level risk measure: it converts the probability and severity of physical climate hazards into an average annual financial loss at the asset. Expected Credit Loss (ECL) by contrast, is a lending measure: it translates climate impacts into the bank's expected credit loss through changes in probability of default (PD), loss given default (LGD) and exposure at default (EAD).

Because they measure different things they should not be expected to move in a one-to-one way. In practice, this means that climate-driven damage or value impairment does not automatically become a credit loss for the lender. The effect depends on borrower resilience, current and stressed loan-to-value position, cure rates, foreclosure assumptions, discounting, and the timing of losses within the ECL framework. As a result, two properties with similar EALs can produce quite different ECL outcomes, while some assets with visible annual climate risk may still show limited ECL impact if there is sufficient collateral headroom or low default sensitivity.

Tail risk is integrated by recognising that climate losses are not only driven by average annual outcomes, but also by relatively rare, high-severity events that can materially worsen credit performance. While EAL smooths these events into a long-run annual average, ECL is more sensitive to the way tail events affect default behaviour and collateral recovery under stress. A severe flood, subsidence event or transition shock may cause a step-change in PD or LGD, even if its contribution to average annual loss is modest. This is why ECL results can differ materially from EAL-based intuition: EAL captures the expected physical damage cost, whereas ECL captures the lender's share of loss after borrower behaviour, capital structure and recovery mechanics are taken into account. In other words, EAL is an input to understanding climate exposure, but ECL reflects how that exposure is transmitted through the credit model, including nonlinear effects from extreme but plausible downside scenarios.

We have sought to align the methodology as closely as possible with established lender risk processes and credit loss frameworks, rather than treating climate risk as a separate or purely theoretical overlay. This means using EAL as an input to assess how climate-related damage and value impairment may feed through into the core components of lender loss modelling — principally PD, LGD and collateral recovery assumptions — in a manner that is consistent with how Client already assess credit risk. Where possible, the approach follows the logic of existing impairment and stress-testing practices, so that climate risk is translated into terms that are comparable with wider portfolio risk management. The intention is therefore not to replace lender models, but to provide a structured and decision-useful way of integrating climate-related asset risk into familiar credit risk processes.

All portfolio properties plotted by geolocation. Markers are colour-coded by portfolio. Use the filters to narrow the view by portfolio, hazard type, risk level or EAL range, then click Apply.