The role (and risk) of energy performance data in insurance decision-making

The financial risks relating to climate change typically arise from two key areas:

1.     Physical Risks stem from the direct impact of climate-related events. For example, extreme weather like floods or heatwaves can affect the value and insurability of properties and assets. Recognising these risks signals the need to better protect homes, communities and infrastructure.

2.     Transition Risks emerge as we shift toward a low-carbon economy. Policies and innovations - such as minimum energy efficiency standards - can influence asset values and market dynamics. Staying ahead of these changes allows organisations to adapt and thrive.

Why the energy performance of homes matters to insurers

There is no shortage of risks for the insurance sector to consider:

• Energy-efficient homes present lower risk profiles, reducing claims and improving portfolio performance. [1]
• Regulatory shifts mean landlords, in the private and social rented sector, must meet minimum energy efficiency standards (MEES) [2]
• Poor EPC ratings affect market value as MEES come in. [3]
• Insurers could support clients with innovative products that reduce risk and retain custom.
• Aligning with ESG goals strengthens brand reputation and supports long-term climate resilience. [4]
• Build Back Better decision-making can affect ESG goals and the insurers environmental impact as a result of both embodied carbon emissions and whether the opportunity is taken to retrofit.[5]
• Retrofit upgrades often increase rebuild costs, adding to a wider concern that many properties remain underinsured- a growing exposure. [6]
• Retrofit can eliminate damp and mould, or – done badly – it can exacerbate problems.

It is therefore no surprise that climate risk data, high resolution energy performance data (beyond the limitations of EPC data) and the quality assurance of retrofit upgrades are sought by insurers to support underwriting, asset protection, and customer value.

But the PRA has observed data gaps in the management of climate risks, and asked firms to identify significant data gaps, the plans they have to close these gaps and the processes they have in place to ensure relevant data and tools are incorporated into their approach. [7]

The Importance of High-Quality Data

Insurers need to have full information to manage risks – and with current EPCs valid for ten years they are working with low-resolution and often out of date data.

There are two core characteristics of the data used in retrofit advice and planning that underpin its quality: its level of detail and its source.

Real vs. Synthetic Data: Real data is collected from a real event, while synthetic data is generated by algorithms trained on real data. While synthetic data can fill gaps, it needs to be continuously retrained on good quality data to avoid becoming outdated.

High vs. Low Resolution: High-resolution data provides more detail, which leads to more accurate cost estimates and a wider range of retrofit options. Open EPC data, for example, is a valuable real dataset, but it is low-resolution and only available for about 60% of homes.

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Just as the relationship between these characteristics affects the reliability of advice for homeowners and landlords, it affects its reliability for risk management.

For example, ESG reports reliant on the Government's EPC register won't be accounting for the decarbonisation of electricity supplies, the impact of the new calculation method (RdSAP10) or a true picture of potential improvements.

That may suffice for reporting requirements now, but with Minimum Energy Efficiency Standards incoming, and the impact of the new method on EPC ratings - certainly for some building types - open data is unlikely to give the full picture on MEES risk.

This is why we've recently launched Net Zero Hub - a wrapper for our housing stock model that allows financial services to view high-resolution data for housing, report on financed emissions, carbon performance, affordability, MEES risks and potential for improvement.

With property owner permission, we can ingest and assess real data, but if not we assess our synthetic dataset - which applies algorithms to fill the gaps in open EPC data, intelligent cloning of similar homes, and verifies relevant fields against Ordnance Survey data.

Continual updates, retraining and modelling with the latest RdSAP10 method makes this the most high-resolution view of the energy and carbon performance of homes available.

It is scalable and cost-effective too, used by the landlords of over 2 million homes, local authorities across the country, and in support of our homeowner and small landlord advice service, Ecofurb.

The introduction of the Home Energy Model will impact ratings further – both positive and negative – something anyone working in or adjacent to the property sector will need to rapidly understand in order to understand pathways to compliance with MEES.

This is why Cotality UK continually improves its housing stock model, and makes it available through different wrappers for landlords, homeowners, lenders and others.

This isn’t just about risk - it's about opportunity. An opportunity to nudge or finance homeowners towards retrofit and resilience in the face of a changing climate and energy insecurity. The insurance industry has a unique role to play in supporting retrofit and resilience adoption, protecting asset value, and empowering homeowners and landlords to future-proof their properties.