Climate risk continues to be a concern for global real estate, but are there ways to manoeuvre this very real risk with building data? So often climate risk scores don’t take into account what’s going on inside an asset, so could dynamic data help asset owners and operators understand their own performance, and in turn their own risk? We break down the realities.
Physical and transition risk assessments have become a fixture of institutional real estate, from SFDR disclosures through to insurer-style scenario modelling. The scale of what’s at stake makes clear why: The OECD’s 2025 real estate risk report puts real estate value across OECD countries at $111 trillion, nearly double total GDP, much of it exposed to floods, fires and heatwaves as well as the regulatory pressures of the transition itself.
These frameworks are essential, but they’re built top-down: Historical data, regional climate projections, and asset-class assumptions applied downward onto a portfolio. What they rarely include is a live account of how an individual building, and the people living in it, are actually responding as conditions shift. A portfolio can carry a favourable risk score while residents inside it are already experiencing the early signs of a problem the model hasn’t caught up to yet.
Climate Risk Is Modelled, Not Observed
Most climate risk assessment today answers a probabilistic question: Given this location, this building type and this climate scenario, what’s the likely exposure? Useful for underwriting and disclosure, certainly, but backward-looking or speculative by nature, drawing on historical weather patterns, EPC ratings taken at a point in time, and regional projections applied uniformly across very different buildings.
Even CBRE’s own research on transition risk points to this limitation. Its Econometric Advisors team has argued that greater data availability and transparency will lead to better informed decisions, a modest claim on the surface, but a telling one from a firm that builds climate risk models for a living.
What most models don’t draw on is the asset’s own behaviour under stress. Two buildings with identical risk scores can perform very differently during the same heatwave or cold snap, depending on fabric, systems and how residents actually use them. Without granular, real-time data from inside the building, that difference stays invisible until it surfaces somewhere costlier, whether that’s a valuation review or a compliance gap. This is the gap The Utopi Platform is built to close, connecting the risk a model assigns to an asset with the room-level evidence of whether that risk is actually playing out.
Where Utopi Fits
The work Utopi has done with Harrison Street Real Estate’s Spanish PBSA portfolio shows what closing that gap looks like in practice, and why it matters commercially. Across nine assets in five Spanish cities, from Barcelona to Salamanca, The Utopi Platform aggregates room-level heating, HVAC and solar generation data into portfolio-wide benchmarks. That gives Harrison Street’s asset management team the visibility to spot underperforming spaces early, and it feeds directly into capex planning and exit strategy decisions further down the line. For an Asset Manager weighing where to spend next, or an Investor assessing what they’re buying into, that’s the difference between a valuation built on assumptions and one built on a verified performance record.
That case sits within a wider evidence base of over 60 billion granular data points, gathered across 87,000 rooms in 13 countries, on how residents heat, occupy and experience their homes. The Utopi Platform sits underneath climate risk modelling rather than replacing it, giving operators and investors the room-level evidence that shows whether the exposure a model predicts is actually materialising, and where. Two signals make that materialisation visible well before it reaches a model: How residents heat their homes under stress, and how transition costs land unevenly depending on that same behaviour.
Heating Behaviour: The Earliest Signal
Of all the signals available, heating behaviour tends to move first. A heatwave pushing internal temperatures up, or a cold snap driving sustained heating demand, shows up in occupancy and heating patterns long before it reaches an EPC downgrade or an insurance claim.
In the Utopi case study with Downing Students, one room reached 40°C. Room-level data and a Smart TRV brought that same room down by over 16°C, without any separate cooling infrastructure, a cooling story hiding inside what most operators still treat as a heating problem. Across their wider portfolio, Downing Students saw the pattern at scale, delivering a 52% reduction in overheated spaces through Smart TRVs and Multisensor data. As Bay Downing, Joint CEO of Downing, put it, centralised controls have been “a game changer” even in gas-heated assets, where energy prices bite less hard than electricity but the behavioural waste is just as real. A standard climate risk score would have missed both results entirely. The heating data caught them well ahead of time.
Transition Risk Beyond Carbon Compliance
Transition risk conversations in European real estate tend to centre on carbon compliance costs, EPC targets and retrofit obligations chief among them. France’s Certificats d’Économies d’Énergie (CEE) scheme is a good example of the mechanisms operators are already navigating, requiring major energy suppliers to fund efficiency upgrades across homes and businesses. It’s a real, present cost of transition, and one that gets modelled carefully.
What gets modelled far less carefully is occupant-driven energy demand itself, the heating behaviour that determines how much of that efficiency gain actually gets realised. Two buildings receiving the same retrofit under a scheme like CEE can post very different energy outcomes afterwards, depending on how residents heat their homes and how well that behaviour is understood and supported. That’s a behavioural risk sitting alongside the compliance one, and a harder one to see without room-level data.
A More Honest Picture of Resilience
Climate risk models describe exposure. Bridging the gap between that description and what’s actually happening, room by room, season by season, turns climate risk from an abstract score into something a portfolio can see, understand and act on as conditions shift.
Resilience is often described in terms of what a building can withstand on paper. Granular, real-time data offers a more honest picture, showing whether an asset is actually coping with a changing climate, as it happens, rather than whether it should be. That distinction is only going to matter more.
For more information on how Utopi can support your Climate Risk strategy, get in touch.