The investment community is at a crossroads when it comes to climate risk analysis.
The stakes from failing to accurately identify and manage transition and physical climate risks faced by firms across both listed and private capital markets are growing. In parallel, regulatory requirements are diversifying and tightening, and stakeholders are demanding much more than generic estimates of companies’ emissions. Most emissions data providers still rely on outdated methodologies that oversimplify the complexities of a company’s emissions and obscure the underlying risks and opportunities. Industry averages are a convenient shortcut, but they are not able to tell the whole story behind a company’s transition risk outlook.
Modelling emissions data at the company level based on proxies or sector-wide emissions intensity estimates is in most cases little better than an educated guess. It overlooks a swathe of highly relevant information at the level of individual carbon-emitting assets. Companies in the same sector and operating in the same region can have drastically different emissions and emissions intensities, driven by factors such as the technology mix making up their asset portfolio, as well assets’ lifecycles and company-specific operating practices. Fitting every company to the same curve can dangerously skew risks, mask outliers, and undermine the confidence of portfolio managers seeking sustainable returns and hedges against transition risk.
An asset-based approach offers a much more accurate and nuanced understanding of emissions and risks for every company—helpful for regulatory reporting, crucial for accurate financed emissions reporting, and the basis of transparent and actionable portfolio composition and analysis.
What are industry average-based estimates?
Industry average-based estimates typically estimate a company’s emissions based on the industry-wide carbon intensity figure most applicable to it, with regional or national variations in some cases. Industry-wide intensity estimates reflect the average historical emissions data for companies within a specific industry. Other methods use emission factors from Environmentally-Extended Input Output (EEIO) models maintained by public bodies such as the US EPA or the EU. One of the most common methodologies used by data providers is a revenue-based fallback approach that correlates average emission intensities with company revenues. In each case, the industry-level approach assumes that companies in the same industry will have comparable carbon intensity ratios.
What is asset-based data?
At Asset Impact, we’ve developed and honed an asset-based approach. We identify and profile every physical asset – and its corporate owner(s) – in the 11+ sectors that we cover to retrieve or estimate the emissions associated with them across different scopes of activity. We work with highly specialized asset-level data providers to understand and model the relevant characteristics of each asset. For each one, we provide both activity metrics (e.g. tonnes of fuel used), and physical emission intensity factors (e.g. tonnes of CO2-equivalent per tonne of fuel) used to model the absolute emissions (e.g. tonnes of CO2-equivalent per year) associated with each asset. In doing so, we consider assets’ geographic locations, the technologies they use, and the stage of their lifecycle they are in. In the final step, we link every individual asset to both direct and indirect owners using transparent and consistent consolidation methodologies.
When rolled up from the asset-level to the company-level, insights are based on real world outcomes. This creates a detailed, consistent, and comparable understanding of a company’s emissions that goes far beyond generic averages.
Graph 2 demonstrates how asset-based data provides much greater detail than averaging approaches and allows investors to ask much more precise questions when identifying investment opportunities and building shareholder engagement strategies. With the underlying asset-level data at hand, it’s possible to dig into understanding exactly what drives a company’s climate performance, and how this compares not just to the industry as a whole, but to specific peers. For example, some companies in the steel sector primarily use state-of-the-art electric arc furnaces powered by renewable energy, while others rely on coal-based blast furnaces, and still others use a combination of both, resulting in dramatically different physical emissions intensities. By contrast, applying the same emissions intensity to all facilities or companies without proper justification would obscure the significant differences across these three cases and can result in misinformed investment strategies or misaligned risk assessments.
Limitations of industry averages for investors
While industry average approaches are by their nature not transparent, they also pose significant risks to investors using the resulting numbers for several reasons:
- They tend to overestimate emissions for larger, more efficient companies with a cleaner, more advanced asset base;
- They are most uncertain for small-cap and emerging market firms subject to myriad company-specific factors that diverge from broad industry trends;
- They apply issuer-level average emissions intensity figures to subsidiaries in different industries and locations, which further dilutes accuracy and risks skewing overall risk assessment;
- They are backward-looking and do not account for ongoing and future investments in electrification, clean technology adoption, process improvements, and carbon capture technologies.
- They are sensitive to outliers generated by companies with exceptionally high or low emissions, which can affect the overall average and create a misleading impression of individual company performance.
Raising the bar for climate data quality
Many data providers still prioritize coverage over accuracy, relying heavily on estimates and models. While this can be convenient, it leaves financial institutions exposed in their climate risk analysis. Yet, Asset Impact covers over 65,000 listed and unlisted companies in 11 sectors, demonstrating that new approaches can offer investors both high levels of transparency and detail without compromising on coverage.
For banks and asset managers in Europe and North America, climate regulations like ISSB S1 and S2, SFDR, TCFD, and the EU Taxonomy are raising the bar for transparency and precision. These requirements demand robust data, enabling financial institutions to accurately measure climate risk and financed emissions.
As financial institutions continue to further integrate climate risk into their risk management processes moving away from easy but risky shortcuts like industry proxies is critical. Asset-based data offers the depth and transparency needed to assess risks accurately and allocate resources responsibly. In a landscape where average estimates clearly no longer suffice, this approach ensures financial institutions are prepared for both regulatory challenges and market expectations.
Learn more about our asset-based approach here or contact us to have your questions answered.