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Beyond Assumptions: How Asset-Level Data Enhances Sustainable Finance

In the past few years, we have seen how financial choices can impact our environment. This sparked a conversation about the need for clearer insights into sustainable finance. To deepen our understanding of this issue, we welcomed Dr. Alex Clark, a recent graduate from the Smith School of Enterprise and the Environment at the University of Oxford and now the Research Director at Asset Impact, a provider of cross-sectoral asset-based data for climate transition risk analysis. Alex is deeply engaged in the space of sustainable finance, with a special focus on greenhouse gas (GHG) emissions data. In his talk on 24 October, hosted by the Oxford Sustainable Finance Student Society, Alex stressed the challenges of current emissions data disclosures, the transformative potential of asset-level data, and the pressing need for genuine transparency in financial commitments towards environmental change.


The Shortcomings of Current Emissions Data in Connecting Financial Activities to Environmental Impact


One of the main issues undermining the credibility of sustainable finance is the difficulty of identifying the tangible environmental benefits and costs that arise from financial activities. This challenge, as indicated by Alex, exists primarily due to a lack of robust methodologies and measurement approaches linking financial market operations to changes in the real economy – good or bad. "When you are trading green bonds and loans on secondary markets, you are not making any direct difference... when you are simply trading these instruments, it does not necessarily make any impact on the real economy," Alex points out. As opposed to the financial economy, which refers to the value and trading of securities on financial markets, the real economy is based on an economy's actual production capacity. With this distinction in mind, Alex suggests that there exists a need for a transformative approach that forges a clear link between financial commitments and environmental changes – past, present, and future.


As a starting point, the data on which financial decisions are based must at the very least be transparent and comparable. Regrettably, conventional (i.e., company-disclosed) emissions data often fails to meet these criteria. As Alex stresses, "When you are trying to measure a company's specific climate transition risk exposure on the basis of its scope 1-2-3 emissions disclosures, you are not going to get very far... emissions disclosure standards, all the way down to the ISO standards that they are based on, are basically not fit for purpose, because they are not designed for comparability.” Alex further emphasizes that while there is a widespread obsession with company-reported emissions, a large chunk of this data – particularly Scope 3 disclosures - are still based on estimations and assumptions, and the justification for these assumptions is often not clear to the end user.


Unlocking the Potential of Asset-Level Data


So, what are the solutions to this challenge? Enter asset-level data. By building a picture based on individual real assets, such as coal mines, power plants, and ships, asset-level data can provide a much more holistic understanding of the environmental footprint of a company or a portfolio of companies. Indeed, as Alex explains, "not only can this help you understand what a company's real economy footprint looks like in detail… you can also overlay really interesting, rich datasets on top of physical locations that can provide you with so much more insight than would otherwise be possible.” These datasets, in combination, would allow for comprehensive analysis — capturing everything from heat stress projections to the legal risks certain assets may be exposed to. It is a promising direction, one that offers a more grounded, accurate, and transformative approach to sustainable finance.


However, the process of data aggregation is anything but straightforward. It involves an intensive process of examining physical asset production data and matching it accurately with direct corporate owners, then to corporate ownership trees, and finally to the financial securities issued by direct or indirect asset owners. "Putting together these data from many, many different sources, making sure they are consistent with each other, and then normalizing them into one single product," Alex notes, is a huge task that requires precision and sector-specific expertise.


In the next phase, Asset Impact transforms the raw production data by parsing it through specialized emissions models. These models are tailored to the various technologies (and where possible, locations) in the dataset. For instance, the emissions model for small aircraft significantly differs from that of larger ones, and the model for a coal-fired power plant in India differs from a combined cycle gas plant in Germany. What stands out in this process is the drive to maintain granularity to ensure accurate and transparent emissions data.


Financial institutions find great value in this granular asset-level data. A significant percentage, "most of our business today," Alex mentions, focuses on aggregated company-level data – broken down by sector, technology, and geography. The insights that can be gleaned from company-level data range from determining how many megawatt-hours are produced by wind farms owned by a given company in each country in which it operates, to understanding the production numbers of vehicle types from factories in different countries. This granularity allows institutions to develop their own emissions or emissions intensity targets, benchmark progress against different transition scenarios, and enhance their climate risk management capacity. The data can also be used to derive ESG scores, among other analytics, which can guide institutions’ strategic environmental initiatives and investments.


Looking Ahead: Authentic Environmental Impact Assessment


As we think about the future of sustainable finance, the problem of greenwashing and superficial environmental promises is a big concern. There is a growing need for financial plans that do more than just pretend to support environmental protection; they must make a real and measurable difference. Alex highlights this need for honesty in financial actions: "No one really knows yet what the concept of “transition finance” is going to look like in practice, and how it is going to be financially justified." It's a testament to the complexities and uncertainties that characterize the future of sustainable finance.


The path forward requires us to better understand how financial decisions cause changes in GHG emissions. It is not enough to simply celebrate a company for cutting its emissions without knowing 'how' and 'why'. Alex illustrates this point: "If emissions by a certain company go down 30%, that does not necessarily mean they decarbonized, it may mean that they just sold a bunch of assets to someone else – and that someone else will probably still be operating them." To spot true environmental improvements, we need to be able to tell the difference between real cuts in emissions and changes made just from moving money around. Alex argues that "Being able to distinguish between these real and virtual changes is the next frontier for what we can do with our data."


In conclusion, making sustainable finance really work is about precision and authenticity. Alex's insights reveal a critical need for refined methodologies. Asset Impact’s methodology, rooted in asset-level data, is one of the solutions. This helps show the actual environmental effect of where money is put and fights against greenwashing. As we navigate this evolving landscape, it is crucial to tell the difference between real environmental gains and simple money shifts. Looking ahead, we need a strong and clear view of sustainable finance to guide the financial world in truly helping the planet.


Yunus Isik, VP (Academics), Chief Editor

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