June 22, 2022
Four hundred and fifty leading financial institutions have signed up to the Glasgow Financial Alliance for Net-Zero and committed to net-zero emissions by 2050. The question, though, is how these institutions, which account for $130 trillion of financial assets, will successfully make the transition.
A critical dependency is sound data to assess Greenhouse Gas (GHG) emissions and to model the potential impact of climate scenarios. The most problematic area is indirect emissions, whether produced upstream in the supply chain or downstream through bank loans and investments. The activities funded by banks account for the vast majority of bank emissions. For example, the City of London would be the ninth largest emitter of CO2 if it were a country. In addition, financial institutions require solid data to measure and reduce direct emissions from their IT, branches and operations.
Unfortunately, a fundamental weakness in much environmental data is that it consists of estimates and proxies or derives from secondary sources such as ratings agencies and annual reports. These represent an interpretation of performance, not actual performance, and therefore the data can be unreliable. There is also a lack of transparency around the audit trail of data. This opaqueness undermines trust and inevitably leads to accusations of greenwashing.
A trio of emerging technologies promises to overcome these limitations by providing direct data: Distributed Ledger Technology (DLT), Spatial Finance and Internet of Things (IoT).
Tracking carbon emissions end-to-end
Distributed Ledger Technologies, or blockchain, can bring transparency around GHG emissions associated with energy consumption and around the carbon embodied in supply chain inputs, i.e., Scope 2 and Scope 3 emissions under the Greenhouse Gas Protocol. When something is produced, data about the greenhouse gases emitted in its production can be tokenized, i.e., recorded on a distributed ledger. This token can then follow the item wherever it goes. So, for example, GHG emissions could be tracked on an open and immutable ledger from the moment that coal or gas is produced or used to generate power. Anyone who consumes that electricity, or for that matter, consumes anything that was produced using that electricity, can access the token and hence record their indirect GHG emissions accurately.
In addition, tokenization on a distributed ledger addresses the issue of double counting that besets carbon trading, where both an organization offsetting its emissions and the host country of a decarbonization project claim the same carbon credit. With tokenization through a distributed ledger, there is a single token so it cannot be claimed twice. Furthermore, there can be knock-on benefits within the energy sector itself, in terms of energy trading and efficient sourcing.
A further advantage of DLT or blockchain is its potential to support green bonds and blue bonds that can channel funds towards sustainable outcomes, say, reforestation or ocean conservation. This is because the transparency of blockchain offers a way of overcoming potential investor concerns, such as lack of secondary markets and transparency into ESG outcomes. Project Genesis: a prototype digital platform for green bond tokenization is an early trial of this use of blockchain.
Finally, DLT could be used to apply a carbon tax. A fundamental barrier in implementing carbon taxes is assessing indirect emissions, especially where carbon consumption is outsourced or offshored. For example, much of the carbon attributable to an automotive manufacturer can be contained in imported parts. With DLT, embodied carbon is tracked across the supply chain from the moment that it is produced in a vehicle part’s manufacture.
While the incredible amounts of energy used in bitcoin mining are of concern given the net-zero emissions goal, the blockchains used for the purposes discussed here would be based on Proof of Stake (PoS), not Proof of Work (PoW), which defines bitcoin. “The consumption rates of PoS-based systems are moderate and thus also much closer to the figures for traditional, centralized payment systems such as VisaNet,” according to a study by UCL.
Connecting data to measure risk
The second way to provide more direct and transparent data is spatial finance. In essence, spatial finance technologies bring together geographical and financial data, and provide a way to tap into the rich seams of environmental data that are now being created. For example, Climate TRACE is a coalition of scientists, activists and tech companies that uses satellite imagery, big data and artificial intelligence (AI) to monitor and transparently report on all of the world's emissions as they happen.
Advances in earth observation and data science make it possible to create transparent and verifiable datasets of every significant asset in the global economy. The Spatial Finance Initiative has shown how these data sets can combine information about the asset, its physical location and its ownership structure. As a result, the physical risk of, say, a forest fire in California, can be calculated for an individual asset and mapped back to the organization that owns the asset. This overlay of financial and geographical data allows financial markets to better measure and manage climate-related risks.
It is no surprise that many fintechs are targeting spatial finance for the banking and insurance sectors. To take just one example, Cervest provides risk assessments related to millions of physical assets that can be fed into financial transactions.
Leveraging real-time data
The final emerging technology to improve environmental data is IoT. IoT can be used to monitor and report environmental data through sensors connected to the Internet that measure (in real-time if required) temperature, geo-positioning and water-purity readings. Obviously, IoT data is of significant value in monitoring and reducing energy usage directly.
In addition, IoT data can be used to support sustainable finance that mitigates climate risk by reporting achievement of sustainability outcomes. For instance, if an enterprise has issued a green bond that is aimed at certain environmental outcomes — say, water purity in a particular location — those outcomes can be measured impartially through IoT sensors and reported to organizations that have underwritten or purchased the bond.
The most powerful solutions will come when this trio of technologies is combined. Spatial finance will map assets and their geo-locations to financial ownership structures; IoT will provide real-time data on the physical status of assets and the environment; and DLT will bring transparency into the origin of assets and the resources consumed in producing them. Each of these technologies already exists — the issue is willingness to innovate and adopt them at scale.