Introducing Carbon Footprinting to Transactions

You are reviewing your bank account statement on your phone. The statement of course shows the amount of money you spent on goods and services. But what if it also shows the amount of greenhouse gas emissions generated to produce them? This has become a reality.

In the past few years, a number of carbon footprint calculators designed for analyzing transactions--be they bank statements or credit card transactions--emerged on the market. The pressure to measure and cut down their carbon footprint is growing rapidly, and mobile apps and websites to support that are springing up. Crucial to this new development are reliable transaction data and the factors that translate such data into greenhouse gas (GHG) emissions.

An important catalyst to this development is the Open Banking initiative in the United Kingdom and Europe. The Open Banking initiative enables access to reliable transaction data. Such transaction data needs to be coupled with reliable GHG emissions factors in order to accurately measure the GHG emissions arising from transactions.

Current Tools

Financial institutions are already applying this idea to create transaction carbon calculators. For instance, Mastercard has created a scoring system for its carbon calculator to estimate near real-time emissions. One such example is the DO card, which uses indices to calculate emissions based on transaction information. Visa has also started adding sustainability features to its card with an internalized calculator that allows the consumers to purchase carbon offsets for their spend.

There are several companies that are working to develop client-facing tools to help businesses and consumers make these calculations. The Åland Index and ecolytiq have developed methodologies for such calculations and make assumptions to categorize available transaction data to match with emissions factors.

However, merchant data is often not sufficient to identify which product category from the merchant was actually purchased. These issues may be addressed through further analysis of point of sale data or the use of the basket of goods from a merchant.

We have also worked with several companies on transactional applications utilizing our Comprehensive Environmental Data Archive (CEDA). The CEDA database has already proven itself in several projects. With Yayzy, a UK banking app, emission factors have been matched to location and transaction type categories. The banking app allows everyday consumers to have an easy way to see their personal impact, as well as buy accredited offsets for those emissions. Matching the items the users spend on to the database’s factors allows buyers to have real-time carbon data upon the completion of a purchase. Similarly, the use of CEDA for circa5000 allows for estimations of climate change impacts from investments. The provision of accurate and science-based estimations allows companies to effectively communicate their footprints and recognize areas where improvements may be further made in their spend and supply.

Examples of Current Tools

Limitations

Even though current transaction data is useful in its estimation to measure emissions, there are several limitations to its usage. The number of categories distinguished in the transaction-based footprinting varies across tools. For instance, ecolytiq only has about a dozen categories, while Yayzy has several dozens. The categories being matched to the transaction may therefore be too coarse and not always perfectly applicable. Additionally, transaction data generally stores the merchant information (e.g., Walmart), not the individual products or services. This limits the ability to accurately quantify the product-specific footprint and instead leaves the estimation to the industry sector rather than a specific product.

Outlook

Reliable estimates of GHG emissions from transaction data require information on exactly what was purchased. Merchant information alone won’t be able to provide accurate measurement. For instance, a $30 purchase from the same merchant may have been a tree sapling that would sequester CO2 throughout its life, or charcoal that would generate CO2, and the current, merchant-level information does not allow us to distinguish the two. Therefore, the system that allows product-level, or Stock Keeping Unit (SKU)-level transaction data would be an important next step. Some countries, such as South Korea, implemented this at a Point-of-Purchase (POS) terminal scale. In the long-run, we need not only product category-specific, but also brand-specific and SKU-specific footprinting. Progress is being made in this direction, such as our development of CEDA Global Enterprise that utilizes country-specific input-output tables.

Takeaways

The need to accurately and effortlessly measure personal and institutional carbon footprints is growing, and transaction-based carbon footprints can be an important pillar to support people’s needs to measure the footprint of each time they spend money. There is still work to be done, such as accessing commodity-level purchase data through transactions and integrating more supplier and product-specific data into available tools. As more and more companies measure and report their emissions, the industry average data will be replaced by supplier, product-specific data. However, transaction analysis provides the first key step of measurement to understand impact.

About VitalMetrics

VitalMetrics created the Comprehensive Environmental Data Archive to create a spend-based approach that helps both consumers and businesses calculate emissions based on spend. As one of the Greenhouse Gas Protocol’s recommended spend-based databases, CEDA includes environmental coverage of 400+ different sectors, commodities, and linkages between them. Because it follows an input-output database model, it is able to provide this complete coverage of every sector and transaction. Transaction data includes several factors that must be considered: the merchant type, the location of the transaction, and the amount spent. The database is able to provide coverage for the different industry categories, such as electronics products manufacturing, legal services, data processing, hosting, and related services, etc., and provides emission factors that are specific to the transaction location per unit of spend.

CEDA contains comprehensive global data stored all in one place

References

Open banking key to cutting carbon footprint. 2021. Retrieved November 29, 2021, from https://tink.com/blog/open-banking/open-banking-powering-sustainability/
Andersson, David. A novel approach to calculate individuals’ carbon footprints using financial transaction data. 2020. Journal of Cleaner Production, 256. https://www.sciencedirect.com/science/article/pii/S0959652620304431
Barendregt, Wolmet, Aksel Biørn-Hansen, and David Andersson. 2020. "Users’ Experiences with the Use of Transaction Data to Estimate Consumption-Based Emissions in a Carbon Calculator" Sustainability 12, no. 18: 7777. https://doi.org/10.3390/su12187777
Open data will catalyse the UK’s progress to net-zero. 2021. Retrieved November 29, 2021 from https://www.finextra.com/newsarticle/37986/open-data-will-catalyse-the-uks-progress-to-net-zero

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