The sustainable finance action plan of the European Union wants to ensure that banks, investors, and insurance companies take into consideration the sustainability impact of their financing activities. When they give money or insurance coverage to a company, that company will engage in various economic activities that may increase or decrease greenhouse gas emissions, water uses, or, to consider a social issue, they may increase or decrease the gender pay gap.

In this example, we are building up the risk assessment of greenhouse gas emission growth due to increasing economic activities. We work with a combined, CO2 equivalent emission of the Kyoto-basket of gases — but of course, or model could create a separate risk assessment for CH4, a very potent greenhouse gas, or CO2, or any of the Kyoto gases. We can also model social impacts, like the gender pay gap, and even governance risk, if there are good, quantified indicators available.

Our example is based on real Hungarian data, because we do our model validation with the central bank of Hungary. But we can re-run this model with about 30 advanced economies, and we hope to include with less granularity every country on Earth.

Locating Greenhouse Gas Emissions

The combined greenhouse gas effects are very much concentrated in the Hungarian economy. We have considered 64 economic sectors, but most of them had less than 1% contribution to the Hungarian GHG emissions.

Concentration of GHG within the economic sectors of Hungary, 2020

Concentration of GHG within the economic sectors of Hungary, 2020

We can compare this basic chart with earlier years, going back till 1995. We could ask questions like which industries are reducing or increasing their GHG footprint? Or, which activities are better located in Hungary, because they have a relatively low impact compared to Slovakia or Germany, for example.

When a bank gives a loan to a bakery, the bakery will certainly use energy for its ovens and heating its premises, by various grains, which in turn all have their embedded GHG emissions in their upstream supply chain. A part of the bakery product gets into supermarkets, restaurants, hotels, resulting in more transport or heating related emissions. The new EU action plan requires financial institutions to consider all these impacts in their lending, investing and insuring decisions.

Supplier Side

We created an environmental impact assessment for the Hungarian economy based on the input-output tables and emissions accounts of the national economy. The input-output tables are based on tax returns, statistical information, and other real economic sources about the supply chains of the national economy. This information is re-measures in full detail every 5 years in the EU countries, and it is updated with some information – for example, with emissions or price data — annually.

Our model allows us to answer questions like “How many million HUFs are spent on consultants and lawyers by banks for every billion HUF of lending activity?” And it can also say what is the typical embedded emission of one million HUF worth of legal or consulting services, based on the spending patterns of law and professional services firms on transportation, hospitality and catering, and so on.

As we have seen earlier, the GHG emissions are very much concentrated around a few economic activities and products, like energy or agricultural products. Most products/services do not have significant CO2, CH4, NOx or PM content that may increase the greenhouse effect. Our risk map contains normalized emissions concentrations, which consider the supply chains of 64 sectors of the national economy.

The named sectors in the left-hand side enumerate those industries that are likely to have a material impact on the GHG emissions when they ask for a loan or an investment to increase their production. The top rows of the matrix (abbreviated for readability, and for avoiding confusion) show the potential sources of embedded emissions.

For example, Residential and social services do carry a risk, because they rely on food and beverages. Even if these services do not emit per se much GHG gases, but they are relatively large buyers of Food, beverages and tobacco products, which in turn embed various GHG gases, mainly CO2 and CH4.

In fact, the upstream (supplier side) risks are concentrated in six value chains:

  1. Chemicals: the industrial value chain that contains chemicals, including pharmaceuticals, fertilizers, plastic and rubber production have the highest risk of increasing emissions through orders to their suppliers.

  2. Fuel supply chain: The fuel supply chains pose the second greatest risk, including the use of refined oil (for vechicles) or coke.

  3. Non-metallic minerals: This is a related value chain to the first two.

  4. Food, beverages and tobacco: In the services sector, the food, beverages and tobacco supply chain poses the greatest risk of supplier side emission growth. This supply chain is connected to the chemical supply chain, for example, via fertilizers.

  5. Mining and quarrying: This value chain that contains building materials made of stone, cement, have a very high risk of greenhouse gas effects.

  6. Basic metal products: The reliance on basic metal products is also indicative of supplier-side emission risks.

Buyer side

At this point, we do not present results for cases when households are buying products or services, though our model takes such end-uses into consideration. To keep this short presentation brief, we only consider business-to-business transactions when we analyze the risks of the downstream (purchaser side) of the value chain.

In our analysis, we have omitted land transport and wholesale logistics, because almost all products need to be stored and delivered for final purchases. The logistic chain is the single most important downstream risk after in the manufacturing of goods or in agriculture.

The following risk map shows the industries that are most likely to increase greenhouse gases through their buyers.

Risk map of purchaser side (downstream) GHG emissions in Hungary

Risk map of purchaser side (downstream) GHG emissions in Hungary

of the entire Hungarian economy are concentrated in three distinctive supply chains:

  1. Chemicals: the industrial value chain that contains chemicals, including pharmaceuticals, fertilizers, plastic and rubber production have the highest risk of increasing emissions through orders to their suppliers.

  2. Fuel supply chain: The fuel supply chains pose the second greatest risk, including the use of refined oil (for vechicles) or coke.

  3. Food, beverages and tobacco: In the services sector, the food, beverages and tobacco supply chain poses the greatest risk of supplier side emission growth. This supply chain is connected to the chemical supply chain, for example, via fertilizers.

Membership organizations are a curious addition. Many polluting sectors do contribute to maintainance of membership organizations, which in this case can be considered of using “dirty money” from an embedded emissions point of view.

The risks are similar, because the underlying physical activities that result in GHG emissions are the same.

Conclusions

These results are very specific to Hungary. Nordic country have a very different agriculture in comparison with the Hungarian agriculture, which carries different GHG risks. From the point of a viable path towards net zero emissions, banks should try to finance agricultural, manufacturing or service activities in the countries where they result in less emissions.

Hungary is a landlocked country with a very advanced manufacturing sector. Being landlocked results in a more carbon-intensive logistic chain which relies on little water transport and much land transport. A significant part of the Hungarian manufacturing output is very-high value-added electronics and other advanced products that are usually shipped with air transport. However, air transport did not appear in our risk assessment, because compared to the value of these products, for example, smart phones, the financial and environmental costs of carrying them to the final destination even with planes is relatively efficient.

The real damage to the atmosphere comes from moving bulky manufacturing products, produce of agriculture and processed food. Generally, in landlocked countries the large CO2 from the logistic chain can be reduced if much value-added activities take place in a geographical cluster. For example, fruits are harvested, processed, and added into high-value food products instead of being carried around in raw, intermediate and final product form around Europe and beyond.

What’s next?

We are developing Eviota to enable financial organizations and large, industrial purchasers to assess the potential impact of Environmental, Social and Governance issues whenever they receive an invoice, make a loan, invest, or sell something else.

Eviota aims to complement your accounting systems on the basis of ‘double materiality’ with this impact assessment. Whenever you purchase services for a million euros, or sell services for a million dollars, we will tell you the embeded GHG cost in tons of CO2-equivalent emissions on both invoices.