Calculating the biodiversity footprint for the banking sector

For ASN Bank, PRé and CREM developed a methodology to calculate the biodiversity footprint of the bank's investments from simple spend data, bringing the complexity of biodiversity down to manageable level.

Challenge

ASN Bank’s aim is to contribute to a fair distribution of the world’s wealth to present and future world citizens. As such, they are concerned about the effects that the investments from the banking sector might have on the state of the world’s biodiversity – their biodiversity footprint. Yet, assessing the impact on biodiversity is complex, requiring a large investment of time from skilled individuals. Moreover, banks do not usually have the required environmental technical data at hand; they only have information about spend, generally with a low level of granularity – only at industry sector level, for instance.

ASN Bank asked PRé and fellow sustainability consultancy CREM to set up the bases of a methodology that would provide insight into their biodiversity footprint and the impact of their investments. Furthermore, ASN Bank asked PRé’s advice on how to apply these insights to reduce impacts in the future, with the long-term objective of reaching a no-net-loss situation.

Solution

The goal was to develop a biodiversity footprinting methodology that would:

  • Allow simple data entry, since the thorough and complex data collection process needed for a life cycle assessment would not have been appropriate
  • Provide simple outputs that can easily be grasped and communicated outside of the scientific world
  • Nevertheless be built upon a robust methodology in the background, with a sound and scientific basis

To develop the methodology, we interviewed experts and policy makers and discussed the results in a stakeholder meeting. Stakeholders participating in this meeting included representatives from the government, methodological experts and representatives of civil society organizations.

The result consists of quantitative calculations, complemented with a qualitative analysis performed by CREM.

For the quantitative approach, we decided to base the solution on an input-output (IO) database, so that the only data required were ‘how much was spent in a given sector and a given country’. IO databases for sustainability assessments work on the basis of certain economic tables coupled with statistical impact data, for example on environmental emissions or social characteristics. Because ASN invests in shares of multi-national companies, we needed a database covering the entire world economy instead of only one country or economic region. This quickly narrowed down the possibilities to Exiobase.

Exiobase v2.2 is a huge compilation of input-output data, divided into 163 industry and services sectors coupled with environmental information such as greenhouse gas emissions (GHG), land use, water consumption, etc.

Using Exiobase, no more information is needed than the number of millions spent of Euros, e.g. 1 M€ in electricity produced from wind energy, from a Dutch provider.

To translate these data into biodiversity footprint results that can be easily understood, we decided to use the ReCiPe method, adapted for biodiversity.

GHG emissions expressed as CO2-eq embodied in trade, in 2007. Extracted from The Global Resource Footprint of Nations

The outcome is a single score in square meters that allows an immediate grasp of the dominant impact indicators. The relative importance of each type of investment is also clearly visible, which can be used to build up a compensation scheme.

Impact of various type of investment expressed in m² impacted per € invested.

While this quantitative methodology covers a wide range of impact categories, many mechanisms that impact biodiversity are not fully covered. Moreover, ASN Bank already sets very high sustainability standards for its investments (e.g. using FSC-labelled forestry products only), while the IO database assumes, by definition, average industry sectors.

To address these aspects, and to provide clearer views on possible compensation or remediation strategies, we subjected each type of investment to a qualitative analysis, with the double objective of understanding the detailed causes of damage to biodiversity and to determine whether:

  • There are reasons to assume that the impact on biodiversity might be higher than the quantitative analysis predicted
  • There are reasons to assume that the impact might be lower
  • There is no reason to assume a difference

This kind of qualitative analysis provides a good mapping of potential impacts that may not be captured by the quantitative calculation, such as overexploitation of land or the introduction of invasive species. These results can be used to derive investment criteria and engagement with investees.

The biodiversity footprint analysis and steps towards providing the metrics to support the long-term biodiversity objectives are not the end, but rather the beginning of biodiversity assessment for ASN Bank. The beginning of a process of deciding on the long-term objective within the bank, of working towards this objective in cooperation with experts and stakeholders, and of optimizing the biodiversity footprint methodology while doing so, as they already did for their climate-neutral investment policy.

Benefits

  • Insight in decision challenges towards responsible financial activities. The interviews and stakeholder consultations showed what decisions and challenges a financial institution might face when assessing its environmental impact, when deciding on its responsibility and when working towards a biodiversity objective. The variety of viewpoints from different stakeholders provided great insights.
  • Building a collaborative stakeholder network. The pool of experts and stakeholders consulted in this project will function as a network that ASN Bank can consult and involve in the development process in the coming years.

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