How data can support financial services when assessing nature impact

Financial institutions need to start assessing their exposure to nature, but with market data still evolving, there are many factors to consider.

In brief

• Nature impacts have the potential to be more financially material than climate risks.
• Data to assess nature risk is nascent; new tools, datasets and guidance will be critical to ensure data quality and reporting standards.
• Financial institutions should start by identifying the most material parts of their portfolios in preparation for more granular assessments.

Where does the data currently exist?

Our research suggests that assessment tools are both disparate in nature and in a relatively juvenile state. No single provider offers the same service or uses the same methodology. Different providers may therefore need to be used for different purposes, e.g., sector nature impact and dependency mapping, project finance, and supply chain analysis.

Site-specific data

Site-specific data, using satellite and other remote sensing techniques or eDnA can be readily deployed at large-scale to capture a significant quantity of data across land usage. The captured data can be useful for analyzing the impact that project finance or land intensive portfolios - such as agriculture - can have on surrounding nature. It also allows a deeper understanding of the nature impact, which in turn enables more informed decision making. However, gathering the data depends on the extent of ownership the financial institution has, and reflects their ability to influence through engagement.

Earth system modeling

There is extensive academic research on nature, which has been leveraged by NGOs and data providers to build earth-systems models that measure global nature impacts and can also be extended to both climate and social impact. Most data providers model a single dimension of nature, such as species or deforestation, with only a few notable providers covering a range of dimensions and their correlations. Although some of these models can be used to map sectors to their nature impacts and dependencies, more granular assessments would involve financial institutions attributing risk exposure to the specific companies and business activities they are financing. In order to attribute this risk, we require asset location data to be overlaid onto earth system models. Therefore, these tools are deployable where a financial institution has asset location data (e.g., retail mortgage portfolios) or for sectors where this data is available (e.g., utilities).

Some data providers are expanding their asset location databases, but these tend to be focused sectors, such as utilities and mining. Apart from these sectors, coverage is not yet broad enough to perform risk and impact assessments across entire portfolios.

Supply chain tools

A large portion of nature exposure resides in a company’s supply chain. Therefore, some providers focus specifically on assessing risks in the supply chains. These tools are readily deployable and map economic activity throughout the supply chain to reveal impacts on nature. Each inherently has its own qualities, some using proxy data to make estimations while others utilize a combination of public data and primary research. However, these tools only cover limited indicators and do not assess all material impacts on nature which may be apparent in the supply chain.

Data limitations and direction of travel

Data availability

While disclosures and therefore availability of nature assessments at an entity level is currently low, finalization of TNFD recommendations and guidance on disclosure metrics (September 2023) is expected to drive further disclosure and greater availability of data. There will likely be a time lag before company specific data is available for portfolio-level assessments. Once the TNFD is finalized, financial institutions should begin to engage with corporates to help drive the assessment and disclosure of their nature impacts in line with the guidance.

In the interim, financial services institutions can use the data that is available to build a directional understanding of their exposures in preparation for more granular assessments in the future.

Data useability

The challenge is not only about data availability, but also how it is interpreted for useful decision-making. By using existing data, financial institutions can assess their initial exposure to nature. The output from these assessments can provide useful information that highlights nature exposure across portfolios and enables better understanding for more accurate decision-making to reduce risks.

As data availability improves, financial institutions can start to test their portfolios under different scenarios, which will provide more granular information on their nature exposure. However, physical nature risks are more complex than climate to model because of the multiple, correlated dimensions (i.e., soil erosion, deforestation, urbanization, water quality and species), as well as their interdependency with climate, for which modeling is already difficult, since it is an area where the science is constantly evolving. Therefore, requisite tools and data are likely to take longer to develop than for climate. Understanding the full picture would also likely require integrating nature and climate models. The market is not yet mature enough to do this.

Furthermore, nature transition risk modeling is driven by economic, policy and technology factors. Regulatory policy for nature is not yet clearly defined, and nature-based solutions are not well established.

Data Management for ESG and nature

Our observation of the market shows that ESG data is not often being integrated or managed in a strategic way, with data sourced and governed in a distributed manner. The addition of nature data adds more complexity and potential further risk of error and inconsistency. By taking this fragmented approach, financial institutions risk building silos of data which may limit their ability to reconcile their progress against ESG commitments.

ESG is expected to continue to become more tightly regulated, with mandatory assurance on ESG disclosures. Therefore, financial institutions should start to build a strategic approach to ESG data management while data needs and sources are still relatively small. This will provide the requisite governance, traceability and auditability that enhanced regulation will require. Conversely, there is a risk of significant cost and time commitment to retrospectively apply such a data strategy to a growing set of ESG data use cases. Additionally, there is significant risk of misrepresentation of sustainable products, lending or in regulatory disclosures e.g., EU Taxonomy.