Comparative study of biodiversity metrics for Public Development Banks (PDBs)

Today, the loss of biodiversity has become a major risk for financial systems. In September 2023, Ravi Menon, Chairman of the NGFS – the network of central banks, financial regulators and financial institutions for the greening of the financial system – warned: "Along with the climate crisis, the degradation of nature is an existential threat facing our planet. Addressing nature-related risks and its broader implications for the financial sector is no longer just prudent – it is an imperative". 

As these risks require rigorous measurement, several frameworks have been proposed. The NGFS has published a conceptual framework for taking into account the risks associated with biodiversity loss. Target 15 of the Kunming Montreal Global Biodiversity Framework also encourages businesses and financial institutions to assess, report on and reduce the risks associated with biodiversity loss and the negative impacts they have by 2030. Lastly, the Task Force on nature-related Financial Disclosure (TNFD) has proposed a reporting framework to help businesses and financial institutions analyse and disclose these risks and impacts, recommending the use of various biodiversity metrics. 

However, as the missions of PDBs focused on achieving the Sustainable Development Goals (SDGs) are very specific within financial institutions, there are few studies to help this type of institution identify the biodiversity metrics best suited to their activities. 

The main objective is to compare six biodiversity metrics to determine which are best suited to the needs of Public Development Banks. By identifying the best practices, this project aims to guide PDBs in their financing decisions, by better integrating biodiversity considerations. This harmonisation of biodiversity measurement practices will improve the environmental impact of the projects financed. 

The research project also seeks to reveal the accessibility costs and the need for training within PDBs so that they can effectively integrate biodiversity considerations into their risk assessments. 

The study, conducted by Biotope and Arcadis, has been carried out in three phases: launch and data collection (briefing, project validation and data collection with recommendations); implementation (summary assessment, then in-depth assessment depending on the data available); consolidation and reporting (analysis of results, comparison of metrics and drafting of summary report). 

Following an preliminary comparative study by The Biodiversity Consultancy, six metrics for assessing biodiversity in PDBs projects were selected:  ENCORE, ABC-map, STAR, CBF, BFFI and GBS. These relevant and scientific metrics cover the main drivers of biodiversity loss. A sample of six varied AFD projects was selected to test these metrics. The projects include initiatives in Africa, Pakistan and Mexico. The European Bank for Reconstruction and Development (EBRD) also tested the same metrics on three of its projects.

The project resulted in three deliverables: 

• A preliminary study proposing several protocols for the use of several metrics in order to compare their results. It also contains information that may be useful to some development banks that simply want to choose a metric and see how they can use it. With this in mind, a decision tree for choosing one of the metrics studied is proposed in Appendix 2 of this preliminary report.
• A policy brief providing synthetic results, a case study and specific recommendations for the integration of these metrics into PDBs financing processes.
• A final research paper. 

To produce a comparative analysis detailing the advantages and limitations of the different biodiversity metrics studied, this research project tested how tools can be applied throughout the investment cycle, from project screening to portfolio reporting. 

Findings show that while tools can deliver meaningful insights, their use is limited by scarce and uneven project data. Time and reporting constraints often force reliance on sectoral averages rather than site-specific inputs, reducing precision. Differences in metrics, units, and classifications complicate comparisons, and some pro-nature impacts (e.g. sustainable agriculture, forestry, anti-poaching) are poorly captured. 

Despite these limits, tools are valuable for early risk screening and aligning finance with nature-positive goals. No single tool meets all needs, but a combined, tiered approach—tailored to project type, data, and disclosure requirements—can add value.