From global biodiversity commitments to local action: revenue potential and allocation dynamics of the Cali Fund

Biodiversity loss around the world is rapidly accelerating. At the same time, financing for conservation efforts falls far short of what is needed, with an estimated annual gap of US$700 billion. Currently, the private sector contributes only around 10% of finance for conservation. Yet pharmaceutical, biotechnology, agriculture and information technology companies increasingly profit from the digital genetic data derived from biological organisms (digital sequence information or ‘DSI’), freely available in public databases. This open architecture, while essential for scientific progress, has allowed companies to benefit from the genetic heritage of biodiversity-rich countries, without any obligation on them to share the financial returns.

The Cali Fund, established at the UN biodiversity summit (Conference of the Parties [COP] 16) in October 2024, is the first attempt to address this. It calls on private companies benefiting from digital genetic data to contribute 1% of their profits or 0.1% of their revenues to channel resources to biodiversity-rich countries and Indigenous communities for conservation. Currently, participation in the fund is voluntary. Its contribution rules and allocation formula are open for revision at COP17 in October 2026.

This paper provides the first global, firm-level analysis of what the Cali Fund is likely to raise and how resources would be distributed, while its design is still being negotiated. The paper highlights how the fund’s three allocation criteria – biodiversity richness, geographic origin of genetic resources and capacity needs – point in different directions and may have unintended consequences. Choices that may seem technical have consequences on distribution that can determine whether the fund achieves its purpose.

Key findings for decision-makers

• The Cali Fund could raise between US$929 million and US$3.6 billion per year: with full participation, annual contributions would reach $3.6 billion across 21,690 eligible firms in seven sectors dependent on digital genetic data. Under more realistic assumptions about voluntary uptake, the estimate falls to US$929 million, reflecting differences in reputational exposure, genetic data use and willingness to engage with voluntary schemes across different sectors.
• Early uptake is likely to be slow, with significant revenue consequences: evidence from comparable voluntary schemes shows that participation starts slowly and builds gradually. Applied to the Cali Fund, slow early uptake could reduce cumulative revenues by $3.9 billion over the first decade. The absence of national measures requiring companies to participate means this is the most likely near-term trajectory.
• A small number of firms and sectors dominate the revenue base: under full participation, two sectors, pharmaceuticals and information and AI services, account for half of contributions, and the top 100 firms for more than a quarter. Under realistic participation, pharmaceuticals alone could account for nearly 50% of revenues. This is a structural vulnerability: with no sovereign or public funding, revenues are entirely dependent on whether a relatively small number of firms decide to participate.
• The payment rule creates instability that COP17 should address: most eligible firms pay into the fund based on their profits rather than revenue, meaning contributions fluctuate with short-term profitability rather than genetic data use. Revenue-based contributions are more stable and harder for firms to reduce through tax planning.
• Who receives funding is determined almost entirely by formula design, and the choices are not neutral: prioritising the geographic origin of digital genetic data, for example, would channel nearly half of all the fund’s resources to wealthy research economies, while African states would receive just 6%. Altering the mathematical structure of the formula alone can shift the fund’s allocations by up to 13 percentage points without changing the underlying allocation criteria.

DOI: 10.21953/researchonline.lse.ac.uk.00138657