Striking a balance between the ‘perfect’ and the ‘practical’ was the task at hand for our advisory group members on November 25th. The group had convened for a second time and were now looking at the assurance signals required by banks in order to confidently provide green financing to farmers.
This balancing act is a particularly delicate one, given that overly stringent assurance requirements might stunt progress by adding significant costs or complexity, potentially alienating both banks and farmers. And yet, a more relaxed approach to assurance could lead to inaccuracies or even fraud risks. Nevertheless, if the right middle ground could be found, then it could have the potential to unlock green financing in the agricultural economy.
Exploring assurance levels
Our refined use case served as the session’s foundation: In order to access green financing, UK arable farmers must share assurable data on their reduction in fertiliser use with banks. We then prompted the AG to explore different levels of assurance and evaluate their feasibility and desirability.
High levels of assurance – such as verified historical fertiliser data, third-party audits, and detailed impact assessments – were quickly deemed too costly and impractical for widespread adoption. A mid-level approach, where farmers provide structured, machine-readable data (e.g., in JSON format), emerged as a more balanced option. This method would give banks reliable insights into sustainability efforts while being less burdensome for farmers.
Practical challenges
These assurance scenarios led our group to assess some of the more practical challenges that both farmers and banks face when dealing with farm-level data. One AG member emphasised the difficulties farmers face when collecting and reporting data on fertiliser usage, noting the variability in fertiliser usage as a prime example of this. Another member addressed the utility of this data, highlighting that farm-level data should serve a clear purpose. Without a direct link to compliance standards or broader utility, data collection risks becoming redundant—even if farmers are compensated for providing it.
“The challenge isn’t merely collecting data but knowing which data to collect for specific standards or compliance requirements”.
A holistic approach
Ultimately, a more holistic, joined up approach to collecting data from farmers would be key to the success of our use case. This would help to avoid the risk of duplicate or siloed data demands. “There is a need to avoid fragmented efforts that overburden farmers by addressing siloed and repetitive data requests from multiple stakeholders”, noted one member. Ensuring that all members of the agricultural supply chain were involved in future iterations of this work is therefore crucial. Collaboration across the agricultural supply chain from farmers, suppliers, retailers, tech providers, banks and beyond will be needed to create a system that works for everyone.
Equally important for our future work is the development of a Tiered Assurance Framework that establishes baseline data collection methods. Pilots would then be run to test assurance mechanisms, refining based on feedback and scalability challenges as well as working toward global alignment on assurance protocols linked to GHG accounting standards.