In the last panel of the day, moderated by Richard Peers, founder of ResponsibleRisk, the discussion centred around the role of data in nature intelligence and financial services.
The panel consisted of Cathrine Armour, director data initiatives, TNFD; Richard Conway, CEO, Elastaloud; Eoin Murray, managing director, Seed; Ana Raposo, business applications and partnerships officer, European Space Agency; and Matt Sandoe, chief of staff, OS Climate.
Core theme of the session was how we bring all forms of data and applications together to support rapid innovation while allowing comparability and interoperability. How can organisations map, measure, and manage the impact and dependency on natural assets as they travel through supply chains? And how can we establish the provenance of high-quality data, make it more accessible and decision ready?
Peers started the discussion by turning towards Armour regarding her take on the role of data as well as the need to standardise, benchmark and support. Armour, representing TNFD (The Taskforce on Nature-related Financial Disclosures, which has developed a set of disclosure recommendations and guidance that help organisations to assess, report and act on their nature-related dependencies, impacts, risks and opportunities.), emphasised that there has been a long demand for nature data.
“We’re really doubling down on the challenges that continue to exist, making the most of available data that is reusable is very important. One of the key things for us at TNFD is to collect once and use many times, but what we’re actually seeing is lots of collection activity but not necessarily specific to the use cases. Ultimately, it’s about getting much more specific about what’s being neglected, but then that moves us to transparency,” Armour explained.
She further teased TNFD’s upcoming launch of a blueprint for a major data facility, including announcements on where they see ecosystem change being required in the nature data space.
Making positive change though open-source technology
On the topic of required change, Peers turned the conversation to Eoin Murray, managing director of Seed. Murray started off by explaining that legacy change is absolutely crucial, and gave a few examples of tools and companies spearheading positive change, including OS Climate, Ocean Ledger, and Cambridge University’s 4Cs group, among others.
“Now what is it that draws all of these together?” Murray continued. “They found that healthy balance between scientific rigour and something which is usable and actionable. Today, that’s often the key in financial institutions. And this addresses challenges around translating nature intelligence, business intelligence, and, a lot of the time, IT departments simply getting in the way. So it’s all possible, and that’s the good news.”
A lot of the good examples mentioned by Murray included open-source technology, so Peers called on Matt Sandoe next, who is chief of staff as OS Climate. He explained that OS Climate is a non-profit which is part of the Linux Foundation, which means they have access to the flagship open-source consortium including members such as Goldman Sachs or Morgan Stanley.
“So we’re in prime position to really plug the philosophy of open-source and open data,” Sandoe emphasised. “Why is open-source so useful? Firstly, it enables you to bridge the gap across research, academia, industry, corporates, financials and data providers. It becomes a shared problem, and the trick is identifying the common layers. It’s all about pre-competitive collaboration.”
Bringing transparency - the impact of space data
At this point in the discussion, the concern around transparency had been mentioned by multiple panel members. Peers turned to Ana Raposo next, who is the business applications and partnerships officer at the European Space Agency (ESA).
Raposo gave an overview of examples of what is meant by space data - whether it’s looking at car parks or the health of crops. Thanks to the resolution of space data, “we can see things at asset level, at regional level and at global level,” she explained. “One of the key things of space is that it brings this transparency that everyone is craving. You no longer have to rely on someone’s reporting - you can actually see it from space.”
She also explained how the advanced technology they have access to allow for multispectral and hyperspectral views. “With hyperspectral, you’re able to distinguish hundreds of colours. The impact of this is that you can understand composition of minerals. This has implications for understanding the stress levels of crops much faster, allowing for decisions on how to act before it’s too late.”
Adding AI to the mix
Lastly, Richard Conway, the CEO at Elastacloud, explained the impact of AI and how large language models (LLMs) can streamline the decision-making process in a time where organisations have access to more data than ever before.
“It’s a lot of effort to take raw data that includes gaps, and get it to a place where it can be shared and you can do analytics on it,” Conway emphasised. “And it’s fantastic that all these building blocks exist with open-source.”
“The change that’s happened over the last 18 months is that you can take all these complex classifiers of data science and you can use software, prompt engineering, and spectral images to derive value from LLMs,” he continued. “If you take a step away from what people are doing in the sustainability space, a lot of people are using these models now to look at images of cancer.”
Summarising the session, the panellists emphasised the need for proactive, holistic approaches to data management. There is lots of technology that organisations can leverage, but they need to identify the right use cases in order to gain the most valuable insights.
A poll to the audience additionally revealed the untapped potential of geospatial data. Asking whether the audience was currently using geospatial data in their business to inform risk and opportunity decision-making, 42% responded no, 29% said they were experimenting, while another 29% said they already were using geospatial data at scale.