Bloomberg to use Natural History Museum data for biodiversity tool

Collaboration comes in response to investor demand for better biodiversity data, data provider tells RI.

Bloomberg will integrate the Natural History Museum’s Biodiversity Intactness Index (BII) into its terminal and data offerings to create a biodiversity tool, the data provider announced today.

Launched in 2014, the BII measures the biodiversity makeup of a specific terrestrial area in comparison to a pristine area with minimal human interference. Ecosystem integrity is categorised on a scale from 100 percent (the naturally present biodiversity remains intact) down to 0 percent (none of the species in a location were naturally found there). 

The BII is built on the Natural History Museum’s PREDICTS database, which incorporates peer-reviewed biodiversity data from over 50,000 sites across the globe, spanning more than 100 countries. It includes data on more than 58,000 distinct species across taxonomic groups including mammals, invertebrates, plants and fungi.

Bloomberg plans to build a tool that combines the museum’s geospatial BII data with its own data on more than one million physical assets linked to nearly 50,000 global companies. This will allow companies to see their proximity to intact ecosystems and the scale of degradation to ecosystems near company operations over time, the firm said.

Nadia Humphreys, manager of global regulatory and climate solutions at Bloomberg LP, told Responsible Investor: “Our hope is that we’re going to get some really interesting insights and be able to unpick biodiversity claims companies are making about themselves or their supply chains.

“This means investors could use the tool to make more informed investment decisions, engaging portfolio companies to operate or source in a more sustainable way, as well as providing a way to start reporting against TNFD.”

Investor demand 

Humphreys said the project had been inspired by rising demand from Bloomberg’s investor clients for better information on the biodiversity impact of investee companies, particularly in response to disclosure requirements such as principle adverse impact reporting under SFDR.

“The communal voice was very much calling for more datasets. Our clients said current datasets available are heavily proxied and estimated – what they wanted was something that was more reliable and that could measure improvement or degradation over time,” she said.

“They also wanted something that was precise when it comes to where companies are operating and their impact, and had scientific weight.” 

Doug Gurr, director of the Natural History Museum, agreed. “When we speak to investors, the main thing we hear is that they are struggling with good biodiversity data. A typical request would be, ‘Is there any way you can look across the spectrum of companies we might invest in and get a sense of who’s doing well and who’s at risk?’

“That got us thinking that we should work with a provider of data to the investment community so that we could approach this issue more systematically.”   

The Natural History Museum had previously explored partnerships with the private sector, but with companies rather than investors. “It became clear very quickly if we wanted to influence corporate behaviour at scale, we had to go upstream to investors,” said Gurr. “And since then interest from asset owners and managers has continued to grow.”  

Metrics, metrics, metrics

The question of which metrics to use to measure biodiversity is the subject of heated debate among investors and other financial institutions.

Other options include means species abundance (MSA), a measurement of the average abundance of native species in a delimited space relative to an undisturbed ecosystems. The metric, which is popular with French market participants, also has a range of 0-100 percent.

Humphreys told RI that Bloomberg “looked at everything”.

“We’re never going to close off any route,” she said. However, when we did our exploration of what was missing in the space, ie being able to say exactly where companies are operating and the impact as a result of where they are operating, and what would give a complete offering to our clients, we thought the BII would be the best.” 

In particular, she flagged the quality of the dataset and the fact that it delivers a time series approach. 

BII stands out for several reasons, according to Gurr. It covers all taxonomic groups, whereas other metrics are “based on a subset of species or fairly broad ecosystem assessment”, and the use of historic data gives institutions an ability to “model forward and ask ‘what if’ questions”.

Gurr also pointed to the “sheer scale of the dataset”.

At the same time, he acknowledged that there are “pros and cons” for all the biodiversity metrics. “I’m not saying any one necessarily does it completely,” he said.  

But he warned against “spending forever” trying to find the perfect metric. “I think we need to be able to agree on a couple that work – we would include BII in this – and start trying them out.”