Catalysing the climate transition
Environmental Finance: What ESG data do you provide?
Girish Narula: Our dataset provides a comprehensive time series of the Greenhouse Gas Protocol defined Scope 1, 2 and 3 emissions of the largest 5,000+ global companies that are directly analysed by us, along with modelled data available for 30,000+ securities. Data includes Scope 1 and Scope 2 emissions for both market and location-based emissions and each of the 15 disclosure categories of Scope 3 emissions, covering all the major investable indices.
EF: What is key to competitive differentiation in this space?
GN: Transparency informs everything we do from collecting, processing, and delivering data through to the design of our climate models, methodologies and analytics.
Our dataset incorporates disclosed and inferred emissions intensity data. We apply an Intensity Inference Methodology to non-disclosing companies and to companies with insufficient publicly disclosed data. The dataset clearly identifies figures that are directly reported and inferred.
The granularity of our data also sets us apart. This is reflected in our coverage of all 15 categories of Scope 3 as well as covering Scope 2 emissions through location and market-based methods.
We also partner with leading practitioners and experts from the financial markets, climate scientists, research bodies, academics and climate-risk focused NGOs. Open collaboration with the climate-science and research community is essential to ensure that the models informing decision making are aligned with the latest scientific research.
This means that our analytics are supported by our close ties with climate scientists and academics and harmonised with the latest Intergovernmental Panel on Climate Change (IPCC) reports, the Science Based Targets initiative (SBTi), EU Taxonomy, Network for Greening the Financial System (NGFS), International Energy Agency (IEA) scenarios and Task Force on Climate-related Financial Disclosures (TCFD) frameworks.
EF: Where does your climate risk platform, Element6, fit into this picture?
GN: The platform offers our clients a holistic view of climate risk at the company, sector and portfolio level, including scenario analysis, sectoral emissions attribution and forward-looking analysis. It is being used by asset owners for strategic allocation and regulatory climate risk reporting as well as asset managers who incorporate climate risk into their portfolio optimisation and stock selection.
All modules in the platform are based on our work or experience with clients. As we find new ways to help them, these are incorporated into product development alongside clients’ feedback on their usage.
The platform isn’t just another product for us – it’s the place that all the flows of information and knowledge from our ecosystem of academia, scientists and research institutes, NGOs and our client-base converge.
EF: How has it evolved over the past year?
GN: From a functionality standpoint, we have introduced a range of new features such as enhanced scenario alignment, a temperature metric and forward-looking metrics as well as bespoke carbon footprint reporting.
Our data team will also soon be introducing an artificial intelligence and neuro-linguistic programming (NLP) driven sentiment-based analysis module to Element6. From a technology perspective, we have developed Application Programming Interface (APIs) for footprinting and portfolio alignment, which will help clients seamlessly integrate Element6 outputs into their systems.
EF: Can you tell us about how your approach is applied to stress testing for banks?
GN: Climate stress testing is an important tool for banks to measure climate-related risks that will affect global financial stability. Urgentem recently developed a methodology and model, which has contributed to the European Central Bank’s climate stress testing framework.
Urgentem’s model can estimate future emissions of more than four million public and private companies, up to the year 2100. It utilises disclosed and modelled corporate emissions data as well as company specific GHG emissions profiles. Key to the methodology is our inference of comprehensive emissions data, which is expanded beyond listed companies to also offer estimated Scope 1, 2 and 3 emissions data for non-listed companies.
The projected future emissions of companies consider regional and global emissions pathways from a suite of NGFS climate scenarios as well as emission reduction targets set by companies.
EF: How does your data support TCFD and Sustainable Finance Disclosure Regulation (SFDR) reporting for asset managers?
GN: Our data and analytics are aligned to TCFD and SFDR for regulatory reporting, and our climate risk platform includes all the TCFD defined foot-printing and alignment metrics. With regards to the SFDR, Urgentem can support clients by providing data for greenhouse gas emissions and energy performance indicators. We are also developing more bespoke analysis and advisory services to meet clients’ SFDR needs.