Urgentem - Element6™ Climate Risk Platform

Data category

Environmental data

What data do you provide?

Urgentem is an independent provider of emissions data, climate risk analytics and advisory to the finance industry for robust carbon investment strategies.

Our dataset provides a comprehensive time series of the Greenhouse Gas Protocol defined Scope 1, 2 and 3 emissions of the largest 4,500+ global companies that are directly analysed by us along with modelled data available for 30,000+ securities.

The data includes Scope 1 emissions, Scope 2 for both market and location-based emissions, and each of the 15 disclosure categories of Scope 3 emissions, covering the major investable indices.

The dataset also contains:

  • Classification of each company into disclosure categories providing insight into data quality.
  • Information concerning third-party assurance of emissions data, including standard used.
  • Outlier assessment of the reported emissions data.
  • Regional and country level analysis and breakdown of data (to the extent available).
  • Absolute and intensity values: tCO2e and tCO2e/$m Revenue.

The complete dataset for 30,000+ securities includes modelled data using Urgentem’s statistical models that are based on a quality assured dataset of directly analysed companies. This data goes all the way back to 2009.

Where and how do you source your data?

Directly Analysed Data: Our selection of directly analysed companies is reviewed annually based on different criteria like historical reporting trends, turnover, trading status, coverage of key indices and incorporation of new companies based on bespoke requests made by clients.

Analysts trained in Greenhouse Gas (GHG) emissions reporting collect data from public sources including but not limited to annual reports, financial statements and sustainability reports. Urgentem’s layered human quality assurance is combined with a modelled statistical outlier assessment to create a robust process in which data points are efficiently flagged, thus ensuring a high standard of data quality.

A proportion of the dataset is based on data received from CDP  on an annual basis. The CDP data is reviewed, enhanced and revised by our team of data analysts to ensure adherence to our Quality Assurance process before it is integrated into the final dataset. 

We also seek a dialogue with companies to encourage and improve their emissions disclosures in accordance with our company’s mission. All directly analysed companies that either do not disclose or have insufficient information are contacted. Our corporate engagement team also liaises with companies on behalf of our clients to assess how well their portfolio companies are transitioning to a low-carbon business model. 

Modelled Data: Urgentem’s Inference Methodology relies on the robust use of statistics. These statistics are calculated on data that has undergone a rigorous process designed to ensure a high level of statistical accuracy. 

Urgentem’s Dataset incorporates both disclosed and inferred emissions intensity data. The dataset clearly identifies figures that are directly reported and inferred. We apply an Intensity Inference Methodology to non-disclosing companies and to companies with insufficient publicly disclosed data.

Who are the data users?

Urgentem works with clients across the financial industry, providing reporting and risk management solutions to the entire value chain from regulators, investment and asset managers and lenders, to financial intermediaries, pension funds, and central banks:

  • Asset Managers who need granular, transparent, and quality assured emissions data for tailoring low carbon investment strategies e.g. breakdown of Scope 3 data or Scope 2 data by location-based and market-based figures with demarcation between modelled and disclosed data.
  • Asset Owners who use detailed corporate level emissions data for asset allocation and reporting.
  • Central Banks who use the data to set out climate risk regulations and maintain oversight.
  • Index providers who use the data to launch products based on corporate emissions.
  • Corporates & NGOs who use the data to create awareness and encourage reduction in corporate emissions.

What is the cost for your data offering?

Please contact Urgentem directly to find out more about licencing the climate risk platform and emissions data on +44 207 183 3221 or email us at info@urgentem.net

What are the key attributes that differentiates the data you offer?

Transparency & Granularity of Data: Our data and methodologies are designed with transparency, collaboration, and science-alignment in mind so that our customers can investigate both the emissions data and the assumptions which inform our methodologies.

Pioneers of Scope 3: While other players in the market focus solely on Scope 1 and 2 emissions, Urgentem looks at the holistic value chain of a company by diving deep into Scope 3 Supply Chain emissions.

Robust Statistical Methodology: Urgentem’s Inference Methodology relies on the robust use of statistics. These statistics are calculated on data that has gone through a rigorous process designed to ensure a high level of statistical accuracy.

Quality Assurance: Each company is independently assessed by two different analysts to avoid selection and sampling bias. The submissions are then independently reviewed by our Quality Assurance (QA) experts. An in-house outlier automated process then flags any discrepancies in the submitted data.

Science Based and Collaborative Approach: In order to continuously improve our data, we partner with leading universities, think-tanks and NGOs to ensure that best practices are met. We also actively engage with companies as part of our data collection regime, making sure we have the most up to date and accurate figures from the companies that we analyse.

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Urgentem’s Element6™ Climate Risk Platform provides climate risk data and analytical tools that enable clients to understand portfolio emissions, view climate risks, and navigate the transition to a net-zero economy.

Contacts

Stephen.Fitzpatrick@urgentem.net

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