{"id":27248,"date":"2022-10-24T03:34:33","date_gmt":"2022-10-24T07:34:33","guid":{"rendered":"https:\/\/www.bloomberg.com\/company\/press\/bloomberg-increases-carbon-emissions-data-to-cover-100000-companies\/"},"modified":"2023-04-12T16:43:31","modified_gmt":"2023-04-12T20:43:31","slug":"bloomberg-increases-carbon-emissions-data-to-cover-100000-companies","status":"publish","type":"press","link":"https:\/\/www.bloomberg.com\/company\/press\/bloomberg-increases-carbon-emissions-data-to-cover-100000-companies\/","title":{"rendered":"Bloomberg Increases Carbon Emissions Data to Cover 100,000 Companies"},"content":{"rendered":"
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Estimation techniques guided by a waterfall principle significantly expands universe of actionable carbon emissions data
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As demand grows for reliable and comprehensive carbon data, Bloomberg has increased its carbon emissions dataset to cover 100,000 companies. This dataset consists of company reported carbon data and estimates based on either a machine-learning smart model or Bloomberg\u2019s newly developed industry-implied model accompanied with a PCAF reliability score.<\/p>\n

\u201cGreater precision in Scope 1, 2 and 3 carbon emissions data will enable asset managers and banks to measure the extent of climate change risk within their investment and lending portfolios, and across their operations as a whole,\u201d said Brad Foster, Head of Enterprise Data Content at Bloomberg. \u201cTo date, limited and inconsistent corporate disclosure of these emissions has posed a significant challenge; our expansion of this dataset will help to address these gaps so clients have actionable information to identify climate related opportunities and risks.\u201d<\/p>\n

When company reported carbon emissions data is not available, Bloomberg applies estimation techniques guided by a waterfall principle to increase the scope of companies covered and thus provide a more complete picture of emissions. The first estimation technique uses Bloomberg\u2019s machine learning-based smart model incorporating 800+ data points to estimate Scope 1 and 2 emissions with historical data going back to 2010. Last year, Bloomberg also released Scope 3 estimates for Oil and Gas, Metals and Mining, and Services industries using a methodology <\/a>combining a bottom-up model with a top-down machine learning model.<\/p>\n

When there is not enough data available to apply these machine-learning smart models, the waterfall technique automatically reverts to Bloomberg\u2019s new industry-implied model. This method uses peer emissions and sales data to estimate a company\u2019s emissions. These estimates are accompanied by a reliability score, using the scale that has been proposed by the Partnership for Carbon Accounting Financials (PCAF) so investors can understand the quality of the underlying datapoint.<\/p>\n

Bloomberg\u2019s carbon emissions data is available via the Bloomberg Terminal. A subset of this carbon data is also available to Bloomberg Data License clients and can be accessed via Bloomberg\u2019s ready-to-use data website, data.bloomberg.com<\/a>.<\/p>\n

Bloomberg\u2019s carbon emissions data is one of Bloomberg\u2019s sustainable finance solutions, which offer data-driven insights to help investors integrate ESG throughout the full investment process and standardize company-reported and third-party ESG data. These solutions include ESG news and research content, indices, scores, analytics, research workflows and regulatory solutions. To learn more, click here<\/a>.<\/p>\n

About Bloomberg<\/strong><\/p>\n

Bloomberg is a global leader in business and financial information, delivering trusted data, news, and insights that bring transparency, efficiency, and fairness to markets. The company helps connect influential communities across the global financial ecosystem via reliable technology solutions that enable our customers to make more informed decisions and foster better collaboration.<\/p>\n

For more information, visit\u00a0Bloomberg.com\/company<\/a>\u00a0or\u00a0request a demo<\/a>.<\/p>\n

Media Contact<\/strong><\/p>\n

Jennifer Molgano
\njmolgano2@bloomberg.net<\/p>\n\n<\/div>\n\n\n<\/div>\n\n\t\t\n\t<\/div>\n<\/div>\n\n","protected":false},"excerpt":{"rendered":"

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