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Our proprietary ESG AI Engine leverages Natural Language Processing to understand which pieces of text count as 'ESG relevant' and which ones dont.
ESG in investing brings together the worlds of financial markets and environmental sustainability. ESG-mandated assets are projected to account for half of all professionally managed assets globally by 2024, according to Deloitte.
But the current state of ESG is flawed. ESG data and ratings are:
• inconsistent (i.e., not standardized), and
• incomplete (i.e., lacking comprehensive data).
We leverage machine learning and natural language processing (NLP) to collect, structure, and analyze ESG data at scale.
AI improves the volume, speed, and accuracy of ESG ratings at 2 key steps in the ratings process: 1) data collection; and 2) data analysis and scoring.
We process millions of documents daily across media, PR, opinions and blogs.
Our Company Context engine determines which companies and stock tickers are involved in each text.
Our ESG AI Engine identifies which text is 'ESG relevant' and what tags to add to them. Non ESG information is discarded.
Domain specific sentiment analysis model is run on the text, giving a score of -1 (negative) to +1 (positive) creating the ESG Pulse
"This is the future of ESG - real time information, from things outside of what companies disclose. This helps us keep track"
"We used ESG Analytics API as part of a dissertation on market based sentiment data. It was a key input into our research."
"We used ESG Analytics to complement our existing research process. Their AI powered analysis provided an 'outside-in' view for the companies we analysed.
Get started with the ESG Analytics today
