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KPMG Austria: Automatic ESG data scraping and processing to derive ESG scores for companies worldwide

Started ‎04-07-2021 by
Modified ‎10-20-2022 by
Views 2,583

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Team Name KPMG Austria
Track Banking
Use Case

During the SAS Hackathon KPMG developed an algorithm to automatically identify ESG risks of companies worldwide by using Web Scraping, Machine Learning and Natural Language Processing. Every single company with an ISIN gets assigned an ESG score between 0 (min risk) and 1 (max risk).

 

This will help portfolio managers to identify green and brown companies. Further measures can then be evaluated as for example increase investment in green assets, decrease investment in brown assets, disclose important information for stakeholders, and define a Green Asset Ratio.
Technology SAS, Python
Region Austria
Team lead Fabius Lenhart @Risk_Fabius 
Team members

@Risk_Richard 

@Risk_Raffael 

@Risk_Fabius 

@RomanD 

@13erger 

@Risk_Dominik 

@Sebastian_S 

@Risk_Martijn 

 

Version history
Last update:
‎10-20-2022 12:32 PM
Updated by:

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