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

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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