ESG Events Clustering using Natural Language Processing

The integration of Environmental, Social and Governance (ESG) factors into investment decisions has accelerated in the last few years. In fact, Bank of America estimates a $20 trillion of asset growth in ESG funds over the next two decades. Evaluating ESG related events of a company is an important task to assess company ESG risk. For public companies, important changes should be covered by the media and possibly by several news. These news need to be grouped under the same ESG event before analysis. Up to now, human analysts have carried out this task manually, a time expensive task and source of possible error due to a large number of text data. The goal of this research is to use natural language processing (NLP) to ensure uniformity across work done by different analysts and analyze the possibility to automate the task in order to save time for future news grouping.

Uros Petricevic
Superviseur universitaire: 
Philippe Langlais
Partner University: