Data Science Salon 2020

Automated Detection of Environmental, Social, and Governance Issues in Financial Documents



There is an immense amount of unstructured data generated every day that can affect companies and their position in the financial markets. A critical task for decision makers is to quantify and analyze this data to quickly identify opportunity and risk.

One of the important indicators in this kind of analysis is ESG (environmental, social, and governance) rating, which identifies issues for a company in these critical areas. This session describes a natural language processing system which automatically achieves

this for documents coming from financial news & disclosures. The models have been deployed in production as part of a big data analytics platform of a leading data provider to the financial services industry.

About the speaker

Alina Petukhova

Alina is a senior data scientist at John Snow Labs, where she is working as a part of the Core team. Her recent work was focus on creating models and pipelines to process business documents and news information to be able to extract structured information from unstructured data in the real time. John Snow Labs is an AI company, focused on NLP, accelerating progress in data science by providing state-of-the-art models, data, and platforms. Before joining John Snow Labs she was working for more than 5 years as a consultant in the area of NLP and Predictive modeling and completed her Ph.D. studies in Apply Mathematics. In her free time, she enjoys hiking and watching indie movies.