US 11,790,385 B2
ESG forecasting
Nadia Farooq, New York, NY (US)
Assigned to S&P Global Inc., New York, NY (US)
Filed by S&P Global Inc., New York, NY (US)
Filed on Apr. 13, 2021, as Appl. No. 17/301,745.
Prior Publication US 2022/0327567 A1, Oct. 13, 2022
Int. Cl. G06Q 30/02 (2023.01); G06Q 40/06 (2012.01); G06Q 30/0201 (2023.01); G06Q 10/04 (2023.01)
CPC G06Q 30/0206 (2013.01) [G06Q 10/04 (2013.01); G06Q 30/0201 (2013.01); G06Q 40/06 (2013.01)] 27 Claims
OG exemplary drawing
 
1. A computer-implemented method of forecasting financial performance of companies, the method comprising:
using a number of processors to perform the steps of:
retrieving from a database, through an application programming interface via JavaScript Object Notation format query, a number of news articles related to a number of companies published within a predefined time period;
vectorizing the news articles;
creating an artificial neural network comprising a sentiment scoring model and an environmental, social, and governance forecast model implemented as nodes in the artificial neural network;
feeding the news articles into the sentiment scoring model;
generating, by the sentiment scoring model implemented in an artificial neural network that employs semantic orientation or Vader sentiment analysis, a number of sentiment scores for the companies over the predefined time period;
feeding the sentiment scores, and historical market data and environmental, social, and governance data related to the companies into the environmental, social, and governance forecast model; and
forecasting, by the environmental, social, and governance forecast model, financial performance of the companies in relation to environmental, social, and governance policies comprising ratings assessing the companies' behavior and policies regarding their environmental performance, social impact and governance issues.