Abstract: A method to forecast financial performance of companies is provided. The method comprises retrieving from a database news articles related to a number of companies published within a predefined time period. The news articles are classified as either ESG articles or non-ESG articles and then vectorized. A subset of relevant non-ESG articles are selected. The ESG and selected non-ESG articles are fed into a sentiment scoring model, which generates sentiment scores for the companies over the predefined time period. The sentiment scores are fed into an ESG forecast model along with historical market data and ESG data related to the companies. The ESG forecast model forecasts the financial performance of the companies in relation to ESG policies.

Abstract: A method of forecasting raw material demand is provided. The method comprises retrieving news articles related to raw material suppliers as well as raw material industry articles related to specified raw materials. The news articles are classified as either ESG articles or non-ESG articles. The news articles and raw material industry articles are vectorized, and a subset of relevant articles are selected from the non-ESG articles. The ESG articles, relevant non-ESG articles, and raw material industry articles are fed into a sentiment scoring model, which generates sentiment scores for the raw material suppliers as well as sentiment scores for the raw materials. The sentiment scores are fed into an ESG forecast model along with supply chain data related to the raw materials and ESG data related to the raw material suppliers. The ESG forecast model then forecasts demand for the raw material suppliers to supply the raw materials.

Abstract: A method to forecast financial performance of companies is provided. The method comprises retrieving from a database news articles related to a number of companies published within a predefined time period. The news articles are classified as either ESG articles or non-ESG articles and then vectorized. A subset of relevant non-ESG articles are selected. The ESG and selected non-ESG articles are fed into a sentiment scoring model, which generates sentiment scores for the companies over the predefined time period. The sentiment scores are fed into an ESG forecast model along with historical market data and ESG data related to the companies. The ESG forecast model forecasts the financial performance of the companies in relation to ESG policies.

Abstract: A method of forecasting raw material demand is provided. The method comprises retrieving news articles related to raw material suppliers as well as raw material industry articles related to specified raw materials. The news articles are classified as either ESG articles or non-ESG articles. The news articles and raw material industry articles are vectorized, and a subset of relevant articles are selected from the non-ESG articles. The ESG articles, relevant non-ESG articles, and raw material industry articles are fed into a sentiment scoring model, which generates sentiment scores for the raw material suppliers as well as sentiment scores for the raw materials. The sentiment scores are fed into an ESG forecast model along with supply chain data related to the raw materials and ESG data related to the raw material suppliers. The ESG forecast model then forecasts demand for the raw material suppliers to supply the raw materials.