The Influence of ESG Scores and Financial Indicators When Using Artificial Neural Networks in Profit Forecasting

Abstract

This study aims to estimate the net profit before extraordinary items, as determined by the accounting information system of companies using artificial neural networks, a method of artificial intelligence, and compare it with the actual value. In this context, the results and error rates for the estimation of net profit before extraordinary items were determined using the ESG (environmental, social, governance) score, environmental support score, social support score, administrative support score, total assets, total revenue, total debt and net profit before extraordinary items of 28 companies operating in the industrial sectors of 9 countries between 2013 and 2022. It has been established that there is a parallelism between the real value and the estimated value of the net profit before extraordinary items.