Unveiling the relationship between ESG and net profit via artificial intelligence : LGBM + XAI

With the advent of the coronavirus 19 era, the importance of ESG in investment is increasingly emphasized. Moreover, with the increasing trend of ESG investment, there exists a tendency to analyze it through AI models. As the existing research about ESG could not explain the relationship between ESG and profit, our research aims to derive the correlation between them via statistical models. We got the dataset from the kaggle website, which involved numerous financial variables and ESG features. Multitudinous models from machine learning and deep learning were utilized for the prediction and the LGBM yielded 0.07 of MAE score, which was the lowest. Moreover, SHAP algorithm and R-squared score were applied in pursuit of better prediction. ESG variable was the third highest feature among variables in the given dataset and R-squared score released 0.99. Both methods proved the high positive relationship between the ESG variable and the net profit margin ratio. Though our research involved a critical limitation that we could not employ various formulas due to the restricted dataset, our research is worthwhile as we successfully derived the positive correlation more accurately compared to previous research.