In an increasingly uncertain, complex socio-economic, and geopolitical environment, the significance of information signals and their perception becomes more crucial, especially in assessing sustainability and environmental impact. The challenges arise from businesses' lack of transparency and reported data, making it difficult for investors and rating agencies to evaluate and manage risks, costs, sustainability, risk-adjusted performance, greenwashing, fiduciary duty clarification, and scoring. This emphasizes the substantial impact of a high level of ambiguity on the market.
Considering the three pillars of ESG parameters, we propose a novel model for
assessing an ESG Rating based on i) the level of disclosure, representing the quality of the signal and released information, and ii) the subjective perception ofthe signal itself. This perception can be influenced by factors such as personal
risk aversion and ESG disagreement arising from controversies in the rating process. Recognizing the identified distortion in the ESG rating as having predictive power, where ambiguity can been seen as a way to represent the market's sentiment, the distortion turns out to play the role of a policy driver capable of identifying sectors where ESG is under/overestimated and testing the robustness of a scoring method.