Artificial Intelligence-Based ESG Greenwashing Detection: Road to Net Zero Carbon and Its Impact on Corporate Performance
Penulis/Author
Ratna Candra Sari (1); Mahfud Sholihin, Prof., Ph.D., Ak., CA., CPA (Aust) (2); Fitra Roman Cahaya (3); Abdullahi Ishola (4); Nurhening Yuniarti (5); Arin Pranesti (6); Annisa Ratna Sari (7); Haryanto (8)
Tanggal/Date
2025
Kata Kunci/Keyword
Abstrak/Abstract
To respond to public criticism on environmental issues, some businesses have significantly improved their environmental performance. Others, on the other hand, have responded symbolically by making little to no changes or by performing greenwashing. While much research has examined greenwashing, AI-based techniques for identifying it have received less attention. The aim of this study is to validate the robustness of our AI-based greenwashing detection (AI-GW). In this study, our proposed AI-GW model is cross-tested with the existing ESG datasets from trusted and reputable financial and market data providers, namely Thomson Reuters and Bloomberg. Further, we examine the impact of greenwashing on corporate performance. To test the hypotheses, we use panel data gathered from all the Indonesian companies that have provided full ESG disclosures from 2017 to 2022. This study finds no difference between greenwashing scores based on our AI-GW and the database. This study also finds a positive correlation between AI-GW and greenwashing scores from a database. Further, the findings show that greenwashing consistently has a negative significant effect on financial performance when using our AI-GW-derived scores and the database-derived data. The results of this study provide support for the validity of the AI-based greenwashing detection method we developed.
