Developing machine learning models to evaluate the environmental impact of financial policies

The intersection of financial policies and environmental impact is a critical area of research given the urgent need to address climate change and sustainability challenges. This review article explores the current state of machine learning (ML) models used to evaluate the environmental impact of financial policies. We discuss the methodologies, applications, challenges, and future directions of this interdisciplinary field. Emphasis is placed on the integration of economic and environmental data, model interpretability, and the potential of ML to provide actionable insights for policymakers.