Machine Learning Predictive Modeling for assessing Climate Risk in Finance

Abstract

We investigate how the application of advanced predictive models could help investors to assess and manage climate risk in their portfolios, contributing to the development of more sustainable and resilient investment practices. We highlight the possible applications of predictive analytics as a key tool in climate finance. It emerges how emerging technologies (blockchain and Artificial Intelligence) can improve transparency, efficiency, and climate risk analysis in sustainable investments. Further lines of research are highlighted, focusing on how investors and portfolio managers can develop strategies to manage the risks associated with climate events and the integration of climate risks into the management of Supply Chain Finance to ensure greater resilience and sustainability. Some generalized models are analyzed focusing the most important aspects and features by which modeling Climate risks and related issues in financial frameworks.