WSEAS Transactions on Environment and Development
Print ISSN: 1790-5079, E-ISSN: 2224-3496
Volume 20, 2024
Machine Learning Predictive Modeling for assessing Climate Risk in
Finance
Authors: , , ,
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.
Search Articles
Keywords: Climate Risk, Machine Learning, Supply Chain Finance, Blockchain, Predictive Models,
Generalized Models
Pages: 852-862
DOI: 10.37394/232015.2024.20.80