Predictive analytics in climate finance: Assessing risks and opportunities for investors
1 Sanctus Maris Concepts Ltd, Nigeria.
2 Independent Researcher, Athens, Georgia.
3 Independent Researcher, Lagos, Nigeria.
4 Independent Researcher, Maryland, USA.
5 Independent Researcher, Chicago USA.
6 Access Bank Plc, Nigeria.
Review Article
GSC Advanced Research and Reviews, 2024, 18(02), 423–433.
Article DOI: 10.30574/gscarr.2024.18.2.0076
Publication history:
Received on 14 January 2024; revised on 25 February 2024; accepted on 27 February 2024
Abstract:
Predictive analytics is increasingly recognized as a pivotal tool in climate finance, offering investors invaluable insights into both the risks posed by climate change and the opportunities for sustainable investment. This Review delves into the burgeoning field of predictive analytics within climate finance, emphasizing its significance in aiding investors to navigate the multifaceted landscape of climate-related risks and opportunities. By leveraging advanced data analytics techniques, predictive analytics empowers investors to anticipate and mitigate climate-related risks, ranging from physical risks such as extreme weather events and sea-level rise to transition risks associated with regulatory changes and technological shifts. Moreover, predictive analytics enables investors to identify emerging opportunities in sectors poised for sustainable growth, such as renewable energy, clean technology, and climate resilient infrastructure. This Review also sheds light on the methodologies and data sources utilized in predictive analytics for climate finance, encompassing climate models, satellite imagery, socioeconomic indicators, and financial data. Through the analysis of historical trends and future projections, predictive analytics provides investors with actionable insights to inform their investment decisions and align their portfolios with climate-related goals and mandates. Despite its potential benefits, the adoption of predictive analytics in climate finance is not without challenges. This Review examines the hurdles associated with data quality, model uncertainty, regulatory complexities, and the integration of climate-related factors into financial decision-making processes. Addressing these challenges necessitates interdisciplinary collaboration, robust risk assessment frameworks, and ongoing innovation in predictive analytics methodologies. In conclusion, this Review underscores the critical role of predictive analytics in climate finance and its transformative potential in enhancing the resilience and sustainability of investment portfolios. By harnessing the power of data-driven insights, investors can proactively manage climate-related risks, capitalize on sustainable investment opportunities, and contribute to the transition towards a low-carbon economy. As climate change continues to exert profound impacts on financial markets, the integration of predictive analytics represents a strategic imperative for investors seeking to navigate the evolving landscape of climate finance effectively.
Keywords:
Investors; Predictive Analytics; Climate Finance; Risks; Opportunities
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Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0
