Analyzing global utilization and missed opportunities in debt-for-nature swaps with generative AI

We deploy a prompt-augmented GPT-4 model to distill comprehensive datasets on the global application of debt-for-nature swaps (DNS), a pivotal financial tool for environmental conservation. Our analysis includes 195 nations and identifies 21 countries that have not yet used DNS before as prime candi...

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Bibliographic Details
Published inFrontiers in artificial intelligence Vol. 7; p. 1167137
Main Authors Tkachenko, Nataliya, Frieder, Simon, Griffiths, Ryan-Rhys, Nedopil, Christoph
Format Journal Article
LanguageEnglish
Published Switzerland Frontiers Media S.A 05.02.2024
Subjects
adaptation finance
Artificial Intelligence
DNS
nature finance
nature-based solutions
retrieval augmented generation
sustainable credit finance
adaptation finance
retrieval augmented generation
generative AI
nature finance
sustainable credit finance
DNS
GPT-4
nature-based solutions
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Summary:We deploy a prompt-augmented GPT-4 model to distill comprehensive datasets on the global application of debt-for-nature swaps (DNS), a pivotal financial tool for environmental conservation. Our analysis includes 195 nations and identifies 21 countries that have not yet used DNS before as prime candidates for DNS. A significant proportion demonstrates consistent commitments to conservation finance (0.86 accuracy as compared to historical swaps records). Conversely, 35 countries previously active in DNS before 2010 have since been identified as unsuitable. Notably, Argentina, grappling with soaring inflation and a substantial sovereign debt crisis, and Poland, which has achieved economic stability and gained access to alternative EU conservation funds, exemplify the shifting suitability landscape. The study's outcomes illuminate the fragility of DNS as a conservation strategy amid economic and political volatility.
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Qiang Kang, Florida International University, United States
Luisa Varriale, Independent Researcher, Napoli, Italy
Edited by: Peter Schwendner, Zurich University of Applied Sciences, Switzerland
Reviewed by: Bertrand Kian Hassani, University College London, United Kingdom
Present address: Nataliya Tkachenko, Lloyds Banking Group, Chief Data and Analytics Office, London, United Kingdom; Judge Business School, University of Cambridge, Cambridge, United Kingdom
ISSN:2624-8212
2624-8212
DOI:10.3389/frai.2024.1167137