Radosavljević, Katica and Bradić, Kristina and Đurđić, Danilo (2025) Sustainable agriculture in the digital age: innovations in insurance. In: Innovations in Insurance: from Traditional to Modern Market. University of Belgrade, Faculty of economics and business, Belgrade, pp. 75-92. ISBN 978-86-403-1879-2
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Radosavljević, Bradić, Đurđić - Innovations in Insurance... Ek fak. (2025).pdf - Published Version Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (494kB) |
Abstract
Sustainable agriculture acts as a crucial pillar of global development, supporting economic stability and resource conservation. Advances in data collection, remote sensing, and machine learning enabled policymakers to make more informed and timely decisions in sustainable farming systems. Furthermore, data driven approach has opened new opportunities for forecasting agriculture outcomes, and ultimately, for transforming agriculture insurance practices. By leveraging Big Data and advanced analytics, insurers can now more precisely estimate risk, reduce uncertainty, and form instruments tailored to farmers’ needs in changing climate. The chapter aims to examine how digital innovations in agriculture, particularly a machine learning-based insurance model, can deliver effective insurance solutions and enhance climate resilience in developing countries like Serbia. Furthermore, it explores the contribution of agriculture to sustainable development by examining key global trends and underlining agriculture’s vulnerability to climate change, particularly in developing countries like Serbia, where rising temperatures threaten GDP and productivity. It also highlights the increasing role of digitalization in modernizing agricultural practices and improving food security. Against this backdrop, the study presents a novel machine learning-based model for calculating agricultural insurance premiums using historical climate and agricultural data. The model integrates climate variability indicators and actuarial principles to calculate expected losses more accurately. Serving as a data-driven decision support tool, it aims to enhance risk assessment and promote sustainable, resilient insurance solutions in Serbia’s agricultural sector.
Item Type: | Book Section |
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Depositing User: | Unnamed user with email srdjan.jurlina@ien.bg.ac.rs |
Date Deposited: | 27 Aug 2025 12:09 |
Last Modified: | 27 Aug 2025 12:09 |
URI: | http://repository.iep.bg.ac.rs/id/eprint/1139 |
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