Classification of climate-related insurance claims using gradient boosting

George Tzougas, Viet Dang, Asif John, Stathis Kroustalis, Debashish Dey, Konstantin Kutzkov

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The aim of this paper is to implement, one of the most representative
supervised learning approaches, the decision tree based ensemble method called gradient boosting for classifying the number of claims caused by storms in Greece using data from a major insurance company operating in Greece. Finally, a machine learning algorithm is used to for categorising the number of claims which have been occurred by a “storm event” into 3 categories: “no claims”, “1 claim”, “2 or more claims”.
Original languageEnglish
Pages (from-to)149-168
Number of pages20
JournalAnales del Instituto de Actuarios Españoles
Issue number28
Publication statusPublished - 15 Dec 2022


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