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Estatística
Título: A DATA SCIENCE AND ACTUARIAL APPROACH FOR GROUNDING RISK DILUTION STRATEGIES INVOLVING EXTREME WINDS IN SOUTHERN BRAZIL
Autor: TAYLOR OLIVEIRA FIDELIS
Colaborador(es): HELIO CORTES VIEIRA LOPES - Orientador
Catalogação: 29/JUN/2023 Língua(s): PORTUGUESE - BRAZIL
Tipo: TEXT Subtipo: THESIS
Notas: [pt] Todos os dados constantes dos documentos são de inteira responsabilidade de seus autores. Os dados utilizados nas descrições dos documentos estão em conformidade com os sistemas da administração da PUC-Rio.
[en] All data contained in the documents are the sole responsibility of the authors. The data used in the descriptions of the documents are in conformity with the systems of the administration of PUC-Rio.
Referência(s): [pt] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=63065&idi=1
[en] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=63065&idi=2
DOI: https://doi.org/10.17771/PUCRio.acad.63065
Resumo:
Increasing extreme weather events are putting insurance companies at risk,with losses reaching billions of dollars. In the South of Brazil, municipalities have suffered losses due to climate events, including a bomb cyclone that caused losses of around 2 billion of reais. These losses are largely insured, but evaluating the probability of losses due to natural disasters is difficult due to the intrinsic dependence between exposed risks. This dissertation seeks to study extreme winds in the Southern region of Brazil, aiming to understand how to price and dilute risk in high impact areas. The research involves the analysis of meteorological and economic data, insurance claims reported by insurers, premiums reported by insurers, population structure, GDP, topography, and other relevant variables for the research. The objective is to estimate loss scenarios resulting from extreme events and offer relevant information to evaluate strategies for diluting the risk of economic losses. The dissertation blends distinct areas, including Economics, Actuarial Science, Data Science, Statistics, and Mathematics.
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