Centro de Documentacion de Fundación MAPFRE - Time series data mining with an application to the measurement of underwriting cycles

Notes: Sumario: Underwriting cycles are believed to pose a risk management challenge to property-casualty insurers. The classical statistical methods that are used to model these cycles and to estimate their length assume linearity and give inconclusive results. Instead, this article proposes to use novel time series data Mining algorithms to detect and estimate periodicity on U.S. property-casualty insurance markets. These algorithms are in increasing use in data science and are applied to Big Data. Related records: En: North American actuarial journal. - Schaumburg : Society of Actuaries, 1997- = ISSN 1092-0277. - 02/09/2019 Tomo 23 Número 3 - 2019 , p. 469-484Materia / lugar / evento: Cálculo actuarial Modelos actuariales Big data Matemática del seguro Empresas de seguros Análisis de riesgos Estados Unidos Otros autores: Owadally, Iqbal
Zhou, Feng
Otunba, Rasaq
Lin, Jessica
Wright, Douglas
Other categories: 6

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