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Si us plau utilitzeu sempre aquest identificador per citar o enllaçar aquest document: https://hdl.handle.net/2445/113623
Social networks Big Data: Personality traits as an explanatory variable in GLM models for insurance claim counts
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In an industry such as the insurer, highly atomized and competitive, where price comparison engines allow customers to have greater control over information in decision-making; insurance companies are investing great part of their efforts to find new formulas that improve customer loyalty. In that sense, using Big Data generated from social networks such as Facebook, Twitter or YouTube, to know the policyholder’s personality, can be used as a strategy that allow companies to compete through personalized service and more competitive premiums. In this study, I analyze the framework to introduce personality as an explanatory variable in Generalized Linear Models for claims count and try to found out any empirical evidence of the relation between personality traits and insurance claims.
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Treballs Finals del Màster de Ciències Actuarials i Financeres, Facultat d'Economia i Empresa, Universitat de Barcelona, Curs: 2016-2017, Tutora: Catalina Bolancé Losilla
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DURÁN PROAÑO, Andrés Santiago. Social networks Big Data: Personality traits as an explanatory variable in GLM models for insurance claim counts. [consulted: 7 of August of 2026]. Available at: https://hdl.handle.net/2445/113623