Machine Learning in Insurance

Machine learning is a relatively new field, without a unanimous definition. In many ways, actuaries have been machine learners. In both pricing and reserving, but also more recently in capital modelling, actuaries have combined statistical methodology with a deep understanding of the problem at hand...

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Detalles Bibliográficos
Otros Autores:	Nielsen, Jens Perch (Editor), Asimit, Alexandru (Otro), Kyriakou, Ioannis
Formato:	Libro electrónico
Idioma:	Inglés
Publicado:	Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2020
Materias:	History of engineering & technology deposit insurance implied volatility static arbitrage parameterization machine learning calibration dichotomous response predictive model tree boosting GLM validation generalised linear modelling zero-inflated poisson model telematics benchmark cross-validation prediction stock return volatility long-term forecasts overlapping returns autocorrelation chain ladder Bornhuetter-Ferguson maximum likelihood exponential families canonical parameters prior knowledge accelerated failure time model chain-ladder method local linear kernel estimation non-life reserving operational time zero-inflation overdispersion automobile insurance risk classification risk selection least-squares monte carlo method proxy modeling life insurance Solvency II claims prediction export credit insurance semiparametric modeling VaR estimation analyzing financial data
Ver en Biblioteca Universitat Ramon Llull:	https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009654760106719