Predictive modelling of losses in non-life insurance
Guardado en:
| Autor: | |
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| Formato: | artículo original |
| Estado: | Versión publicada |
| Fecha de Publicación: | 2020 |
| Descripción: | Accident and health insurance with differentiated premiums for homogeneous risk groups was analyzed. The estimation of these premiums on previous opportunities was in univariate form, which has the limitation that when there are risk groups with few observations, the results are very volatile and omit the information that could provide predictive variables. Therefore, it was decided to estimate the expected claims (which are an input in the premium calculation) with three multivariate models: ordinary linear, additive and mixed linear. Several were used in order to compare their forecasting capability. Performance was acceptable within both the fit and test samples in the case of ordinary linear and additive models with a difference of about 1% from the real data. Linear mixed could not make predictions for combinations of predictors not observed in the fit data. |
| País: | Portal de Revistas UCR |
| Institución: | Universidad de Costa Rica |
| Repositorio: | Portal de Revistas UCR |
| Lenguaje: | Español |
| OAI Identifier: | oai:portal.ucr.ac.cr:article/39030 |
| Acceso en línea: | https://revistas.ucr.ac.cr/index.php/matematica/article/view/39030 |
| Palabra clave: | insurance pricing predictive modelling linear models additive models mixed models software R seguros tarificación modelación predictiva modelos lineales modelos aditivos modelos mixtos paquete estadístico R |