Supplementary Files
Keywords
pricing
predictive modelling
linear models
additive models
mixed models
software R
seguros
tarificación
modelación predictiva
modelos lineales
modelos aditivos
modelos mixtos
paquete estadístico R
How to Cite
Abstract
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.
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