Stochastic gradient boosting frequency-severity model of insurance claims.
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ABSTRACT:
SUBMITTER: Su X
PROVIDER: S-EPMC7458339 | biostudies-literature | 2020
REPOSITORIES: biostudies-literature
Publications
Stochastic gradient boosting frequency-severity model of insurance claims.
PloS one 20200831 8
The standard GLM and GAM frequency-severity models assume independence between the claim frequency and severity. To overcome restrictions of linear or additive forms and to relax the independence assumption, we develop a data-driven dependent frequency-severity model, where we combine a stochastic gradient boosting algorithm and a profile likelihood approach to estimate parameters for both of the claim frequency and average claim severity distributions, and where we introduce the dependence betw ...[more]
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