• Communications for Statistical Applications and Methods
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• v.30 no.5
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• pp.437-451
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• 2023

Generalized linear models and generalized linear mixed models (GLMMs) are fundamental tools for predictive analyses. In insurance, GLMMs are particularly important, because they provide not only a tool for prediction but also a theoretical justification for setting premiums. Although thousands of resources are available for introducing GLMMs as a classical and fundamental tool in statistical analysis, few resources seem to be available for the insurance industry. This study targets insurance professionals already familiar with basic actuarial mathematics and explains GLMMs and their linkage with classical actuarial pricing tools, such as the Buhlmann premium method. Focus of the study is mainly on the modeling aspect of GLMMs and their application to pricing, while avoiding technical issues related to statistical estimation, which can be automatically handled by most statistical software.

• The Korean Journal of Applied Statistics
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• v.13 no.2
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• pp.247-263
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• 2000

Natural catastrophe is defined as all damages caused by natural phenomenon such as typhoon, flood, inundation, windstorm, tidal wave, tremendous snowfall, drought,earthquake and to on It is classified at a huge hazard because of the large severity ofdamage In Korea, Fire Insurance policy includet the coverage clauses and rates of naturalcatastrophe like'Flood , Inundation Coverage Clause'and'Earthquake Coverage Clause'These clauses and rates do not reflect accurate risk of flood, inundation and earthauakein Korea. because those are tariff from other countries Hence, we determine the claimsize distributions and the rates for typhoon coverage and flood-inundation coverage byusing statistical methods which have not been used so far in Korean non-life insurance,and calculate appropriate premium for policyholder's interest