Date of Award

December 2020

Document Type


Degree Name

Master of Science (MS)


School of Mathematical and Statistical Sciences

Committee Member

Xiaoqian Sun

Committee Member

Yuyuan Ouyang

Committee Member

Mark Cawood


This thesis introduces two estimation mechanisms to estimate risk premium; namely, Bayesian premium and Bühlmann-Straub credibility premium. To implement the two models, we use a data set from Singapore Driving Experience in 1993. We estimate the average claim counts of each insured when weighted by their exposure of risk, i.e., given the record of claim counts and exposure weights, we build a model to estimate the claimcounts of the insured by means of Bayesian premium and Bühlmann-Straub credibility premium.



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