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LOSS FUNCTION IN ACTURIAL SCIENCE AND ESTIMATION
ABSTRACT
The objective of this thesis is to gain a comprehensive understanding of loss functions and their estimation in the context of non-life insurance pricing. Non-life insurance pricing involves determining the premium or tariff that policyholders pay to insurance companies in order to transfer the risk. A crucial aspect of this process is accurately estimating the distribution of claims and claim frequencies.
To achieve this objective, various concepts from Measure Theory, Probability Theory, and Statistics have been combined and applied in the analysis of loss functions and their estimation. In particular, an insurance dataset available on the Kaggle platform (https://www.kaggle.com) has been utilized to illustrate the practical implementation of these concepts. The statistical software R has been employed to obtain the results of our study.
By delving into the intricacies of loss functions and their estimation, this thesis aims to contribute to the advancement of non-life insurance pricing methodologies. The insights gained from this research can aid insurance companies in making informed decisions regarding premium calculation and risk management.
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