this paper examines whether combining generalized hyperbolic skew-t distribution, recently introduced in the field of insurance, and extreme value theory (evt) could result in a modeling of loss function that could model central value as well as extreme value in appropriate manner. the data used in this study are the amount of property damage and bodily injury covered under automobile liability...

Organizations use data mining to improve their customer relationship management processes. Data mining is a new and well-known technique, which can be used to extract hidden knowledge and information about customers’ behaviors. In this paper, a model is proposed to enhance the premium calculation policies in an automobile insurance company. This method is based on customer clustering. K-means a...

In classification ratemaking, the multiplicative and additive models derived by actuaries are based on two common methods; minimum bias and maximum likelihood. These models are already considered as established and standard, particularly in automobile and general liability insurance. This paper aims to identify the relationship between both methods by rewriting the equations of both minimum bia...

The prediction of an adequate amount of claim reserves is of the greatest importance to face the responsibilities assumed by an insurance company. Although many different deterministic and stochastic methods based on statistical analyses are used for claims analysis, presence of many internal and external factors that increase the uncertainty in insurance environment may lead to considerable lo...

We show how data collected from a GPS device can be incorporated in motor insurance ratemaking. The calculation of premium rates based upon driver behaviour represents an opportunity for the insurance sector. Our approach is based on count data regression models for frequency, where exposure is driven by the distance travelled and additional parameters that capture characteristics of automobile...