Dissertation presented as partial requirement for obtaining the Master’s degree in Statistics and Information Management, with a specialization in Risk Analysis ManagementThe insurance activity offers their clients the opportunity to transfer risk in exchange of a fixed insurance premium. This premium should be enough to assure that the company will be able to respond to its possible future liabilities. These liabilities are, obviously, unknown when the premium is calculated, what means that they should be estimated a priori. However, different people belong to different risk classes, which leads to one of the big challenges of the insurance activity: the definition of a technically balanced tariff, or rate.
This dissertation has the objective to develop a pricing analytical model for Motor insurance using business factors and insured environment variables. In order to do so we need to treat our data and do exploratory analysis. After these preliminary steps we will construct two different models, one for claims’ frequency and another for claims’ severity using linear regressions in data mining. At the end of this work we pretend to indicate which variables explain better our data. The data we are using in this dissertation was provided by a Portuguese insurance company
