Enhancing Generalised Linear Models with Data Mining

Generalized linear models (GLM) appear to be a tool that has become very popular and have shown to be effective in the actuarial work over the past decade. Data mining methodologies are more recent and their popularity in the actuarial community is increasing. They have been used in insurance for risk prediction/assessment, premium setting, fraud detection, health costs predication, treatment management optimization, investments management optimization, customer retention research and acquisition strategies. The main reasons for the increasing attractiveness of the data mining approach is that it is very fast computationally and also overcomes some well-known shortcomings of traditional methods.