The insurance companies are extremely interested in the prediction of the future. Accurate prediction gives a chance to reduce financial loss for the company.
The insurers use rather complex methodologies for this purpose. The major models are a decision tree, a random forest, a binary logistic regression, and a support vector machine. A great number of different variables are under analysis in this case. The algorithms involve detection of relations between claims, implementation of high dimensionality to reach all the levels, detection of the missing observations, etc. In this way, the individual customer's portfolio is made.
