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This paper examines in details six overlooked facts of using generalized linear models (GLMs) for non-life pricing and discusses whether the use of GLMs is still fit for purpose in a competitive market. The six facts of GLMs discussed are

1. Either zero or full credibility is given to the data and there is no way to do blending

2. Prediction of a risk depends on data in other completely independent segments

3. Model predictions depend on the mixture of rating factors in the data

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Calculating deterministic reserves is no longer sufficient in our times of enhanced Risk Management. Today, Insurers strive to have a complete view of the risk underlying reserves valuation: therefore stochastic projection methods become central to today’s actuaries.

It is even more the case with the Solvency II European Regulation which requires a VaR99.5% valuation… and consequently a very robust stochastic model to obtain a credible tail valuation.

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The aim of the paper is to provide general insurance actuaries a starting point for evaluating and engaging with ruin theory in a practical manner. Towards this goal, the paper undertakes three tasks. First, it sets out the basic mathematical principles behind the classical model with mixed exponential claim distributions. In particular, this part contributes to the reference literature in that the discussion is extraordinarily detailed. Second, it highlights risk management questions that could be contemplated already by this classical model.

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