When constructing parametric models to predict the cost of future claims, several important details have to be taken into account: (i) models should be designed to accommodate deductibles, policy limits, and coinsurance factors, (ii) parameters should be estimated robustly to control the...

With some regularity conditions maximum likelihood estimators (MLEs) al-ways produce asymptotically optimal (in the sense of consistency, efficiency, sufficiency,and unbiasedness) estimators. But in general, the MLEs lead to non-robust statisticalinference, for example, pricing models and risk...

Many quantities arising in non-life insurance depend on claim severity distributions, which are usually modeled assuming a parametric form. Obtaining good estimates of the quantities, therefore, reduces to having good estimates of the model parameters. However, the notion of ‘good estimate'...