Titlebook: Risk and Insurance; A Graduate Text Søren Asmussen,Mogens Steffensen Textbook 2020 Springer Nature Switzerland AG 2020 non-life insurance.l

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https://doi.org/10.1007/978-3-030-35176-2non-life insurance; life insurance; empirical Bayes; tails of sums; in homogeneous Markov processes; valu

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Chapter XIII: Selected Further Topics, often arise, and the total claim amount may not be known at the time the claim occurs. One typical example is accident insurance, where the degree of disability is not a priori known and treatment takes place over a period.

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Chapter II: Experience Rating,Let .  =  (.., …, ..) be a vector of r.v.s describing the outcome of a statistical experiment. For example, in the insurance context, . can be the number of persons insured for losses due to accidents in the previous year, and .. the payment made to the .th.

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Chapter III: Sums and Aggregate Claims,In this chapter, we study the often encountered problem of assessing the order of magnitude of . for some sequence .., .., … of r.v.s and .. = .. + ⋯ + ... In many applications, . is an r.v. . rather than deterministic, and the object of interest is then ..

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Chapter VII: Special Studies in Life Insurance,In this section, we study two extensions to the general Markov framework studied in Chap. V. The two extensions draw to some extent on the same mathematical generalization, but arise from two practically very different sources. One extension is an extension to duration-dependent intensities.