Introduction to Insurance Mathematics: Technical and by Annamaria Olivieri

By Annamaria Olivieri

The e-book goals at offering technical and monetary beneficial properties of lifestyles coverage, non-life coverage, pension plans. The booklet has been deliberate assuming non-actuarial readers as its “natural” objective, particularly - complicated undergraduate and graduate scholars in Economics, enterprise and Finance; - execs and technicians working in assurance and pension parts, whose task may perhaps regard investments, danger research, monetary reporting, and so on, and for that reason implies a verbal exchange with actuarial execs and bosses. Given the assumed goal, the e-book makes a speciality of technical and fiscal facets of assurance, even though keeping off using complicated mathematical instruments. during this feel, the e-book will be put at a few “midpoint” of the present literature, a part of which adopts extra formal ways to coverage difficulties implying using non-elementary arithmetic, while one other half addresses useful questions completely keeping off even easy mathematical instruments (which, in our opinion, can conversely supply powerful instruments for proposing technical and fiscal gains of the assurance business).

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Extra info for Introduction to Insurance Mathematics: Technical and Financial Features of Risk Transfers

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Xm the possible outcomes for every random amount Xk , k = 1, 2, . . , N. Then, the common probability distribution (that is, the same distribution for k = 1, 2, . . 27) fh = P[Xk = xh ]; h = 1, 2, . . , m The expected value x¯ = E[Xk ], k = 1, 2, . . 13). The case of no accident and hence damage equal to 0 is now accounted for by the outcome N = 0 of the random number of accidents. As regards the random number N, a discrete distribution should be obviously assigned. In particular, a finite distribution requires the choice of a reasonable maximum outcome nmax .

A possible accident causes a loss, whose amount depends on the severity of the accident itself. 001 The outcome X = 0 denotes that the accident does not occur. 64 Assume now that an accident (whatever its severity may be) does occur. The outcomes of the random losses are now restricted to the positive values, namely 24 1 Risks and insurance 100, 200, 300, 400, 500 Of course, the sum of the relevant probabilities must be equal to one. 1 can be formalized as follows. The probability p of an accident (whatever its severity may be) can be expressed, according to the notation adopted in Sect.

1, monitoring is not the “final” phase of the risk management process: indeed, no final phase exists because, after monitoring, the risk management process starts again, with the re-identification of risks in a possibly changed scenario, and so on. Hence, the risk management process is actually a never-ending “cycle”. 1 Some preliminary ideas As already mentioned in Sect. 2, risk assessment (or risk quantification) mainly aims at expressing in quantitative terms the impact of risks on significative target results (monetary outgoes, profits, and so on).

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