Actuarial risk assessments

Note that some of the risk information is actuarial (based on statistical data, typically collected and organized by insurance companies), and some of it has been derived from the type of risk assessment discussed in this book (chloroform in chlorinated drinking water, afla-toxin in peanut products). While the uncertainties associated with the figures in Table 11.2 are much greater for some risks than for others (not a trivial problem in presentation of risk data), such a presentation, it would seem, is helpful to people who are trying to acquire some understanding of extremely low probability events, of the order of one-in-one million. 

A natural gas high pressure pipeline with a diameter of 20" (508 mm), a wall thickness of 8 mm subject to a pressure of pi = 70 bar is planned in the vicinity of a residential area. For the section passing close by this residential area a risk assessment is to be performed. This is a so-caUed risk-based analysis, since the expected frequency of the undesired event (rupture of the pipeline and gas release) is directly taken from statistical material (actuarial approach) and not determined by a detailed analysis of the engineered systems involved. 

Therefore, extreme value projection may be useful in calculation probabilities to be used for risk assessment codes or total risk exposure codes based on actuarial data. Extreme value projection can also be useful in communicating hazard information to management and may aid in drawing management attention to a problem before a serious accident occurs. 

Actuarial science is one of the largest and most thoroughly developed fields within risk assessment In actuarial science, statistics and probability are... 

Bisping M (2013) Risk transformation through capital markets. In Lane M (ed) Alternative (re)insurance strategies, 2nd edn. Risk Books, Chicago Clark K (1986) A Formal Approach to Catastrophe Risk Assessment and Management, in the Proceedings of the Casualty Actuarial Society, Vol. 73, Part 2, No. 140... 

Potential health and economic consequences of nuclear power plant accidents include early fatalities, early injuries, latent cancers, population doses, various health effects, and onsite and offsite costs. For such consequence measures, application of the preceding deftnition of risk becomes more complicated, because frequencies must be estimated for accidents with varying degrees of severity. For example, the frequency of transportation accidents involving 100 or more early fatalities is substantially lower than the frequency of transportation accidents involving only 1 fatality. In risk assessments, frequencies of accidents with all possible consequence levels are estimated. It is desirable to combine the risks associated with high, moderate, and low consequence accidents into an overall risk measure. For this purpose, the concept of actuarial or consequence-weighted risk is used. 

The total consequence-weighted risk is the sum of the consequence weighted risks of the individual accidents. The process of calculating consequence-weighted risk is illustrated in Table 2.6-1 for a hypothetical plant that has only four possible accidents. Consequence-weighted risk is so widely used in probabilistic risk assessments that the modifier consequence-weighted (or actuarial) is usually dropped, and the total consequence-weighted risk is simply called the plant risk. 

An investor acquiring a pool of mortgt es from a lender measures the amount of associated prepayment risk by using a financial model to project the level of expected future payments. Although it is impossible to evaluate with any accuracy the prepayment potential of an individual mortgage, such analysis is reasonable for a large pool of loans. This is similar to what actuaries do when they assess the future liability of an insurer that has written personal pension contracts. The level of prepayment risk for a pool of loans is lower than that for an individual mortgt e. 

Insurance models in actuarial sciences and financial engineering have a long history of development and wide applications in assessing underwriting risks. Popular approaches for characterizing catastrophic risk processes include a compound Poisson process (e.g., Rolski... 

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