Description: Session 1b discussant comments

Description: Abstract: We introduce a logistic regression-based modeling approach for analyzing the U.S. insured mortality experience, including at advanced ages where less credible experience data are available. As a validation, we create a version of industry basic experience tables based on the model-estimated mortality and compare them to standard industry experience tables produced by the Society of Actuaries (SOA). The conclusion is that properly designed logistic modeling processes can more efficiently utilize available data to deliver solutions for multiple needs, including: a) testing mortality drivers’ statistical significances in explaining mortality variations; b) estimating normalized mortality slopes and mortality differentials such as how mortality increases by duration or varies between underwriting classes while product and attained-age distributions are controlled; and c) addressing analytical challenges such as extrapolating for ultimate mor tality, smoothing between select and ultimate estimations, and constructing multidimensional basic experience tables.

Description: The projection of future mortality experience constitutes a challenge for both actuaries and demographers. As we show, some of the currently used standard mortality projections have several shortcomings which might pose a serious threat to insurers, pension funds, and social security systems. In this paper, we propose a new projection methodology which overcomes these shortcomings. We introduce a model which allows mortality improvements to depend on age, period, and cohort, and we explain how the model can be estimated and applied. In particular, we show how coherent projections for several populations, i.e. males and females of the same country and populations from closely related countries, can be derived. The basis for these projections are coherent extrapolations of historical life expectancies. As aggregated mortality statistics, life expectancies typically exhibit steady patterns which often makes forecasting rather obvious. We observe that the incorporation of information on the mortality experience of other populations can have a significant impact on the projection for a given population. A comparison with other commonly used projection models shows that our methodology provides stable and highly plausible projections. Finally, we discuss uncertainties in our projection approach and explain how they can be accounted for. In order to illustrate our methodology, we derive fully specified projections for German males and females as members of a large reference set of European populations.

Description: Abstract for A Study of Measuring the Mortality Compression

Description: Living to 100 program

Description: For the purposes of risk management and stress testing, we characterize a spectrum of plausible extreme events, that we dub Grey Swans, by introducing a probabilistic method involving the concentration of measure phenomenon. As a result, stress tests can be triaged according to severity, probability and, now, information-based plausibility.

Description: Recently researchers, practitioners, and regulators had intense debates about how to treat the data collection threshold in operational risk modeling. There are several approaches under consideration—the empirical approach, the “naive” approach, the shifted approach, and the truncated approach—for fitting the loss severity distribution. Since each approach is based on a different set of assumptions, different probability models emerge. Thus, model uncertainty arises. When possible we investigate such model uncertainty analytically, otherwise we use Monte Carlo simulations. For specific parametric examples we consider exponential and Lomax distributions which are special cases of the generalized Pareto family. Our primary goal is to quantify the effect of model uncertainty on risk measurements. This is accomplished by evaluating the probability of each approach producing conservative capital allocations based on the value-at-risk measure. These explorations are further illustrated using a real data set for legal losses in a business unit (Cruz, 2002).

Description: This is the panel transcript for the 2017 LT100 Symposium Session 2C: Impact of Aging: What Can Individuals and the Private Sector Do to Address Challenges?

Description: This is the informal discussion transcript for Session 4B: Mortality Projections from the January 4-6, 2017 Living to 100 Symposium in Orlando.