The approaches to liability valuation, assessment of prudential capital and measurement of profit for life offices are undergoing radical change. A common thread runs through all of these proposed changes — each change represents a move away from traditional actuarial approaches towards a more economically coherent, market-consistent approach. These changes should encourage a general improvement in the life industry's risk management processes. However, they will come at a cost. The measurement of the economic risks generated by the complex guarantees written by life offices is far more difficult than applying the latest resilience test equity fall. This will require a step change in the sophistication of life offices' risk and capital measurement and management know-how. The measurement of value, risk and capital will soon demand the application of ‘stochastic’ modelling tools. In this paper, we explore some of the issues raised by the application of these approaches to the valuation and risk management of with-profits business.

Rapid developments in genetic science have been accompanied by confusion regarding the predictive power of DNA-based tests and in the impact of such tests on the insurance industry. The United Kingdom actuarial profession has begun to engage in the associated social policy issues and to try to throw some light on the issues through quantitative research and objective analysis. At the same time, many insurance industry actuaries have been involved in work on behalf of the insurance industry to develop a sound basis for permission to be sought to make use of the results of certain predictive genetic tests. This paper briefly outlines some of the history of the development of the debate in the U.K. and draws together some of the debates and discussions which have taken place within the Genetics Group of the Social Policy Board of the U.K. actuarial profession, as well as providing some pointers to the directions which the debate might take in the future, with some important potential consequences for the insurance industry and for actuaries.

For estimates of critical illness (CI) insurance premiums in the presence of a known mutation leading to a genetic disorder, the key quantity is the penetrance, that is the probability q(x) that the disease has developed by age x. This function is often estimated in the genetics literature, though typically with large confidence intervals. In this paper we suggest that the main features of real penetrance functions can be represented reasonably well by simple one-parameter families of functions, which can be scaled to fit the age range and lifetime penetrance. This gives a simple, direct, pragmatic way to obtain quick estimates of CI premium rates from published penetrance estimates, and also some indicative bounds for such premium rates, which are useful since confidence intervals usually cannot be estimated. To aid this process, as a short-cut to the solution of Thiele's equations in a multiple-state model, we give extensive tables in another report (Macdonald & Yang, 2003).

In this paper a system for recommending investment channel choices to members of defined contribution retirement funds is proposed. The system is interactive, using a member's answers to a series of questions to derive a utility function. The observed values are interpolated by means of appropriate formulae to produce a smooth utility function over the whole positive range of benefits at retirement. The resulting function, together with stochastic models of the returns on the available channels and of the annuity factor at exit, is then used to recommend an optimum apportionment of the member's investment. The proposed system is applied to the observed values of utility functions of post-retirement income elicited from members of retirement funds. Difficulties in the application are discussed and the results are analysed. The sensitivity of the recommendations to the parameters of the stochastic model is discussed.

We discuss classes of risk measures in terms both of their axiomatic definitions and of the economic theories of choice that they can be derived from. More specifically, expected utility theory gives rise to the exponential premium principle, proposed by Gerber (1974), Dhaene et al. (2003), whereas Yaari's (1987) dual theory of choice under risk can be viewed as the source of the distortion premium principle (Denneberg, 1990; Wang, 1996). We argue that the properties of the exponential and distortion premium principles are complementary, without either of the two performing completely satisfactorily as a risk measure. Using generalised expected utility theory (Quiggin, 1993), we derive a new risk measure, which we call the distortion-exponential principle. This risk measure satisfies the axioms of convex measures of risk, proposed by Föllmer & Shied (2002a,b), and its properties lie between those of the exponential and distortion principles, which can be obtained as special cases.