Measures of solvency in the regulation of the UK life assurance industry
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The problem of designing appropriate solvency regulations is addressed with respect to the U. K. life assurance industry using various theoretical and methodological techniques. These alternative approaches to the measurement of insurer solvency are explored in order to provide a framework for assessing regulations. Reviews of the current insurance regulatory environment as well as an extensive statistical and economic analysis of the life assurance industry provide a practical backdrop to subsequent model building. Building on these reviews, a 'Monte-Carlo' simulation model of an insurer portfolio is constructed to demonstrate additional considerations relevant to solvency regulation. The hypothetical insurance company is assumed to maximise the expected utility of 'ultimate surplus', which is taken as an indicator of end-of-period wealth. Five asset classes are used and liabilities are assumed fixed. The simulated run-off performance of the portfolio is evaluated in terms of the probability of insolvency demonstrating a 'U' shaped relationship between the risk preference of the insurer and the insolvency probability. Implications for the design of regulatory constraints are also assessed with respect to the simulations. In particular, the contrast between ex ante and ex post measures of insurer solvency are highlighted with the conclusion taken that current regulations might gain further insight into the underlying solvency performance of insurance companies if they were to use ex ante solvency measures. This subsequent policy prescription is qualified by two factors: first, that the value of simulations and forecasting as an ex ante measure of performance is only as good as the models used to forecast ex ante; and second, that any proposed regulatory shift must be assessed within a cost-benefit analysis. Overall, the simulation analysis suggests that current regulations provide an incomplete picture of the solvency performance of the U. K. life assurance industry.
Thesis, PhD Doctor of Philosophy
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