This abstract relates to the following paper: BlakeD., CairnsA. J. G., DowdK. and KesslerA. R.Still living with mortality: the longevity risk transfer market after one decadeBritish Actuarial Journal, 23. doi: 10.1017/S1357321718000314.

It has been remarked on many occasions that whilst there is a plethora of material which has been contributed to the Institute and the Students' Society on the actuarial valuation of liabilities, the subject of valuation of assets seems to have been consistently overlooked by all save one or two authors. We believe that a compelling reason for this apparent indifference to the subject may be found in the trend of interest rates within the experience of the actuaries who introduced the valuation techniques which a student may now tend to take for granted.

Consider Table 1, compiled from information given in a paper by C. M. Douglas, F.F.A., on ‘The Statistical Groundwork of Investment Policy’. During the period 1833–1912 the average annual rate neither exceeded £3. 11s. od.% nor fell below £2. 9s od.%, and in general the yield drifted slowly downwards.

As far as we are aware there have been no life insurance demutualizations in the U.K. in recent times, that is conversions from mutual to proprietary form. There has been movement in the other direction: in the 1960's a number of U.K. proprietary companies converted to mutual form to escape the unwelcome attentions of the corporate raiders of the time.

In the U.S. and South Africa however, the two countries which give us the demutualization examples in this paper, there have been in recent years a number of significant demutualizations. In the next chapter we give a sketch of the background to demutualization in these countries.

In Section 3 we explore why a mutual might wish to undergo such a lengthy, costly and probably painful process. The motivation will vary from country to country, depending on the particular economic and institutional background. We have tried to be as general as possible.

We explore some of the risks related to Artificial Intelligence (AI) from an actuarial perspective based on research from a transregional industry focus group. We aim to define the key gaps and challenges faced when implementing and utilising modern modelling techniques within traditional actuarial tasks from a risk perspective and in the context of professional standards and regulations. We explore best practice guidelines to attempt to define an ideal approach and propose potential next steps to help reach the ideal approach. We aim to focus on the considerations, initially from a traditional actuarial perspective and then, if relevant, consider some implications for non-traditional actuarial work, by way of examples. The examples are not intended to be exhaustive. The group considered potential issues and challenges of using AI, related to the following key themes:

• Ethical

  • ○ Bias, fairness, and discrimination

  • ○ Individualisation of risk assessment

  • ○ Public interest

• Professional

  • ○ Interpretability and explainability

  • ○ Transparency, reproducibility, and replicability

  • ○ Validation and governance

• Lack of relevant skills available

• Wider themes

This paper aims to provide observations that could help inform industry and professional guidelines or discussion or to support industry practitioners. It is not intended to replace current regulation, actuarial standards, or guidelines. The paper is aimed at an actuarial and insurance technical audience, specifically those who are utilising or developing AI, and actuarial industry bodies.

This paper describes how statistical methods can be tested on computer-generated data from known models. We explore bias and percentile tests in detail, illustrating these with examples based on insurance claims and financial time series.

This paper considers the variety of social security and complementary pension scheme arrangements which have developed in different countries, and examines some recent trends in pension reforms, designed to address the problem of the ageing population and other structural shortcomings in existing structures.

This research employs a vector autoregression (VAR) analysis to explore the volatility and dynamic interactions between stock, commodity, and cryptocurrency markets. It focuses on the returns of the S&P 500, gold, crude oil, and Bitcoin to analyse their interconnections. Our results indicate that Bitcoin returns positively affect S&P 500 and crude oil, but negatively impact gold. Conversely, crude oil returns have a positive influence on gold but lead to decreased returns for Bitcoin and the S&P 500. Similarly, higher gold returns correspond to increased returns in crude oil and S&P 500 but decreased returns in Bitcoin. The rise of the S&P 500 negatively influences Bitcoin and crude oil returns, while gold returns remain unaffected. However, these relationships exhibit weak and limited strength. Including these assets in a portfolio can help risk mitigation, as Bitcoin diversifies crude oil, gold, and S&P 500, and crude oil diversifies S&P 500. These findings contribute to our understanding of global financial dynamics and inform decision-making in risk assessment, portfolio management, risk mitigation, and diversification strategies.

The subject of sickness insurance does not appear to have been previously discussed before this Institute except in relation to Friendly Societies and the National Health Insurance Act. There is, however, a most comprehensive paper by Mr W. A. Robertson, the present President of the Faculty, in the Transactions, Vol. xiv, page 21. Disability in the sense of long-term sickness insurance has been considered on several occasions, but purely as an added benefit to life assurance contracts. The results shown by the American offices, who at one time transacted a large volume of this business, have been anything but encouraging.