Allowing for shocks in portfolio mortality models

The COVID-19 pandemic creates a challenge for actuaries analysing experience data that include mortality shocks. Without sufficient local flexibility in the time dimension, any analysis based on the most recent data will be biased by the temporarily higher mortality. Also, depending on where the shocks sit in the exposure period, any attempt to identify mortality trends will be distorted. We present a methodology for analysing portfolio mortality data that offer local flexibility in the time dimension. The approach permits the identification of seasonal variation, mortality shocks and occurred-but-not reported deaths (OBNR). The methodology also allows actuaries to measure portfolio-specific mortality improvements. Finally, the method assists actuaries in determining a representative mortality level for long-term applications like reserving and pricing, even in the presence of mortality shocks. Results are given for a mature annuity portfolio in the UK, which suggest that the Bayesian information criterion is better for actuarial model selection in this application than Akaike’s information criterion.

The IFRS 17 contractual service margin: a life insurance perspective

IFRS 17 Insurance Contracts is a new accounting standard currently expected to come into force on 1 January 2023. It supersedes IFRS 4 Insurance Contracts. IFRS 17 establishes key principles that entities must apply in all aspects of the accounting of insurance contracts. In doing so, the Standard aims to increase the usefulness, comparability, transparency and quality of financial statements. A fundamental concept introduced by IFRS 17 is the contractual service margin (CSM). This represents the unearned profit that an entity expects to earn as it provides services. However, as a principles-based standard, IFRS 17 results in entities having to apply significant judgement when determining the inputs, assumptions and techniques it uses to determine the CSM at each reporting period. In general, the Standard resolves broad categories of mismatches which arise under IFRS 4. Notable examples include mismatches between assets recorded at current market value and liabilities calculated using fixed discount rates as well as inconsistencies in the timing of profit recognition over the duration of an insurance contract. However, there are requirements of IFRS 17 that may create economic or accounting mismatches of its own. For example, new mismatches could arise between the measurement of underlying contracts and the corresponding reinsurance held. Additionally, mismatches can still arise between the measurement of liabilities and the assets that support the liabilities. This paper explores the technical, operational and commercial issues that arise across these and other areas focusing on the CSM. As a standard that is still very much in its infancy, and for which wider consensus on topics is yet to be achieved, this paper aims to provide readers with a deeper understanding of the issues and opportunities that accompany it.

Asset–liability modelling in the quantum era

This paper introduces and demonstrates the use of quantum computers for asset–liability management (ALM). A summary of historical and current practices in ALM used by actuaries is given showing how the challenges have previously been met. We give an insight into what ALM may be like in the immediate future demonstrating how quantum computers can be used for ALM. A quantum algorithm for optimising ALM calculations is presented and tested using a quantum computer. We conclude that the discovery of the strange world of quantum mechanics has the potential to create investment management efficiencies. This in turn may lead to lower capital requirements for shareholders and lower premiums and higher insured retirement incomes for policyholders.

Long-term stochastic risk models: the sixth generation of modern actuarial models?

This paper discusses the use of modelling techniques for the purpose of risk management within life insurers. The key theme of the paper is that life insurance is long-term business and carries with it long-term risks, yet much of modern actuarial risk management is focussed on short-term modelling approaches. These typically include the use of copula simulation models within a 1-year Value-at-Risk (VaR) framework. The paper discusses the limitations inherent within the techniques currently used in the UK and discusses how the focus of the next generation of actuarial models may be on long-term stochastic projections. The scope of the paper includes a discussion of how existing techniques, together with new approaches, may be used to develop such models and the benefits this can bring. The paper concludes with a practical example of how a long-term stochastic risk model may be implemented.

The importance of actuarial management in insurance business decision-making in the twenty-first century

This study aims to carry out and document a systematic analysis of the literature on the importance of actuarial management in insurance managerial decision-making in the twenty-first century. After a short introduction to the business context, the paper presents an analysis of a rigorous review of the literature published between the years 2000 and 2020, which highlights the benefits and challenges of the formal application of various risk management tools. The following topics are emphasized: (i) actuarial cycle control and uncertainty management, (ii) quantitative strategic risk framework and financial modelling, and (iii) enterprise risk management with a value-based approach. This work will help future researchers to gain a better understanding of, and explicitly account for, the different contributions and benefits of actuarial management in the context of managerial decision-making in an organisation.

The pensions dashboard: an actuarial perspective

The pensions dashboard has been talked about across the industry for a long time. With the proposed implementation date of 2019 (although it has been questioned by some whether this is achievable or not), it is time to consider the actuarial aspects behind providing individuals with details of their pension benefits. This paper outlines the perspective of the IFoA’s Future Pensions Landscape working party. The paper considers the objectives of the dashboard and the functionality that may be required to deliver on those. It also highlights the difficulties of the necessary consistency between different types of benefits and the need for alignment with other pensions communications. Lastly, it considers what is needed to enhance the dashboard to enable members to understand what their benefits might look like at retirement and the opportunities the dashboard delivers for further modelling and financial planning. Objectives and functionality Much has been made about the difficulty (or otherwise) of delivering on the promise of a pensions dashboard, but ultimately that will depend on what it aims to provide for the individual. The working party has considered the short and longer-term opportunities with a dashboard and what functionality these may require. It is clear that a balance between functionality and deliverability must be struck to ensure that something meaningful is delivered within a reasonable timeframe (2). Different types of benefits The working party has considered the features of occupational and personal pensions, defined benefit (DB) schemes (5.21), defined contribution (DC) schemes (5.25) and the state pension (3). We believe that it is essential to deliver key information around each of them in a way that is consistent but takes account of the differences between them, including the need to: use scheme/benefit-specific pension commencement dates (4); display accrued and prospective benefits at retirement in real terms (5.6, 5.20); display dependants’ benefits when a part of the scheme rules (5.12); display details of benefits in payment or already in drawdown (5.4); ensure that deferred DBs are revalued to a recent date (5.22); be clear about the level of pension increases payable using inflation linking as a default (5.17); and outline any options on a benefit such as tax-free pension commencement lump sum (5.8). Having included the above, the dashboard must then consider how to allow for consistency of projection of benefits to the scheme/benefit-specific pension commencement dates. For DBs, this can be achieved relatively easily in real terms by allowing merely for future accrual based on the current position and benefit structure. For DC benefits, this needs a standardised approach. After consideration of multiple options (5.25), we have recommended a simplified projection approach using a risk-based allowance for real investment growth depending on the assets held (or a risk categorisation) (5.50). This would enable the dashboard to carry out consistent projections across DC pots. In an ideal world, we recommend that benefit statements use projections aligned to this approach, too. In order to build confidence in any dashboard (and in pensions in general), consistency between benefit statements and scheme provision of information is key (8). This includes the need for dates and speed of information provision, the type of information provided and assumptions and projection approaches to be standardised. We have also considered other hybrid benefit structures that exist. Many or all of these can revert to using the approach outlined for DB, DC, or a combination of the two along with the expertise of a provider to achieve the aims of consistent dashboard provision (6). We have also tried to allow for some of the legacy or complex issues within the UK pensions landscape that we consider relevant to the provision of a usable dashboard, such as the need to include Guaranteed Annuity Rates, and the need to explain the various risks and uncertainties with both DB and DC provision (7). Future opportunities for supporting financial planning The working party has considered the longer-term opportunities to use the dashboard to assist individuals with planning for their retirement. We recommend that the dashboard infrastructure be set up with this in mind from the beginning, even if the deployment of this type of support is a long way away (9) or even provided through third parties (10). The working party looks forward to the Department for Work and Pensions feasibility study on the dashboard (which is due for publication) and welcomes the chance to influence the shape of what has the potential to be a huge engagement opportunity for the pensions industry.