This paper updates Living with Mortality published in 2006. It describes how the longevity risk transfer market has developed over the intervening period, and, in particular, how insurance-based solutions – buy-outs, buy-ins and longevity insurance – have triumphed over capital markets solutions that were expected to dominate at the time. Some capital markets solutions – longevity-spread bonds, longevity swaps, q-forwards and tail-risk protection – have come to market, but the volume of business has been disappointingly low. The reason for this is that when market participants compare the index-based solutions of the capital markets with the customised solutions of insurance companies in terms of basis risk, credit risk, regulatory capital, collateral and liquidity, the former perform on balance less favourably despite a lower potential cost. We discuss the importance of stochastic mortality models for forecasting future longevity and examine some applications of these models, e.g. determining the longevity risk premium and estimating regulatory capital relief. The longevity risk transfer market is now beginning to recognise that there is insufficient capacity in the insurance and reinsurance industries to deal fully with demand and new solutions for attracting capital markets investors are now being examined – such as longevity-linked securities and reinsurance sidecars.

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.

A well-known feature of the great H1N1 influenza pandemic of a century ago is that the highest mortality rate was amongst young adults. The general explanation has been that they died from an over-reaction of their active immune systems. This explanation has never been very satisfactory because teenagers also have very active immune systems. Recent virological research provides a new perspective, which is important for life and health insurers. There is now strong recent scientific evidence for the principle of antigenic imprinting, where the highest antibody response is against influenza virus strains from childhood. The peak ages of 1918 pandemic mortality correspond to a cohort exposed to the H3N8 1889–1890 Russian influenza pandemic. The vulnerability of an individual depends crucially on his or her exposure to influenza during their lifetime, especially childhood. Date of birth is thus a key indicator of pandemic vulnerability. An analysis of the implications is presented, with focus on those now in their fifties, who were exposed to the H3N2 1968 Hong Kong influenza.

Some UK insurers have been using real-world economic scenarios for more than 30 years. Popular approaches have included random walks, time series models, arbitrage-free models with added risk premiums or 1-year Value at Risk distribution fits. Based on interviews with experienced practitioners as well as historical documents and meeting minutes, this paper traces historical model evolution in the United Kingdom and abroad. We examine the possible catalysts for changes in modelling practice with a particular emphasis on regulatory and socio-cultural influences. We apply past lessons to provide some guidance to the direction of capital market modelling in future, which has been key for business and strategy decisions.

This abstract relates to the following paper: Jakhria, P., Frankland, R., Sharp, S., Smith, A., Rowe, A. and Wilkins, T. (2019) Evolution of economic scenario generators: a report by the Extreme Events Working Party members. British Actuarial Journal. Cambridge University Press, 24. doi:10.1017/S1357321718000181.

Cyber Operational Risk: Cyber risk is routinely cited as one of the most important sources of operational risks facing organisations today, in various publications and surveys. Further, in recent years, cyber risk has entered the public conscience through highly publicised events involving affected UK organisations such as TalkTalk, Morrisons and the NHS. Regulators and legislators are increasing their focus on this topic, with General Data Protection Regulation (“GDPR”) a notable example of this. Risk actuaries and other risk management professionals at insurance companies therefore need to have a robust assessment of the potential losses stemming from cyber risk that their organisations may face. They should be able to do this as part of an overall risk management framework and be able to demonstrate this to stakeholders such as regulators and shareholders. Given that cyber risks are still very much new territory for insurers and there is no commonly accepted practice, this paper describes a proposed framework in which to perform such an assessment. As part of this, we leverage two existing frameworks – the Chief Risk Officer (“CRO”) Forum cyber incident taxonomy, and the National Institute of Standards and Technology (“NIST”) framework – to describe the taxonomy of a cyber incident, and the relevant cyber security and risk mitigation items for the incident in question, respectively.Summary of Results: Three detailed scenarios have been investigated by the working party:

• ∙ Employee leaks data at a general (non-life) insurer: Internal attack through social engineering, causing large compensation costs and regulatory fines, driving a 1 in 200 loss of £210.5m (c. 2% of annual revenue).

• ∙ Cyber extortion at a life insurer: External attack through social engineering, causing large business interruption and reputational damage, driving a 1 in 200 loss of £179.5m (c. 6% of annual revenue).

• ∙ Motor insurer telematics device hack: External attack through software vulnerabilities, causing large remediation / device replacement costs, driving a 1 in 200 loss of £70.0m (c. 18% of annual revenue).

• ∙ While the presented scenarios are deemed material at this point in time, the threat landscape moves fast and could render specific narratives and calibrations obsolete within a short-time frame.

• ∙ There is a lack of historical data to base certain scenarios on and therefore a high level of subjectivity is used to calibrate them.

• ∙ No attempt has been made to make an allowance for seasonality of renewals (a cyber event coinciding with peak renewal season could exacerbate cost impacts)

• ∙ No consideration has been given to the impact of the event on the share price of the company.

• ∙ Correlation with other risk types has not been explicitly considered.

The last 12 years have seen the evolution of a new funding regime under the supervision of the Pensions Regulator. Over this period, there has been significant turbulence in financial markets, including record low interest rates. This paper takes a critical look at the development of funding approaches and methodologies over this period. It analyses the Pensions Regulator guidance and how scheme specific actuarial methods have emerged since the move away from the Minimum Funding Requirement in 2001 and the introduction of the Scheme Specific Funding Requirements in 2005. It asks whether these new methodologies have been successful from the perspective of members, trustees, employers and shareholders. At a time when actuarial valuation methodologies have faced considerable criticism, this paper aims to propose a pension funding methodology which is fit for purpose and also reflects the latest guidance from the Pensions Regulator on integrated risk management.

This abstract relates to the following paper: Cowling, C. A., Fisher, H. J., Powe, K. J., Sheth, J. P. and Wright, M. M. (2019) Funding defined benefit pension schemes: An integrated risk management approach. British Actuarial Journal, Cambridge University Press, 24. doi: 10.1017/S135732171800034X .

This abstract relates to the following paper: Gitsels, L. A., Kulinskaya, E. & Wright, N. R. How medical advances and health interventions will shape future longevity. British Actuarial Journal. doi: 10.1017/S1357321719000059

Medicine-related research includes numerous studies on the hazards of mortality and what risk factors are associated with these hazards, such as diseases and treatments. These hazards are estimated in a sample of people and summarised over the observed period. From these observations, inferences can be made about the underlying population and consequently inform medical guidelines for intervention. New health interventions are usually based on these estimated hazards obtained from clinical trials. A lengthy lead time would be needed to observe their effect on population longevity. This paper shows how estimated mortality hazards can be translated to hypothetical changes in life expectancies at the individual and population levels. For an individual, the relative hazards are translated into the number of years gained or lost in “effective age”, which is the average chronological age with the same risk profile. This translation from hazard ratio to effective age could be used to explain to individuals the consequences of various diseases and lifestyle choices and as a result persuade clients in life and health insurance to pursue a healthier lifestyle. At the population level, a period life expectancy is a weighted average of component life expectancies associated with the particular risk profiles, with the weights defined by the prevalences of the risk factor of interest and the uptake of the relevant intervention. Splitting the overall life expectancy into these components allows us to estimate hypothetical changes in life expectancy at the population level at different morbidity and uptake scenarios. These calculations are illustrated by two examples of medical interventions and their impact on life expectancy, which are beta blockers in heart attack survivors and blood pressure treatment in hypertensive patients. The second example also illustrates the dangers of applying the results from clinical trials to much wider populations.

Digital technology is starting to enable new and improved modes of healthcare delivery. The healthcare and disability claims spaces are closely intertwined. Disability claimants certainly have healthcare needs but disability claims management has the added dimension of supporting return to work.

In this paper, we explain what is meant by the term “Digital Health.” We then compare the challenges in the healthcare and disability claims management spaces where digital technology may improve outcomes. We touch briefly on how the efficacy of digital technology may be evaluated. The later parts of the paper focus on Digital Health technology providers who have engaged with the insurance industry and we conclude with some learnings around the challenges of implementing these technology-based opportunities.

This paper focuses on interventions once a policyholder’s health has failed to the extent that they need to claim. There are many opportunities to improve wellness and prevent claim using digital technology, as noted by the IFoA Wearables and Internet of Things Working Party,1 and we do not discuss these further this paper.

Solvency II came into force on 1 January 2016 and included a transitional measure on technical provisions (“TMTP”) designed to help smooth in the capital impact of Solvency II over a 16-year period. The working party’s view is that the main intention of the TMTP is to mitigate the impact of the introduction of the risk margin, which significantly increases the technical provisions of firms, relative to their Solvency I Pillar 2 liabilities.

The majority of firms who hold a TMTP have now had at least one recalculation approved by the Prudential Regulation Authority (PRA); or are in the process of applying for a recalculation. Despite this large number of approved recalculations, there remains significant uncertainty in the industry around the approach and triggers for recalculation.

This paper considers aspects of TMTP recalculation for regulated UK life firms, for example practicalities of the calculation, asset and liability considerations, and communications/announcements.

In this paper, we outline the need for pragmatism when considering the approach to recalculation of a measure originally intended to serve as the bridge between two regimes. We call for an allowance for doing what is sensible in a principles-based regime balancing what might be more theoretically correct with what is practical and possible to support effective management of the business.

The Age-Period-Cohort-Improvement (APCI) model is a new addition to the canon of mortality forecasting models. It was introduced by Continuous Mortality Investigation as a means of parameterising a deterministic targeting model for forecasting, but this paper shows how it can be implemented as a fully stochastic model. We demonstrate a number of interesting features about the APCI model, including which parameters to smooth and how much better the model fits to the data compared to some other, related models. However, this better fit also sometimes results in higher value-at-risk (VaR)-style capital requirements for insurers, and we explore why this is by looking at the density of the VaR simulations.

This abstract relates to the following paper: Currie, I., Kleinow, T., Richards, S. and Ritchie, G. (2019) A stochastic implementation of the APCI model for mortality projections. British Actuarial Journal. Cambridge University Press, 24. doi:10.1017/S1357321718000260.

The term ‘investment risk’ is often used loosely, and frequently confused with the notion of short-term price volatility, particularly for equity instruments. For the long-term investor, however, what is most apposite is the ability to meet future real cash flows as they become due. This paper addresses the concept of economic fundamentals of long-term investment, the objectives of long-term investors (and how these differ from those of short-term investors), the notion of real value shortfall risk, what is meant by an investor’s risk capacity (as opposed to risk appetite) and liquidity management considerations. Subsequently, some of the constraints and barriers to appropriate risk measurement and management are considered, in particular the regulatory and behavioural biases that are overlaid on fundamental asset/liability management. Various alternative approaches to measuring risk, and their appropriateness for purpose, are outlined, in the hope of further informing the discussion and thereby helping to accelerate productive change.

Demographic and societal changes make it more and more indispensable to protect against the risk of care costs surpassing a person’s financial means. Nevertheless, only few governments have acted to create public funding systems that, if existent at all, usually only cover part of the expenses for elder care. Long-term care insurance (LTCI) is designed to fund basic care needs in later life, such as washing and dressing. Regardless of where individuals receive this support in old age, how it is funded is a growing issue. In many countries, people may augment their compulsory state system with private policies available from insurance companies.

In Germany, a well-established public system that underwent major reforms exists. From 2017 onwards, a completely new care definition and assessment process replaced the former ones. Two major changes constitute the reform: First, when evaluating the need for care, the former focus on estimating the length of time required for care was replaced by the determination of the degree of independence. Second, cognitive impairments will be acknowledged more adequately than in the past, where the focus was on physical abilities. Furthermore, the contribution to be paid by the care recipient in a nursing home will no longer be dependent on the severity of the care need.

In Germany, private LTC products used a combination of the social security definition, an ADL-based trigger and a dementia trigger until the end of 2016. Thus, the reform has repercussions for the local private insurance industry. What would happen to in-force business, how a new benefit trigger should look like, how old and new definition compare and how pricing rates can be derived were only some of the questions that had to be answered in advance.

The reform could point the way for future public schemes and private policies elsewhere. Which questions had to be answered and what issues had to be solved in advance, together with lessons learned during and shortly after the reform was undertaken, can serve as an accompaniment for the introduction or reform of public LTC schemes and for the local insurance industry in other countries.

This abstract relates to the following papers:

Groyer, A. & Campbell, R. (2019) Digital health and disability claims. British Actuarial Journal 24: e11. doi:10.1017/S1357321719000011

Woo, G. (2019) Age-dependence of the 1918 pandemic. British Actuarial Journal 24: e3. doi:10.1017/S1357321719000023

Link, S. (2019) Long term care reform in Germany – at long last. British Actuarial Journal 24: e17. doi:10.1017/S1357321719000096.

This abstract refers to the following paper: Egan, R., Cartagena, S., Mohamed, R., Gosrani, V., Grewal, J., Acharyya, M., Dee, A., Bajaj, R., Jaeger, V.-J., Katz, D., Meghen, P., Silley, M., Nasser-Probert, S., Pikinska, J., Rubin, R. & Ang, K. (2019). Cyber operational risk scenarios for insurance companies. British Actuarial Journal, 24: e6. doi:10.1017/S1357321718000284