The current banking crisis has reminded us of how risks materialising in one part of the financial system can have a widespread impact, affecting other financial markets and institutions and the broader economy. This paper, prepared on behalf of the Actuarial Profession, examines how such events have an impact on the entire financial system and explores whether such disturbances may arise within the insurance and pensions sectors as well as within banking. The paper seeks to provide an overview of a number of banking and other financial crises which have occurred in the past, illustrated by four case studies. It discusses what constitutes a systemic event and what distinguishes it from a large aggregate system wide shock. Finally, it discusses how policy-makers can respond to the risk of such systemic financial failures.

Data held within administration records of occupational pension schemes yield a rich source of information on mortality rates and the statistical predictors (covariates) of longevity. In this paper we provide, for the first time, a multivariable analysis of post-retirement mortality using the detailed information held within occupational pension scheme records.

Using the extensive dataset of over one million living pensioners and dependants and 530,000 historic deaths collected by Club Vita, we investigate the importance of factors including gender, affluence and lifestyle on the observed period life expectancy of individuals. We describe one approach to constructing a multivariable model for pensioner baseline mortality, showing how such factors explain a variation in observed period life expectancy in excess of ten years. The relative importance of each factor on mortality is analysed and we describe the interactions between these factors and age, answering questions such as whether the impact of a healthy lifestyle or affluence attenuates with age. Further, we highlight the importance of the choice of affluence measure in analysing mortality, and show that the salary at retirement is a better predictor of longevity than the pension amount for male pensioners.

The results of this paper are directly relevant to any pensions actuary advising on an appropriate baseline assumption (i.e. current mortality rates) for use with occupational pension schemes.

This abstract relates to the following paper:

BesarD., BoothP., ChanK.K., MilneA.K.L. & PicklesJ.Systemic risk in financial services ‐ Abstract of the London Discussion. British Actuarial Journal, doi:10.1017/S1357321711000110

This abstract relates to the following paper:

MadrigalA.M., MatthewsF.E., PatelD.D., GachesA.T. & BaxterS.D.What Longevity Predictors Should be Allowed for When Valuing Pension Scheme Liabilities? ‐ Abstract of the DiscussionBritish Actuarial Journal, doi:10.1017/S1357321711000018.

The focus of the paper is non-profit lifetime annuities in the UK. Annuity insurers have been faced with, or have initiated, an unprecedented amount of change during the last decade, and rapid change is still continuing. We draw out implications for the actuarial management of the business, arising from the evolution of: longevity risk assessment and management, investment strategy and operations, financial reporting, and enterprise risk management. We discuss Solvency II in some technical depth, analysing the proposed rules for technical provisions and solvency capital requirement.

This abstract relates to the following paper:

BesarD., BoothP., ChanK.K., MilneA.K.L. & PicklesJ.Systemic risk in financial services ‐ Abstract of the Edinburgh Discussion. British Actuarial Journal, doi:10.1017/S1357321711000110.

The General Insurance Board of the Faculty and Institute of Actuaries responded to some of the criticisms raised in the Morris review of the Actuarial Profession and in the press by rating agencies and others, regarding the Actuarial Profession's approach to actuarial reserving in general insurance by setting up a taskforce known as the General Insurance Reserving Issues Taskforce (GRIT). The taskforce worked from 2004 to 2006 and produced a significant report, including some new professional content and recommendations for further areas of development and research. Since then, through the GRIT successor body: the Reserving Oversight Committee (ROC), many working parties have formed and many General Insurance Research Organisation (GIRO) presentations and papers have been forthcoming. One area that has been a recurring theme through the last five years is how the Profession models and communicates the uncertainty in the claims reserving process. In the context of recent events in global financial markets, the forthcoming new regulatory framework of Solvency II, and the developments in other professions globally through IFRS and other drivers, it is timely that actuaries take stock of the many changes in our practices over the last five years and consider the direction actuaries should take for the challenges that lie ahead. This paper is a meta-study of the output of GRIT and ROC on reserving and uncertainty, with the intention of meeting these objectives.

This abstract relates to the following paper:

TelfordP.G., BrowneB.A., CollingeE.J., FulcherP., JohnsonB.E., LittleW., LuJ.L.C., NurseJ.M., SmithD.W. & ZhangF.Developments in the Management of Annuity Business ‐ Abstract of the Edinburgh Discussion. British Actuarial Journal, doi:10.1017/S1357321711000213

A major outcome of ERM activities in insurance companies has been the bringing together of all of the key risks in the company, to be managed collectively in a holistic fashion. The authors of this paper believe that an ERM framework also needs to look beyond the company, and have regard to the risk management needs of investors, from the point of view of the contribution of the insurance company to the overall risk and reward of their total investment portfolios. To meet these needs, the ERM framework needs to provide sufficient information on topics such as systematic risk, potential correlations of earnings from future new business with macroeconomic trends, other risks to franchise value, and sources of model risk within the company. The paper does not provide solutions for the issues described above; but limits itself to describing and discussing the direction for some important new initiatives in ERM activities.

This abstract relates to the following paper:

TelfordP.G., BrowneB.A., CollingeE.J., FulcherP., JohnsonB.E., LittleW., LuJ.L.C., NurseJ.M., SmithD.W. & ZhangF.Developments in the Management of Annuity Business ‐ Abstract of the London Discussion. British Actuarial Journal, doi:10.1017/S1357321711000213

This abstract relates to the following paper:

GibsonE.R., BarlowC., BruceN.A., FeliskyK.M., FisherS., HilaryN.G.J., HilderI.M., KamH., MatthewsP.N. & WinterR.A Meta-study of the General Insurance Reserving Issues Taskforce and Reserving Oversight Committee Research in this area between 2004 and 2009 ‐ Abstract of the Discussion. British Actuarial Journal, doi:10.1017/S1357321711000067.

This paper covers a number of different topics related to the measurement and modelling of dependency within economic capital models. The scope of the paper is relatively wide. We address in some detail the different approaches to modelling dependencies ranging from the more common variance-covariance matrix approach, to the consideration of the use of copulas and the more sophisticated causal models that feature feedback loops and other systems design ideas.

There are many data and model uncertainties in modelling dependency and so we have also endeavoured to cover topics such as spurious relationships and wrong-way risk to highlight some of the uncertainties involved.

With the advent of the internal model approval process under Solvency II, senior management needs to have a greater understanding of dependency methodology. We have devoted a section of this paper to a discussion of possible different ways to communicate the results of modelling to the board, senior management and other interested parties within an insurance company.

We have endeavoured throughout this paper to include as many numerical examples as possible to help in the understanding of the key points, including our discussion of model parameterisation and the communication to an insurance executive of the impact of dependency on economic capital modelling results.

The economic capital model can be seen as a combination of two key components: the marginal risk distribution of each risk and the aggregation methodology which combines these into a single aggregate distribution or capital number. This paper is concerned with the aggregation part, the methods and assumptions employed and the issues arising, and not the determination of the marginal risk distributions which is equally of importance and in many cases equally as complex.

This abstract relates to the following paper:

HitchcoxA.N., KlumpesP.J.M., McGaugheyK.W., SmithA.D. & TavernerN.H.ERM for insurance companies – adding the investor's point of view ‐ Abstract of the London Discussion. British Actuarial Journal, doi:10.1017/S1357321711000122

The text of this paper, together with the abstract of the discussion held by the Institute of Actuaries on 24 November 2008, are printed in British Actuarial Journal, 15, II.

This abstract relates to the following paper:

ShawR.A., SmithA.D. & SpivakG.S.Measurement and modelling of dependencies in economic capital ‐ Abstract of the London Discussion. British Actuarial Journal, doi: 10.1017/S1357321711000249

The Solvency II Directive mandates insurance firms to value their assets and liabilities using market consistent valuation. For many types of insurance business Economic Scenario Generators (ESGs) are the only practical way to determine the market consistent value of liabilities. The directive also allows insurance companies to use an internal model to calculate their solvency capital requirement. In particular, this includes use of ESG models. Regardless of whether an insurer chooses to use an internal model, Economic Scenario Generators will be the only practical way of valuing many life insurance contracts. Draft advice published by the Committee of European Insurance and Occupational Pensions Supervisors (CEIOPS) requires that insurance firms who intend to use an internal model to calculate their capital requirements under Solvency II need to comply with a number of tests regardless of whether the model (or data) is produced internally or is externally sourced. In particular the tests include a ‘use test’, mandating the use of the model for important decision making within the insurer. This means that Economic Scenario Generators will need to subject themselves to the governance processes and that senior managers and boards will need to understand what ESG models do and what they don't do. In general, few senior managers are keen practitioners of stochastic calculus, the building blocks of ESG models. The paper therefore seeks to explain Economic Scenario Generator models from a non-technical perspective as far as possible and to give senior management some guidance of the main issues surrounding these models from an ERM/Solvency II perspective.

Personal finance is a challenging topic which can benefit from a scientific approach to individual financial planning. This paper presents an individual asset liability management (iALM) model for life cycle planning which uses the methodology of dynamic stochastic optimisation and incorporates ideas from both classical and behavioural finance. Its implementation is in the form of a decision support tool for use by financial advisers or wealth managers. The investment universe is given by a set of indices for major asset classes and their returns are simulated forward over the lifetime of a household. On the liability side the foreseen cash flows of incomes and outgoings are simulated and punctuated by life events such as illness and death. The household's utility function is constructed for each time period over a range of monetary values in terms of household financial goals and preferences. Taxes and pension savings are treated using the tax shielded saving accounts specific to a national jurisdiction in terms of constraints in the optimisation sub-models. The paper goes on to present an analysis of iALM model recommendations for a representative UK household, together with an evaluation of the sensitivity of the financial plan generated to changes in market environments such as the 2007–9 crisis. The promise of this new technology is to bring modern decision support tools to individual investors in order to facilitate custom designed consumption, savings and investment policies.

This abstract relates to the following paper:

VarnellE.M.Economic Scenario Generators and Solvency II ‐ Abstract of the Discussion. British Actuarial Journal, doi:10.1017/S1357321711000079

Statement of Standard Accounting Practice (SSAP) 24 required, for the first time, particular levels of disclosure in relation to firms’ pension arrangements. Whilst this was a major step forward, it allowed a significant degree of discretion. This discretion meant that SSAP 24 was an observable measure of the quality and quantity of accounting disclosure for firms. This information can be used to determine the types of firms that give less information or use weaker assumptions. In my analysis, I find some evidence that large firms give more complete disclosures, but also that they are more able to exert influence on their actuaries to use weaker assumptions for the valuation of pension scheme liabilities. There is also some evidence that more profitable firms disclose less, so firms with a higher average tax rate might want to overfund their pension scheme. Finally, there is evidence that highly levered funds are less likely to give complete disclosure, and that when they do disclose their assumptions, they use a weaker basis.