This report explores key considerations in relation to adopting a dynamic discount rate funding approach and the impacts of doing so in a range of areas, including funding volatility, investment strategy and end game objectives. It considers the advantages and disadvantages of this approach from the perspective of a range of stakeholders and the challenges that need overcoming in order to fully implement and support the approach, for example data challenges and the new skills required in the industry. The report includes sample modelling to highlight the practical issues that arise when adopting this approach. It describes a step-by-step approach for assessing the risks to be considered when determining an appropriate level of assets to provide funding for a sample set of pension scheme cash flows, as summarised in the table below.

It also considers how a dynamic discount rate approach fits within the proposed future funding regulations. Finally, the report puts forward recommendations for the IFoA, Scheme Actuaries and TPR.

Consequences of schemes adopting a dynamic discount rate approach could include very different investment strategies with investment in a wider pool of assets, less use of leveraged Liability Driven Investment, fewer schemes targeting buy-out as their end game strategy and an increase in technical work for actuaries in advising on the optimisation of asset and liability cash flows.

In the present technological age, where cyber-risk ranks alongside natural and man-made disasters and catastrophes – in terms of global economic loss – businesses and insurers alike are grappling with fundamental risk management issues concerning the quantification of cyber-risk, and the dilemma as to how best to mitigate this risk. To this end, the present research deals with data, analysis, and models with the aim of quantifying and understanding cyber-risk – often described as “holy grail” territory in the realm of cyber-insurance and IT security. Nonparametric severity models associated with cyber-related loss data – identified from several competing sources – and accompanying parametric large-loss components, are determined, and examined. Ultimately, in the context of analogous cyber-coverage, cyber-risk is quantified through various types and levels of risk adjustment for (pure-risk) increased limit factors, based on applications of actuarially founded aggregate loss models in the presence of various forms of correlation. By doing so, insight is gained into the nature and distribution of volatile severity risk, correlated aggregate loss, and associated pure-risk limit factors.

The rise in interest rates globally in 2022–23 led to improved scheme funding for many defined-benefit pension schemes. Many schemes in the UK now find themselves closer to, or at, a fully funded position on a low-risk basis (annuity buyout or self-sufficiency). Finishing the journey while managing the risk of losses on that journey is highly desirable, but may be difficult to achieve in practice.

However many schemes are not yet sufficiently funded to buy out liabilities in full with an insurer. Others may not wish to, and many who can afford to do so are not yet able to for investment reasons (such as holding illiquid assets) or operational reasons (such as the time needed to resolve member data issues). For schemes that instead look to adopt self-sufficient ongoing management with low dependency on the sponsoring employer, this may be difficult to maintain in practice. In short, there remains a risk that benefits will not be secured in full, which with hindsight could have been avoided.

The addition of capital to pension scheme assets has long been deployed to enhance the security of member benefits e.g., capital from insurers in the case of a buyout or capital from sponsors in the form of contingent assets.

More recently, providers have developed a diverse set of arrangements that draw on external capital to aid trustees and corporates to meet scheme funding ambitions. Capital Backed Funding Arrangements (“CBFA”) are in this context an additional tool in the trustee toolkit for delivering funding strategies.

This paper focusses on the UK-defined benefit market but the dynamics are applicable to other jurisdictions, with CBFAs being developed for wider markets (e.g., Ireland).

In this paper we:

• survey the current scheme funding landscape and consider the need in this environment for arrangements to support scheme funding journeys to deliver benefits in full

• summarise the key features of arrangements in the market that may support these objectives

• set out considerations for trustees and sponsoring companies when assessing these arrangements.

The aim of this paper is educational – to increase awareness of the key issues and potential solutions. Professional advice will always be required prior to any transaction. We welcome feedback from readers on further material that would be beneficial to support consideration of these arrangements.

This paper extends previous research on using quantum computers for risk management to a substantial, real-world challenge: constructing a quantum internal model for a medium-sized insurance company. Leveraging the author’s extensive experience as the former Head of Internal Model at a prominent UK insurer, we closely examine the practical bottlenecks in developing and maintaining quantum internal models. Our work seeks to determine whether a quadratic speedup, through quantum amplitude estimation can be realised for problems at an industrial scale. It also builds on previous work that explores the application of quantum computing to the problem of asset liability management in an actuarial context. Finally, we identify both the obstacles and the potential opportunities that emerge from applying quantum computing to the field of insurance risk management.