Integrated crop-livestock systems (ICLS) are currently promoted agricultural production systems that aim to use better resources through production integration and intensification. While this system reduces some risks, it adds complexity and new risks to businesses due to interdependence between the agricultural modules. To deal with these issues, integrated risk management is required to reduce the effects of risks and to take advantage of the opportunities of an ICLS. Generically, enterprise risk management (ERM) meets this need by proposing comprehensive and coherent risk management, instead of managing agricultural module risks individually. However, there is a need to customize the ERM approach to ICLS. Therefore, the current study aims to develop a method to manage risks for ICLS based on ERM, integrating the management of risks and aligning risk management with the strategic objectives. A literature review, a pilot study, interviews with experts, four case studies and 20 practitioners supported the method development and evaluation through three versions. As a result, the method identifies and relates risks through process mapping with a qualitative and quantitative analysis of their impacts, determines risk responses based on willingness to take risks, and helps identify processes to control, communicate and monitor the risks. The method also stimulates the implementation of ICLS in market-oriented farms, providing an approach to increase the chances of ICLS success. The main difference from previous research lies in the integrative management of multiple risks, the alignment of risks with strategy and the consideration that a risk might be considered an opportunity.

We demonstrate both analytically and numerically that the existing methods for measuring tail dependence in copulas may sometimes underestimate the extent of extreme co-movements of dependent risks and, therefore, may not always comply with the new paradigm of prudent risk management. This phenomenon holds in the context of both symmetric and asymmetric copulas with and without singularities. As a remedy, we introduce a notion of paths of maximal (tail) dependence and utilize the notion to propose several new indices of tail dependence. The suggested new indices are conservative, conform with the basic concepts of modern quantitative risk management, and are capable of differentiating between distinct risky positions in situations when the existing indices fail to do so.

The UK Pension Protection Fund (PPF) was established in April 2005 to protect the pensions of members of UK private sector defined benefit pension schemes which have insufficient assets and whose corporate sponsor fails. The Fund takes over the pension scheme assets and assumes responsibility for the payment of compensation to the former members of the scheme. The PPF is funded by a levy on the population of eligible schemes. This paper discusses the application of Enterprise Risk Management principles and techniques to the unique situation of the PPF. The elements of the financial management of the Fund have been developed by reference to practice within proprietary insurance institutions and within pension funds. The paper will be of interest and, we hope, of some value to students, researchers and analysts and also to the PPF's own stakeholder groups that have a stake in an effective pension protection regime.

This paper explores the application of ERM-style techniques to pension funds. It uses the term ‘entity-wide risk management’ rather than ‘enterprise risk management’, even though both have the same acronym (‘ERM’), because many pension funds do not view themselves as business ‘enterprises’ as such. Some of the techniques that business enterprises have for managing risk (e.g. raising new capital from shareholders or branching into new business areas if existing ones have unattractive risk-reward characteristics) may not be open to many pension funds. The paper argues that the holistic approach to risk management (and governance) that is a hallmark of ERM is as appropriate to pension funds as it is to any other type of entity. This is the case whether the fund is defined benefit or defined contribution in nature, or a hybrid. It is also the case whether the ‘entity’ is deemed to be the fund itself, the sponsor or the two combined. Indeed, there are aspects of pension arrangements, such as the relationship between the fund and its sponsor, that lend added impetus to the use of ERM-style techniques in practical pension fund management.

This paper focuses on Enterprise Risk Management (ERM) and strategic business management for health insurance companies in our world of ‘unknown unknowns’ and the emergence of unexpected risks over time. It illustrates how Chief Risk Officers (CROs) can focus on ‘risk and opportunity management’ through an ERM framework, and thereby balance risks against opportunities, whilst being resilient against ‘unknown unknowns’ and their emergence over time as ‘known unknowns’ and ‘known knowns’. The paper has been designed to meet the broad requirements of health insurers that would like to implement an ERM framework for the effective risk management of their health insurance lines of business. Risk management for health insurers in the context of Solvency II and broader European Commission regulatory requirements is also discussed. The authors discuss how insurers can develop and apply risk management to build resilience in the face of the storms and shocks that may lie ahead.

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.

The paper overviews the application of existing actuarial techniques to operational risk. It considers how, working in conjunction with other experts, actuaries can develop a new framework to monitor/review, establish context, identify, understand and decide what to do in terms of the management and mitigation of operational risk. It suggests categorisations of risk to help analyses and proposes how new risk indicators may be needed, in conjunction with more normal quantification approaches.

Using a case study, it explores the application of stress and scenario testing, statistical curve fitting (including the application of extreme value theory), causal (Bayesian) modelling and the extension of dynamic financial analysis to include operational risk. It suggests there is no one correct approach and that the choice of parameters and modelling assumptions is critical. It lists a number of other techniques for future consideration.

There is a section about how ‘soft issues’ including dominance risk, the impact of belief systems and culture, the focus of performance management systems and the psychology of organisations affect operational risk. An approach to rating the people aspects of risk in parallel with quantification may help give a better overall assessment of risk and improve the understanding for capital implications.

The paper concludes with a brief review of implications for reporting and considers what future work will help develop the actuarial contribution. It is hoped the paper will sow seeds for the development of best practice in dealing with operational risk and increase the interest of actuaries in this emerging new topic.

This presidential address looks at the current state of affairs, the opportunities and threats to our traditional areas of interest and the importance of developing in wider fields. It pays tribute to all the volunteers who help make it the organisation that it is whilst highlighting the need for all Fellows and students to be engaged with its future.

The authors have reviewed over 60 texts on the subject of Enterprise Risk Management (ERM). In this paper they set out a summary of ERM based on three of those sources, selected for their relevance and breadth of view. The paper observes that the approaches described vary widely in nature. A separate ‘on-line” source is provided, which summarises key readings from the 60 texts. Combining findings from these texts with the authors' own experiences, the paper suggests some best practice checklists, designed to enable organisations to take stock of their current ERM frameworks. It discusses other aspects of ERM for practitioners, including extreme events, opportunity management and the link with corporate strategy. The paper looks at immediate and longer-term implications for actuaries in the United Kingdom, and then poses questions about future professional development and education. It suggests an emerging role for the ‘ERM actuary’, and, finally, it suggests future work to progress the development of ERM and the actuaries' role.

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.