This paper investigates a well-known downside protection strategy called the constant proportion portfolio insurance (CPPI) in defined contribution (DC) pension fund modeling. Under discrete time trading CPPI, an investor faces the risk of portfolio value hitting the floor which denotes the process of guaranteed portfolio values. In this paper, we question how to deal with so-called ‘gap risk’ which may appear due to uncontrollable events resulting in a sudden drop in the market. In the market model considered, the risky asset price and the labor income are assumed to be continuous-time stochastic processes, whereas trading is restricted to discrete-time. In this setting, an exotic option (namely, the ‘cushion option’) is proposed with the aim of reducing the risk that the portfolio value falls below the defined floor. We analyze the effectiveness of the proposed exotic option for a DC plan CPPI strategy through Monte Carlo simulations and sensitivity analyses with respect to the parameters reflecting different setups.

In today’s insurance market, numerous cyber insurance products provide bundled coverage for losses resulting from different cyber events, including data breaches and ransomware attacks. Every category of incident has its own specific coverage limit and deductible. Although this gives prospective cyber insurance buyers more flexibility in customizing the coverage and better manages the risk exposures of sellers, it complicates the decision-making process in determining the optimal amount of risks to retain and transfer for both parties. This article aims to build an economic foundation for these incident-specific cyber insurance products with a focus on how incident-specific indemnities should be designed for achieving Pareto optimality for both the insurance seller and the buyer. Real data on cyber incidents are used to illustrate the feasibility of this approach. Several implementation improvement methods for practicality are also discussed.

Novel methods of data collection and analysis can enhance traditional risk management practices that rely on expert engineering judgment and established safety records, specifically when key conditions are met: Analysis is linked to the decisions it is intended to support, standards and competencies remain up to date, and assurance and verification activities are performed. This article elaborates on these conditions. The reason engineers are required to perform calculations is to support decision-making. Since humans are famously weak natural statisticians, rather than ask stakeholders to implicitly assimilate data, and arrive at a decision, we can instead rely on subject matter experts to explicitly define risk management decision problems. The results of engineering calculation can then also communicate which interventions (if any) are considered to be risk-optimal. It is also proposed that the next generation of engineering standards should learn from the success of open source software development in community building. Interacting with open datasets and code can promote engagement, identification (and resolution) of errors, training and ultimately competence. Finally, the profession’s tradition of independent verification should also be applied to the complex models that will increasingly contribute to the safety of the built environment. Model assurance will be required to keep pace with model development to identify suitable use cases as adequately safe. These are considered to be increasingly important components in ensuring that methods of data-centric engineering can be safely and appropriately adopted in industry.

Written accounts suggest there were major changes in agricultural practices in Anatolia as the region switched between Roman, Byzantine, Arab and Turkic control, yet archaeological evidence of these changes is offered only on a site-by-site basis. This article presents the first synthesis of archaeobotanical, palynological and zooarchaeological evidence for changes in plant and animal husbandry in Anatolia through the first and second millennia AD. Available data indicate a minimal role of climate change in agricultural shifts but offer evidence for substantial changes towards short-term-return agricultural strategies in response to declining personal security, changing patterns of military provisioning and distinct taxation regimes.

This article discusses the EU supply chain legislation, by virtue of the recently adopted Corporate Sustainability Due Diligence Directive (CSDDD) which aims to reduce negative sustainability impacts in global supply chains with regard to a list of human rights and environmental standards specified in its Annex I of the CSDDD.

We argue that the CSDDD marks a fundamental change on the EU level, from disclosure duties to mandating prevention of, and compensation for, adverse sustainability impacts in supply chains.

We further find that the CSDDD is a legal transplant combining the principles laid down in the OECD Guidelines for Multinational Enterprises on Responsible Business and those of the UN Guiding Principles on Business and Human Rights, along with elements of French supply chain legislation from 2017 (which relies on a private enforcement model) and the German supply chain law from 2021 (which is based on a public enforcement model). Like all legal transplants, the resulting legal text generally prompts questions about consistency and specifically raises doubts as to whether combining all of the components of a private and a public enforcement model is proportionate for the purpose of the CSDDD which is to ensure that companies take effective steps to counter violations of human rights and environmental standards in global supply chains. The scope provisions (including smaller in-scope EU firms while leaving non-EU peers of a similar size aside) paired with significant high compliance burden provide grounds to argue that the CSDDD impacts on the competitiveness of these smaller in-scope EU companies, and thus the EU economy at large.

Multiple instances of safeguarding failures and criticisms of poor process and weak governance have afflicted the Church of England for many years, despite repeated assurances that ‘Lessons would be learned’. An Independent Safeguarding Board has been formed and then abolished without being replaced. A report by Professor Alexis Jay, former Chair of Independent Inquiry into Child Sexual Abuse, recommending the creation of two independent charities to oversee Church safeguarding has been passed to a Response Group and is being resisted by various groups within the Church. This article examines issues of the management of safeguarding within the overall governance of the organisation, compares issues within the Church with those which have been exposed by the Post Office Horizon scandal and considers the potential role of the audit function to concern itself with safeguarding matters as part of its oversight of risk management and corporate governance.

The growing concern over cyber risk has become a pivotal issue in the business world. Firms can mitigate this risk through two primary strategies: investing in cybersecurity practices and purchasing cyber insurance. Cybersecurity investments reduce the compromise probability, while cyber insurance transfers potential losses to insurers. This study employs a network model for the spread of infection among interconnected firms and investigates how each firm’s decisions impact each other. We analyze a non-cooperative game in which each firm aims to optimize its objective function through choices of cybersecurity level and insurance coverage ratio. We find that each firm’s cybersecurity investment and insurance purchase are strategic complements. Within this game, we derive sufficient conditions for the existence and uniqueness of Nash equilibrium and demonstrate its inefficiency. These theoretical results form the foundation for our numerical studies, allowing us compute firms’ equilibrium decisions on cybersecurity investments and insurance purchases across various network structures. The numerical results shed light on the impact of network structure on equilibrium decisions and explore how varying insurance premiums influence firms’ cybersecurity investments.

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.

A reflective analysis is presented on the potential added value that actuarial science can contribute to the field of health technology assessment. This topic is discussed based on the experience of several experts in health actuarial science and health economics. Different points are addressed, such as the role of actuarial science in health, actuarial judgment, data inputs and their quality, modeling methodologies and the use of decision-analytic models in the age of artificial intelligence, and the development of innovative pricing and payment models.