This study emphasizes the need for clearer, consumer-friendly disclosures in home insurance policies regarding natural catastrophe coverage. Despite some insurers providing accurate information, vague language and inconsistent definitions in Insurance Product Information Documents (IPIDs) often confuse consumers about coverage for events like floods or fires. With only a quarter of natural disaster losses insured in Europe, unclear disclosures contribute to a significant protection gap, leaving households vulnerable. EIOPA suggests improved IPID design, including detailed peril taxonomies and clear exclusion terms, to help consumers make informed decisions.
Insurance Europe responded to EIOPA's draft Opinion on AI governance in insurance, supporting clarity on existing rules but raising concerns over potential new obligations. It cautioned that the draft's language might lead to supervisory expectations being misinterpreted as binding requirements, conflicting with the EU's simplification goals for smaller firms. Insurance Europe also highlighted risks of dual supervision in some regions and emphasized the need for clear distinctions between different AI types and user roles. It urged EIOPA to focus on aligning the Opinion with established frameworks like Solvency II and GDPR for effective oversight.
The UK regulator plans to simplify its insurance rulebook by removing outdated and duplicate requirements, aiming to reduce costs and increase market access while maintaining customer protection. Proposed changes include exempting large commercial clients from some conduct rules, reducing mandatory annual product reviews, allowing flexible lead insurer arrangements, broadening bespoke contract exclusions, and eliminating certain training requirements. These reforms aim to boost competitiveness while protecting smaller clients. The regulator seeks feedback on these proposals by July 2, 2025, as part of its ongoing effort to streamline regulations and support industry growth.
As extreme weather events intensify, insurers face limits in absorbing losses, necessitating a shift from post-event compensation to loss prevention. This requires interlinked public, public-private, and private solutions, with tough policy decisions on responsibilities and cost allocation. Insurers can leverage risk expertise, data, and technology to promote loss prevention through knowledge-sharing and financing household measures, fostering a cycle of enhanced insurability, reduced protection gaps, and business growth. While insurance law traditionally supports compensation, tailored loss prevention clauses could become standard, addressing protection gaps and creating transformative opportunities. Prevention surpasses post-event claims and uninsured losses.
Researchers proposed a new risk metric for evaluating security threats in Large Language Model (LLM) chatbots, considering system, user, and third-party risks. An empirical study using three chatbot models found that while prompt protection helps, it's not enough to prevent high-impact threats like misinformation and scams. Risk levels varied across industries and user age groups, highlighting the need for context-aware evaluation. The study contributes a structured risk assessment methodology to the field of AI security, offering a practical tool for improving LLM-powered chatbot safety and informing future research and regulatory frameworks.
The European Union’s AI Act significantly reshapes corporate governance, imposing new responsibilities on directors, compliance officers, in-house counsels, and corporate lawyers. It demands transparency, risk management, and regulatory oversight for AI systems, particularly high-risk ones. These professionals must integrate AI oversight into governance, manage liability, conduct impact assessments, and ensure cross-border compliance. With its extraterritorial reach, the Act influences non-EU entities and sets global standards for AI governance. This paper aims to offer strategic guidance on aligning corporate policies with these emerging legal requirements, emphasizing proactive risk management and ethical AI adoption.
“The European Insurance and Occupational Pensions Authority (EIOPA) has published the technical information on the symmetric adjustment of the equity capital charge for Solvency II with reference to the end of April 2025.”
This study addresses a novel risk-sharing problem where an agent maximizes expected wealth under ambiguity, penalized by a chi-squared model ambiguity. The framework generalizes monotone mean-variance preferences and accommodates multiple reference models for applications like climate risk. Explicit solutions are derived for the insurer’s optimal risk-sharing strategy, decision measure, and wealth process, which depends linearly on auxiliary processes linked to Radon-Nikodym derivatives. The model penalization parameter affects wealth variance, and the optimal strategy considers the counterparty’s model and premium. Future work could explore Lévy-Itô processes, alternative divergences, or a Stackelberg game framework.
All strategic and operational decisions should consider risk-adjusted earnings value, as all management inherently involves risk management. Effective risk management requires skilled personnel and a robust system to analyze, monitor, and manage risks, focusing on seven key areas: decision-oriented risk management, value-oriented corporate management, risk quantification (including economic, geopolitical, and sustainability risks), and risk aggregation using Monte Carlo simulations. A strong corporate strategy ensures financial sustainability and manageable earnings risks, while embedded risk management enables employees to address risks. These areas, underexplored in literature, warrant further attention, particularly risk aggregation through simulation methods.
As all transactions become digital, any involvement with EU users-even minor-triggers complex compliance risks, shifting the landscape from predictable “risk” to broader “uncertainty.” Compliance now dominates, reducing litigable individual rights and increasing disputes, but with a trend toward alternative and online dispute resolution (ADR/ODR). Traditional contract and litigation strategies are less effective, as mandatory compliance overrides forum or law choices. Future disputes will increasingly involve digital elements, requiring new approaches and cooperation between parties, especially regarding AI, data, and cybersecurity. Litigation will not decrease, but its nature will fundamentally change, demanding innovative risk management in international commercial litigation.