Nos derniers articles

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The UK regulator plans to simplify its insurance rulebook by removing outdated and duplicate requirements, aiming to reduce costs and increase market access while maintaining customer protection.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.

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.”

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.

The Cyber Due Diligence Object Model (CDDOM) is a structured, extensible framework designed for SMEs to manage cybersecurity due diligence in digital supply chains. Aligned with regulations like NIS2, DORA, CRA, and GDPR, CDDOM enables continuous, automated, and traceable due diligence. It integrates descriptive schemas, role-specific messaging, and decision support to facilitate supplier onboarding, risk reassessment, and regulatory compliance. Validated in real-world scenarios, CDDOM supports automation, transparency, and interoperability, translating compliance and trust signals into machine-readable formats. It fosters resilient, decision-oriented cyber governance, addressing modern cybersecurity challenges outlined in recent research.

This study introduces a novel capital allocation mechanism for banks, using game theory to assign capital requirements while enforcing macro-prudential standards. Based on competition for lower requirements, the approach employs insensitive risk measures from Chen et al. (2013) and Kromer et al. (2016), typically yielding a unique Nash allocation rule, while sensitive measures from Feinstein et al. (2017) may need additional conditions for uniqueness. The Eisenberg-Noe (2001) clearing system is analyzed for systemic risk, with numerical Nash allocations demonstrated. The study claims that further investigation into properties like continuity, monotonicity, or convexity is needed, noting that not all can hold simultaneously due to firm interactions.

FERMA supports the EIOPA and ECB's proposal for a European public-private reinsurance scheme to address the natural catastrophe protection gap. While backing the risk-based premium model and the potential for price stability, FERMA emphasizes the need for reliable and consistent data collection across nations. They also highlight the importance of a sufficiently large EU pool to manage premium pricing, a clear regulatory framework avoiding unnecessary burdens, and mechanisms to encourage long-term private sector engagement beyond annual renewals. FERMA advocates for continuous consultation and leveraging the scheme to incentivize risk prevention.

The EBA has launched an ESG dashboard to monitor climate risks across the EU/EEA banking sector using Pillar 3 disclosures. It benchmarks transition and physical risks, revealing high bank exposure (>70%) to carbon-intensive sectors, suggesting significant transition risk. Physical risk exposure is lower (<30%), but data granularity varies. Around half of real estate lending has relatively high energy efficiency, though data relies on estimates. The Green Asset Ratio (GAR) is low (~3%), reflecting the early stage of EU Taxonomy alignment. This framework supports the monitoring of climate-related financial stability risks. The dashboard uses data from December 2023 and June 2024.