The 𝗘𝗕𝗔 announces updated guidance for banks concerning 𝗲𝗻𝗵𝗮𝗻𝗰𝗲𝗱 𝗿𝗲𝗽𝗼𝗿𝘁𝗶𝗻𝗴 𝗿𝗲𝗾𝘂𝗶𝗿𝗲𝗺𝗲𝗻𝘁𝘀 𝗳𝗼𝗿 𝗼𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗿𝗶𝘀𝗸. This guidance follows a postponement of the mandatory application date for new reporting obligations, now shifted from March 2026 to the 𝗲𝗻𝗱 𝗼𝗳 𝗝𝘂𝗻𝗲 𝟮𝟬𝟮𝟲 by the European Commission's Regulation (EU) 2025/2475. The EBA specifies that institutions must use the 𝗖𝗢𝗥𝗘𝗣 𝗢𝗙 𝗺𝗼𝗱𝘂𝗹𝗲 (𝗿𝗲𝗹𝗲𝗮𝘀𝗲 𝟰.𝟮) 𝗮𝗻𝗱 𝗰𝗹𝗮𝗿𝗶𝗳𝗶𝗲𝘀 𝘄𝗵𝗶𝗰𝗵 𝘀𝗽𝗲𝗰𝗶𝗳𝗶𝗰 𝗿𝗲𝗽𝗼𝗿𝘁𝗶𝗻𝗴 𝘁𝗲𝗺𝗽𝗹𝗮𝘁𝗲𝘀, 𝗖 𝟭𝟲.𝟬𝟮, 𝗖 𝟭𝟲.𝟬𝟯, 𝗮𝗻𝗱 𝗖 𝟭𝟲.𝟬𝟰, 𝗮𝗿𝗲 𝗻𝗼 𝗹𝗼𝗻𝗴𝗲𝗿 𝗿𝗲𝗾𝘂𝗶𝗿𝗲𝗱 𝗳𝗼𝗿 𝘁𝗵𝗲 𝗠𝗮𝗿𝗰𝗵 𝗿𝗲𝗳𝗲𝗿𝗲𝗻𝗰𝗲 𝗱𝗮𝘁𝗲 𝗯𝘂𝘁 𝘄𝗶𝗹𝗹 𝗯𝗲 𝗺𝗮𝗻𝗱𝗮𝘁𝗼𝗿𝘆 𝗶𝗻 𝗝𝘂𝗻𝗲 𝟮𝟬𝟮𝟲. This announcement also mentions the availability of updated technical instructions and IT solutions to help banks implement the revised operational risk reporting framework smoothly. Finally, this information is framed within the EBA's broader roles, which include developing harmonized rules, promoting supervisory convergence, and providing risk and data analysis for the European financial system.
"The three European Supervisory Authorities (EBA, EIOPA and ESMA – ESAs) published two factsheets designed to help consumers protect themselves from crypto and other online frauds and scams and explain how fraudsters increasingly use artificial intelligence (AI) to deceive consumers. To make the information easily accessible, 𝘁𝗵𝗲 𝗳𝗮𝗰𝘁𝘀𝗵𝗲𝗲𝘁𝘀 𝘄𝗶𝗹𝗹 𝗯𝗲 𝘁𝗿𝗮𝗻𝘀𝗹𝗮𝘁𝗲𝗱 𝗶𝗻𝘁𝗼 𝗮𝗹𝗹 𝗼𝗳𝗳𝗶𝗰𝗶𝗮𝗹 𝗘𝗨 𝗹𝗮𝗻𝗴𝘂𝗮𝗴𝗲𝘀 𝗮𝗻𝗱 𝗿𝗲𝗽𝗿𝗼𝗱𝘂𝗰𝗲𝗱 𝗯𝘆 𝗻𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗮𝘂𝘁𝗵𝗼𝗿𝗶𝘁𝗶𝗲𝘀."
EIOPA’s December 2025 Financial Stability Report outlines several risks facing European insurers and pension funds, including growing exposures to private credit, vulnerabilities from a weakening U.S. dollar, and the impact of global market interconnectedness. It describes private credit’s expansion, associated liquidity, valuation and concentration risks, and insurers’ sizable U.S. dollar-denominated holdings with complex hedging needs. The report also notes interconnected international exposures that could elevate market and currency risks, alongside other topics like cyber threats and AI-related systemic vulnerabilities, while acknowledging resilient capital and funding ratios amid economic uncertainty.
France Assureurs publie la 9ᵉ édition de son étude annuelle “Assurance et finance durable”, présentant les données clés du secteur de l’assurance à fin 2024 dans une perspective ESG (environnementale, sociale, gouvernance) à l’occasion du 10ᵉ anniversaire de la COP 21 et de l’Accord de Paris. Le rapport dresse un état des politiques d’investissement responsable des assureurs, incluant objectifs de neutralité carbone à 2050, analyse de l’impact sur la biodiversité, niveaux d’investissements verts et exposition aux énergies fossiles, ainsi que l’intégration de critères durables dans les produits d’assurance et l’accompagnement des épargnants.
Europe is facing an unprecedented surge in cyber threats. Malware targeting banking apps alone has grown 200% year-on-year, with affected applications tripling from 600 to 1,800. These numbers reflect a simple truth: cybersecurity is no longer just a tech challenge—it’s a talent challenge.
Despite growing investments, Europe’s cybersecurity skills gap continues to widen, leaving our digital ecosystem exposed. Today, this shortage of skilled professionals is arguably our single greatest vulnerability.
To close this gap, ENISA introduced the European Cybersecurity Skills Framework (ECSF)—a much-needed step toward a common skills language across Member States. Its ambition is right. Its mission is essential. But its practical impact remains limited.
A recent structural analysis highlights six critical gaps holding the ECSF back:
🔹 No seniority levels, making career pathways unclear
🔹 Weak links between tasks, skills, and knowledge, complicating curriculum design
🔹 No graded proficiency levels, limiting meaningful assessment
🔹 Inconsistent role definitions, misaligned with real-world job functions
🔹 Flat, unstructured knowledge lists, difficult to reuse or map
🔹 Lack of scalable coding, hindering interoperability with frameworks like NICE, SFIA, and CyBOK
The good news? These issues are solvable.
A smarter, next-generation ECSF could be built by:
1️⃣ Introducing hierarchical categories for tasks, skills, and knowledge
2️⃣ Defining explicit links between them
3️⃣ Integrating competence tiers
4️⃣ Adding junior–mid–senior levels
5️⃣ Creating a modular structure for emerging domains
6️⃣ Mapping skills directly to training and certifications
This is more than framework design—it’s a strategic investment in Europe’s digital sovereignty. A coherent ECSF empowers educators, enables precise hiring, enhances mobility across Member States, and builds the coordinated workforce we urgently need.
This annual report analyzes how cybersecurity policy translates into practical actions, investments, and operational changes within organizations across the EU, particularly those in high-criticality sectors under the NIS2 Directive. The findings, based on a survey of over 1,000 professionals, highlight that while regulatory compliance is the main driver of investment, challenges persist, such as the cyber talent crunch and difficulties with fundamental tasks like patching and security assessments. Key insights from the report show a shift in spending toward technology and outsourcing, and an ongoing concern over ransomware and supply-chain attacks. This ENISA study ultimately aims to inform policymakers by revealing the practical obstacles and shifting priorities faced by entities working to enhance their cyber resilience.
This paper explores the relationship between Artificial Intelligence (AI) and cybersecurity, emphasizing AI's critical role in modern digital defense. The abstract and introduction establish the urgent need for advanced security solutions due to the increasing reliance on digital platforms and the rise of cyber threats. The research specifically examines how AI technologies like machine learning and deep learning enhance threat detection and incident response for organizations. Conversely, the document addresses significant risks associated with AI in security, including algorithmic bias, adversarial attacks, and the threat of deepfake technologies. Finally, the conclusion argues that AI's benefits outweigh its drawbacks when implemented with robust mitigation strategies, such as quantum security and human oversight, ensuring ethical and effective use.
This paper summarizes the use of Extreme Value Theory (EVT) for modeling large insurance claims, particularly within reinsurance, where managing tail risk is paramount.
The core argument is that standard EVT must be adapted to overcome unique actuarial data challenges, including censoring (due to limits/delays), truncation (due to maximum possible losses), and data scarcity.
Key adaptations discussed include:
Truncation and Tempering Models to account for limits or weakening tail behavior.
Censoring-Adapted Estimators (e.g., modified Hill) for incomplete data.
Splicing/Composite Models that combine body and tail distributions (e.g., Mixed Erlang/Generalized Pareto) for a full-range fit.
Advanced Regression and Multivariate Models to incorporate covariates (like climate change effects) and analyze spatial dependencies.
A profound, tailored application of EVT is deemed critical for sound pricing and risk management of catastrophic risks.
Le baromètre 2025 met en évidence une prise de conscience généralisée du risque géopolitique, désormais perçu comme un facteur de rupture majeur pour les entreprises. Si son intégration dans la gouvernance et les cartographies progresse, les moyens dédiés restent limités : budgets faibles, absence de ressources spécialisées et formations rares. Le pilotage demeure fragmenté et souvent réactif, malgré une reconnaissance de l’interdépendance croissante entre tensions internationales, chaînes de valeur et risques opérationnels. Les organisations identifient comme menaces principales les conflits potentiels impliquant les grandes puissances et appellent à une évolution vers une culture d’anticipation structurée et transversale.
This paper addresses the difficulty of 𝗶𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗻𝗴 𝗰𝗼𝗺𝗽𝗹𝗲𝘅, 𝗵𝗶𝗴𝗵-𝗱𝗶𝗺𝗲𝗻𝘀𝗶𝗼𝗻𝗮𝗹 𝘀𝗽𝗮𝘁𝗶𝗮𝗹 𝗱𝗮𝘁𝗮, 𝘀𝘂𝗰𝗵 𝗮𝘀 𝗰𝗹𝗶𝗺𝗮𝘁𝗲 𝗮𝗻𝗱 𝘀𝗮𝘁𝗲𝗹𝗹𝗶𝘁𝗲 𝗶𝗺𝗮𝗴𝗲𝗿𝘆, 𝗶𝗻𝘁𝗼 𝗽𝗿𝗲𝗱𝗶𝗰𝘁𝗶𝘃𝗲 𝗺𝗼𝗱𝗲𝗹𝘀 𝗳𝗼𝗿 𝗶𝗻𝘀𝘂𝗿𝗮𝗻𝗰𝗲.
The study proposes a novel multi-view contrastive learning framework designed to generate low-dimensional spatial embeddings. This method aligns data from multiple sources (e.g., satellite imagery and OpenStreetMap features) with coordinate-based encodings.
The resulting embeddings are shown to consistently improve predictive accuracy in risk models, demonstrated through a case study on French real estate prices. The paper highlights that the embeddings capture spatial structure, enhance model interpretability, and exhibit transferability to unobserved regions.