Nos derniers articles

"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.

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.

The paper summarizes a study of U.S. listed firms (2010‑2022) that examines how major cyber incidents—defined as events affecting ≥10,000 individuals or disclosed in an 8‑K—drive lasting upgrades in personnel, technology, and architecture. Findings indicate a 27% rise in cybersecurity hiring that persists for at least two years, alongside increased adoption of specialized software (+30%), cloud services (+11%), and memory‑safe languages (+50‑60%). Breached firms often surpass peers, and spillover effects occur through industry and IT‑system similarity networks, but not via geographic proximity. Cyber‑insurance coverage correlates with muted responses, suggesting potential moral hazard.

The paper argues that Shapley allocation is the most suitable risk allocation method for financial institutions, balancing theoretical properties, accuracy, and practicality. It overcomes perceived computational intractability by replacing the exponential analytical approach with an efficient Monte Carlo algorithm that scales linearly and becomes preferable for ≥10-14 units. The study proposes solutions for negative allocations, a consistent multi-level hierarchical framework (PTD, CTD, BU approaches), and demonstrates applicability to large trading portfolios under Basel 2.5 and FRTB regimes, showing Shapley better captures diversification and hedging effects compared to simpler methods.

Le G7 Cyber Expert Group analyse l’impact croissant de l’intelligence artificielle sur la cybersécurité du secteur financier. L’IA, notamment l’IA générative et les systèmes agentiques, offre des capacités avancées pour renforcer la détection des menaces, automatiser l’analyse d’anomalies, améliorer la réponse aux incidents et surveiller plus efficacement les fournisseurs et chaînes d’approvisionnement. Ces atouts peuvent accroître la résilience opérationnelle des institutions financières.

Parallèlement, l’IA génère de nouveaux risques. Les acteurs malveillants peuvent utiliser ces technologies pour créer des attaques plus sophistiquées, automatiser le développement de maliciels, produire des campagnes d’hameçonnage hautement personnalisées ou contourner des systèmes de défense. Les modèles d’IA eux-mêmes deviennent vulnérables à la manipulation des données, aux fuites d’informations ou aux attaques d’ingénierie sociale visant les systèmes automatisés.

Le rapport souligne que ces évolutions exigent une adaptation de la gouvernance, de la supervision, de la gestion des tiers et des compétences internes. Les institutions doivent intégrer la cybersécurité dans le développement et l’usage de l’IA, assurer une supervision humaine adéquate, protéger les données, renforcer la détection et la réponse aux incidents et investir dans les compétences spécialisées. Les autorités sont encouragées à actualiser leurs cadres de risque, à coopérer avec l’industrie et la recherche, et à promouvoir une IA sûre, fiable et transparente pour préserver la stabilité du système financier.

The paper applies an extended mean-field game framework to model policyholder behavior in a large mutual insurance company, where surplus/deficit is shared among members. It proves global existence and uniqueness of the Nash equilibrium, characterized by constrained MF-FBSDEs, and solves these numerically using a modified deep BSDE algorithm. Key findings include: insurance demand rises with risk aversion, loss volatility, and surplus-sharing ratio; optimal coverage decreases toward the horizon; practical no-short-selling constraints reduce wealth disparities; and pool composition affects all members’ strategies through interdependence. Extensions to survival models and decentralized insurance are proposed.

This paper explores the role of a cybersecurity engineer within existing cybersecurity workforce frameworks. It specifically compares how the NIST NICE Framework, the European Cybersecurity Skills Framework (ECSF), and the UK Cyber Security Council (UKCSC) pathways align with and diverge from the cybersecurity engineer job title. The research employs a machine learning methodology to analyze job advertisements from LinkedIn against these frameworks to identify commonalities in required Tasks, Knowledge, and Skills (TKS). The central finding suggests that while the engineer title is highly in demand, its functions are distributed across multiple work roles in these frameworks, with US-based frameworks focusing more on technical abilities and breach prevention, while UK/EU frameworks emphasize operational roles and risk assessment. Ultimately, the paper seeks to make recommendations for creating a distinct and standardized cybersecurity engineer career field to address workforce planning gaps.

This case study examines how a leading Australian financial organization operationalizes 𝗰𝘆𝗯𝗲𝗿-𝘁𝗵𝗿𝗲𝗮𝘁 𝗶𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 (𝗖𝗧𝗜), using military intelligence doctrine (the intelligence cycle) as a theoretical lens. The research, framed as a stakeholder-activity process model, reveals 𝗮 𝗳𝘂𝗻𝗱𝗮𝗺𝗲𝗻𝘁𝗮𝗹 𝗶𝗻𝘃𝗲𝗿𝘀𝗶𝗼𝗻 𝗼𝗳 𝗲𝘀𝘁𝗮𝗯𝗹𝗶𝘀𝗵𝗲𝗱 𝗶𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 𝗻𝗼𝗿𝗺𝘀.
Instead of strategic requirements driving CTI downward from leadership, 𝗶𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 𝗳𝗹𝗼𝘄𝘀 𝘂𝗽𝘄𝗮𝗿𝗱 𝗮𝗻𝗱 𝗼𝘂𝘁𝘄𝗮𝗿𝗱 from technology operations. This challenges the assumption of intelligence-led security in civilian contexts. The study finds 𝗼𝗿𝗴𝗮𝗻𝗶𝘇𝗮𝘁𝗶𝗼𝗻𝘀 𝗽𝗮𝗿𝗮𝗱𝗼𝘅𝗶𝗰𝗮𝗹𝗹𝘆 𝗹𝗶𝗺𝗶𝘁 𝗖𝗧𝗜'𝘀 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗰 𝘃𝗮𝗹𝘂𝗲 𝗱𝘂𝗲 𝘁𝗼 𝗶𝘁𝘀 𝗹𝗼𝘄 𝗼𝗿𝗴𝗮𝗻𝗶𝘇𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗽𝗼𝘀𝗶𝘁𝗶𝗼𝗻𝗶𝗻𝗴, a 𝗸𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗴𝗮𝗽 𝗯𝗲𝘁𝘄𝗲𝗲𝗻 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗮𝗻𝗱 𝗜𝗧, and a lack of strategically relevant analytical products. The findings provide an empirical explanation of CTI practice and a diagnostic model for bottom-up operationalization.