The report outlines how digitalization and technological innovation introduce significant operational and digital risks to global financial stability. Key vulnerabilities include the expansion of Artificial Intelligence (AI), which complicates governance and monitoring while increasing systemic correlations. Furthermore, the report highlights risks from third-party dependencies, particularly cloud concentration among a few providers, which could amplify crises. Operational resilience is also a primary concern; outages at critical nodes or cyber incidents are viewed as direct threats. Consequently, the FSB is prioritizing standardized incident reporting and public-private collaboration to mitigate these emerging threats by 2026.
This report assesses how the Minimum Requirement for own funds and Eligible Liabilities (MREL) has influenced the EU banking sector between 2022 and 2024. The document examines the regulatory impact on financial markets, bank profitability, and the evolution of funding structures following the full implementation of BRRD II. It highlights that while most institutions met their final targets by the 2024 deadline, smaller banks still face structural hurdles in accessing wholesale funding markets. Data indicates a significant shift toward senior non-preferred (SNP) debt as a primary tool for meeting subordination requirements. Ultimately, the report concludes that while compliance costs are higher for retail-oriented firms, MREL has successfully strengthened loss-absorbing capacities without destabilizing bank business models.
The article reports that the European Insurance and Occupational Pensions Authority and the EU Agency for the Space Programme present a joint white paper examining the use of Copernicus Earth observation data for supervising extreme weather risks. It describes a pilot project suggesting satellite data can provide near real-time, independent insights to improve risk assessment, loss estimation, and stress testing in the insurance sector. The paper argues such data can enhance identification of affected areas, support micro- and macro-level analysis, and strengthen model validation, contributing to more effective management of climate-related disasters.
The Q4 2025 EBA Risk Dashboard summarizes the European banking sector’s condition using a "traffic light" Risk Indicator heatmap. The report describes a period of high liquidity, noting that no sampled assets fell into the highest risk category for Liquidity Coverage Ratios. While solvency remains strong, with 79% of assets in the top Tier 1 capital bracket, this reflects a slight decrease from 2024. Profitability remains a concentrated risk, as nearly half of assets show high cost-to-income ratios. Overall sector stability is monitored through asset-weighted indicators and a composite Risk Assessment meter.
This research presents a machine learning framework designed to predict and reduce the risk of identity theft caused by phishing and social engineering. The authors developed a Cyber Risk Score (CRS) that combines observable security habits, like password hygiene, with latent psychological traits such as impulsive link-clicking. By utilizing a hybrid stacking ensemble model, the study achieved a 93% accuracy rate in identifying vulnerable social media users. Beyond mere prediction, the system uses SHAP analysis to provide transparent, personalized recommendations tailored to an individual’s specific behavioral weaknesses. This user-centered approach aims to bridge the gap between cybersecurity knowledge and actual online behavior through evidence-based interventions. Ultimately, the framework offers a scalable, ethical solution for organizations to protect users in increasingly sophisticated digital environments.
This paper investigates dynamic insurance pricing and risk management when insurers face correlation ambiguity between underwriting and financial investment risks. By employing a robust control framework and G-expectation theory, the research models how insurers make decisions under worst-case beliefs regarding these unknown dependencies. The authors identify five distinct equilibrium regimes, such as pure underwriting or zero underwriting, which shift based on market conditions and ambiguity levels. A key finding challenges traditional assumptions by showing that uncertainty does not always lead to higher premiums or reduced utility for the insurer. Instead, ambiguity aversion can sometimes improve an insurer’s position by encouraging more conservative and robust portfolio allocations. Ultimately, the study highlights that accurately understanding risk dependence is essential for effective regulatory policy and equilibrium pricing in modern financial markets.
This paper analyzes the shift in European digital regulation from a science-based model to one rooted in constitutional values. While traditional risk management relied on the precautionary principle and quantifiable data, modern frameworks like the GDPR, DSA, and AI Act focus on safeguarding fundamental rights and democracy. The authors argue that this transformation addresses the intangible nature of digital harms and the significant imbalance of power between public regulators and private tech firms. By delegating risk assessment to private entities, the EU utilizes accountability and proportionality as tools to govern technological uncertainty. Ultimately, the text illustrates how legal and ethical standards have replaced empirical science as the primary metrics for regulating the digital ecosystem.
This paper provides a rigorous mathematical analysis of the axiomatic foundations used to quantify financial risk. The author traces the evolution of risk measurement from early standards like Value-at-Risk to more sophisticated frameworks including coherent, convex, and spectral risk measures. Central to the text are the representation theorems that define these measures through dual sets of probability scenarios and penalty functions. The scope extends to dynamic settings, where time-consistency is required for multi-period assessments, and systemic risk involving interconnected institutions. Finally, the research bridges the gap between theory and practice by integrating machine learning techniques, specifically examining the concentration of empirical estimators and the use of conformal prediction for distribution-free risk control.
This position paper emphasizes the insurance industry's role as a strategic asset for the continent's economic stability and long-term growth. The organization argues that over-regulation and complex, overlapping legal frameworks currently hinder the sector's ability to invest in European priorities like green technology and infrastructure. To address this, they propose a simplification package and a “Financial Services Omnibus” aimed at reducing administrative burdens and stopping unnecessary new rules. By streamlining requirements for reporting and capital, the industry believes it can better support household savings and enhance the global competitiveness of the Single Market. Ultimately, this paper serves as a formal call for EU leaders to prioritize regulatory efficiency to ensure that insurance providers can continue to anchor Europe’s financial resilience.
This paper by Caroline Hillairet, Olivier Lopez and Lionel Sopgoui (CREST, UMR CNRS) describes a stochastic SIR model designed to quantify the financial impact of contagious cyber-attacks on corporate revenues and insurance portfolios. By blending epidemiological frameworks with economic granular growth models, the researchers account for the reality that larger firms are more frequent targets and exhibit different internal infection dynamics. The model specifically utilizes Cox-Ingersoll-Ross (CIR) processes to incorporate environmental variability, allowing for more realistic simulations of how ransomware spreads within and between organizations. A key practical application analyzes the 2024 LockBit ransomware attacks, offering insurers a method to calculate Aggregate Exceedance Probabilities to forecast potential losses. Ultimately, the framework bridges the gap between cybersecurity technicalities and financial risk management, providing a tool for measuring systemic cyber threats across diverse industrial sectors.