Nos derniers articles

The paper presents a dual-model framework for chaotic inference and rare-event detection. Model A, using Poincaré–Mahalanobis, focuses on geometric structure for stable inference. Model B, employing Correlation–Integral with Fibonacci diagnostics, emphasizes recurrence statistics and volatility clustering. The Lorenz–Lorenz experiments show that diagnostic weighting shifts inference from stability to rare-event focus. The Lorenz–Rössler experiments demonstrate Model B’s generalization across attractors, maintaining sensitivity to volatility. The framework combines stable geometric anchoring with robust rare-event detection, advancing systemic risk analysis. Future work aims to extend the models to higher-dimensional systems, optimize computational efficiency, and apply them to finance, climate, and infrastructure.

The insurance industry in Europe is facing the immediate and growing financial impacts of climate change. It advocates for a comprehensive and collaborative approach to climate resilience, stressing the foundational importance of emissions reduction, robust prevention measures, and a proactive funding model. The industry emphasizes that effective solutions must be tailored to local contexts and require strong leadership and financial commitment from public authorities in collaboration with the private sector.

“ESG integration enhances bank stability and competitiveness, contributing to sustainable economic development.”

“The financial impact of cybercrime paints a concerning picture. According to the FBI's Internet Crime Complaint Center (IC3), cybercrime complaints in 2023 reached record highs, with reported losses exceeding $10 billion (IC3, 2023). Furthermore, IBM's 2023 Cost of a Data Breach Report estimates the average global cost of a data breach to be a staggering $4.5 million (IBM, 2023). These statistics highlight the immense financial burden cybercrime places on individuals, organizations, and governments.”

"The essay presents a vision of the AI-enhanced actuary, who leverages AI to build more accurate and efficient models, incorporates new data sources, and automates routine tasks while adhering to professional and ethical standards. We also discuss the challenges and speed-bumps along the way, including explainability, bias and discrimination risks, regulatory hurdles, and the need for actuaries to acquire AI knowledge and skills."

This research develops a mathematical model using Extreme Value Theory and Risk Measures to estimate and forecast major fire insurance claims, enhancing insurers' understanding of potential risks. Utilizing a three-parameter Generalized Pareto Distribution in the Extreme Value Theory framework, the study effectively models large losses, aiding in risk management and pricing strategies for insurance firms.

The Three Lines of Defence model (based on defence-in-depth approaches) has become one of the primary risk management frameworks. Yet, its application in the cybersecurity space, one of the fastest-growing areas of risk for modern organisations, has been fragmented at best. In this article, we conducted a systematic literature review on the application of this model in cybersecurity.