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A Europe-wide survey by Insurance Europe and the European Youth Parliament, involving 651 young people from 33 countries, revealed that young Europeans value insurance for protection but find the purchasing process complex and paperwork-heavy. They demand simpler, more digital, and user-friendly solutions. Insurance Europe urges EU policymakers to simplify processes for young consumers.
A review of 28 studies (2019–2023) shows growing academic interest in the relationship between fintech and banking risk, using diverse models and frameworks. Research focuses on bank-level, country-level, and fintech-specific measures, analyzing risks like insolvency, credit, liquidity, and market risk. The study highlights the importance of interdisciplinary and cross-country research, recommends adopting multi-theoretical frameworks, and urges consideration of individual-level factors such as financial literacy and digital access. For policymakers, it offers guidance on monitoring fintech’s impact and stresses the need for comprehensive regulation and global cooperation to ensure financial stability and effective risk management.
This article presents modeling approaches—both structural and reduced-form—to improve the understanding and prediction of environmental risks. It enhances existing models for better risk assessment and pricing, particularly in infrastructure and land use contexts. Potential extensions include advanced temperature and rainfall modeling, such as stochastic mean-reversion and regime-switching Lévy processes. The paper also suggests future research comparing insurance pricing methods and exploring parametric insurance mechanisms, where payouts are triggered by measurable parameters rather than actual losses. These developments aim to refine environmental risk management and insurance strategies.
As extreme weather events intensify, insurers face limits in absorbing losses, necessitating a shift from post-event compensation to loss prevention. This requires interlinked public, public-private, and private solutions, with tough policy decisions on responsibilities and cost allocation. Insurers can leverage risk expertise, data, and technology to promote loss prevention through knowledge-sharing and financing household measures, fostering a cycle of enhanced insurability, reduced protection gaps, and business growth. While insurance law traditionally supports compensation, tailored loss prevention clauses could become standard, addressing protection gaps and creating transformative opportunities. Prevention surpasses post-event claims and uninsured losses.
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.
This study addresses a novel risk-sharing problem where an agent maximizes expected wealth under ambiguity, penalized by a chi-squared model ambiguity. The framework generalizes monotone mean-variance preferences and accommodates multiple reference models for applications like climate risk. Explicit solutions are derived for the insurer’s optimal risk-sharing strategy, decision measure, and wealth process, which depends linearly on auxiliary processes linked to Radon-Nikodym derivatives. The model penalization parameter affects wealth variance, and the optimal strategy considers the counterparty’s model and premium. Future work could explore Lévy-Itô processes, alternative divergences, or a Stackelberg game framework.
All strategic and operational decisions should consider risk-adjusted earnings value, as all management inherently involves risk management. Effective risk management requires skilled personnel and a robust system to analyze, monitor, and manage risks, focusing on seven key areas: decision-oriented risk management, value-oriented corporate management, risk quantification (including economic, geopolitical, and sustainability risks), and risk aggregation using Monte Carlo simulations. A strong corporate strategy ensures financial sustainability and manageable earnings risks, while embedded risk management enables employees to address risks. These areas, underexplored in literature, warrant further attention, particularly risk aggregation through simulation methods.
EIOPA's April 2025 Insurance Risk Dashboard indicates stable, medium-level risks in the European insurance sector, though pockets of vulnerability exist due to geopolitical uncertainty and market volatility. Macroeconomic risks are stable but with concerning GDP growth and inflation forecasts. Credit risks remained stable until early April, when spreads widened slightly. Market risks are elevated due to bond and equity volatility. Liquidity, solvency, profitability, financial interlinkages, and insurance risks are stable. Market sentiment is medium risk, and ESG risks are steady but with an intensifying outlook due to shifting environmental agreements.
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.