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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.
This paper extends prior work to model an insurance company facing a future "tipping point" where catastrophe risks increase. Using viscosity solutions of a Hamilton-Jacobi-Bellman equation, the authors solve an optimal control problem to find the best dividend strategy. They show that, under fair premium adjustments and full observability, increased catastrophe risk may benefit shareholders. Numerical examples support these findings, and future research may explore relaxing model assumptions.
The World Economic Forum (WEF) and the University of Oxford’s GCSCC released the *Cyber Resilience Compass* to help organizations strengthen cyber resilience. Based on global expert input, it outlines seven key areas: leadership, governance, people and culture, business processes, technical systems, crisis management, and ecosystem engagement. It stresses that cyber resilience requires more than technical fixes; it demands aligning strategies with business goals, continuous learning, and collaboration. Tailored approaches are essential, given differing organizational risks and structures. The Compass aims to foster knowledge-sharing and build a scalable, adaptable framework for long-term, effective cyber resilience.
Integrating Cyber Security (CS) with Enterprise Architecture (EA) offers a holistic approach to managing complex cyber risks. This study, through literature review, focus groups, and interviews, identified four key integration strategies: embedding CS in EA frameworks, leveraging agile secure development, enhancing knowledge exchange, and aligning CS/EA functions. Implementing these can improve Cyber Risk Management efficiency and reliability.
Fairness in machine learning is vital, especially as AI shapes decisions across sectors. In insurance pricing, fairness involves unique challenges due to regulatory demands for transparency and restrictions on using sensitive attributes like gender or race. Traditional fairness methods may not align with these specific requirements. To address this, the authors propose a tailored approach for building fair insurance models using only privatized sensitive data. Their method ensures statistical guarantees, operates without direct access to sensitive attributes, and adapts to varying transparency needs, balancing regulatory compliance with fairness in pricing.
This paper tackles corporate fraud detection using real-world Chinese stock market data. It highlights challenges like information overload and hidden fraud. The proposed KeGCNR model enhances detection with knowledge graph embeddings and robust training. Experiments show superior performance. Future research should address class imbalance and IND noise. Public datasets are provided.
The paper explores the link between sustainability, carbon metrics, and fund performance before and after COVID-19. It finds that environmental ESG factors align closely with climate risk, while overall ESG scores show weaker correlations. Investor preferences for sustainability shift based on economic conditions, emphasizing profitability over sustainability in investment decisions.
The study examines Pareto optimal risk sharing in insurance with consumption substitution and saving in a two-period model. It confirms the robustness of classical risk-sharing results, even with recursive utility, and explores the link between consumption elasticity and saving. Precautionary savings and partial separation of risk aversion are demonstrated.
This paper introduces CATALIST, a detailed sectoral model of the Spanish economy, to assess transitional risks from climate policies like carbon pricing. It reveals varied sectoral impacts, potential financial stability risks, and growth opportunities via smart tax revenue use, offering a versatile tool for policy and scenario analysis.