Nos derniers articles

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.

Insurance decisions range from trivial to significant, accumulating impact over time. Intuition can mislead, especially when premiums rise due to risk. Key factors include hazard size, wealth, risk aversion, and insurer margins. Greater transparency in insurance margins can help families make informed choices, improving financial well-being and societal welfare.

This article also has links to a calculator and spreadsheet which apply the framework described herein.

The EU's Digital Services Act and Corporate Sustainability Due Diligence Directive both require large companies to implement internal risk management systems. This approach, however, strengthens corporate power by minimizing regulatory costs, reinforcing technocratic solutions, and enabling corporations to evade responsibility for negative social impacts by framing them as external risks. This procedural focus hinders effective enforcement.

Natural disasters drive insurance premium increases in affected areas for three years and cause delayed, smaller rises in unaffected areas. Insurers also adjust rejection rates, particularly in low-income regions. Financial constraints influence cost distribution, raising concerns about equity and affordability as climate risks grow and insurers adapt pricing strategies.

The insurance sector faces pressure from rising catastrophic risks, leading to higher premiums and policy non-renewals. This paper proposes an arbitrage-free method for pricing catastrophe reinsurance using the compound dynamic contagion process and Esscher transform. The findings help insurers assess liabilities amid emerging risks like climate change, cyberattacks, and pandemics.