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QFNN‑FFD: Quantum Federated Neural Network for Financial Fraud Detection

“Our findings reveal that the QFNN-FFD framework, supported by a robust computational infrastructure and optimized through sophisticated preprocessing techniques, can effectively identify fraudulent transactions with high precision. Its resilience against various quantum noise models is particularly noteworthy, indicating its suitability for real-world application in the near-term QC landscape.”

Risk exchange under infinite‑mean Pareto models

The study explores optimal decision-making for agents minimizing risks with extremely heavy-tailed, possibly dependent losses. Focused on super-Pareto distributions, including heavy-tailed Pareto, it finds non-diversification preferred with well-defined risk measures. Equilibrium analysis in risk exchange markets indicates agents with such losses avoid risk sharing. Empirical data confirms real-world heavy-tailed distributions.

Climate transition risk and the role of bank capital requirements

“Introducing carbon taxes to reduce carbon emissions from fossil energy induces risk spillovers into the banking sector. Sectoral capital requirements can effectively address risks from energy-related exposures, benefiting household welfare and indirectly facilitating capital reallocation.”

Flood Insurance Purchasing Behavior in Two Gulf Coast Communities

“We determined that vulnerable residents who are at high risk for flood hazards with low financial resiliency most need flood insurance but are least likely to own it. In addition, residents who voluntarily own flood insurance are most influenced by the cost of coverage and do not generally apply perceptions of coastal hazard risk when making decisions to purchase flood insurance.”

A Method to Categorize and Classify Artificial Intelligence applicable to the Risk‑Based Audit Approach

“… the present study developed the AI Categorization and Classification (AI-CC) Method as a central artifact to provide guidance on the use of AI within the profession. The target users of the AI-CC Method are regulators, standard setters, the strategic management of the Big Four, and individual auditors.”

Cyber Risk Management: The Impact of Data in the Assessment of Cyber Risk by Cyber Insurers

The challenge for cyber insurers lies in the scarcity of data, hindering risk assessment and product development. Organizations fear sharing information due to the risk of further attacks. Balancing transparency with discretion is crucial. With better data sharing, insurers can offer tailored products, assess risks accurately, and enhance corporate compliance.

An AI Vision for the Actuarial Profession

"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."