“This paper provides a comprehensive analysis of the recent EU AI Act, the regulatory framework surrounding Artificial Intelligence (AI), focusing on foundation models, open-source exemptions, remote biometric identification (RBI), copyright, high-risk classification, innovation, and the implications for fundamental rights and employment.”
“This study explores the impact of AI on auditing through a Systematic Literature Review to develop a Conceptual Framework for auditing practices.”
“… we aim to provide a summary of the evolving landscape of AI applications in finance and accounting research and project future avenues of exploration.”
“... we construct a novel factor to measure the aggregate physical climate risk in the financial market and discuss its applications, including the assessment of insurers’ exposure to climate risk and the expected capital shortfall of insurers under climate stress scenarios.”
The study delves into optimizing reinsurance amidst uncertainty, aiming to minimize insurer's worst-case loss. It establishes a connection between optimal strategies under a reference measure and those in worst-case scenarios, applicable to tail risk quantification. Conditions for common optimal solutions are provided, with applications to expectile risk measures explored. Cooperative and non-cooperative models are compared.
“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.”
"The study discusses the potential of text analysis in regulatory monitoring of financial institutions, aiming to aid in identifying unique risks of financial institutions."
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.
“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.”
“... management forecasts in response to cyber risk convey more positive information for longer horizons but exhibit lower precision and accuracy.”