Nos derniers articles

Cyberattacks primarily impact firm value through increased costs rather than sales declines, indicating financial burdens over reputational damage. Costs persist beyond the short term, and firms invest in recovery efforts. Over time, reputational concerns have diminished as cyber resilience improves. These findings emphasize the need for strong corporate risk management, focusing on cost recovery, recovery planning, and trust restoration strategies tailored to specific contexts.

A structured IT outsourcing risk management policy is crucial for navigating third-party service complexities. This study proposes a framework integrating IT outsourcing principles with COBIT standards, covering risk identification, analysis, mitigation, and ongoing monitoring. Implementing this policy enhances organizational asset protection, operational continuity, and minimizes outsourcing risks. It improves information security and business process efficiency. This framework provides practical guidance for organizations to effectively manage risks and optimize IT outsourcing value.

The banking industry faces complex financial risks, including credit, market, and operational risks, requiring a clear understanding of the aggregate cost of risk. Advanced AI models complicate transparency, increasing the need for explainable AI (XAI). Understanding risk mathematics enhances predictability, financial management, and regulatory compliance in an evolving landscape.

This study integrates cybersecurity risks into a neoclassical growth model, revealing that proactive investments enhance long-term stability, while industry-specific vulnerabilities (capital-intensive resilience vs. labor-intensive disruptions) and systemic risks affect macroeconomic resilience. Optimal resource allocation, adaptive risk strategies via Bayesian updating, and prioritizing cybersecurity in long-term planning balance security with growth.

This work presents a framework for constructing elicitable risk measures with properties like monotonicity, translation invariance, and convexity using multiplicative scoring functions. It defines necessary conditions for these properties and provides a method for developing new elicitable functionals, with applications in finance, statistics, and machine learning.

This paper examines the Solvency II correlation matrix used in Solvency Capital Requirement (SCR) calculations. It warns against misinterpreting null correlations as independence and highlights the matrix's limitations without a well-defined probabilistic model. It also critiques the flawed practice of arbitrarily increasing correlations to inflate capital requirements conservatively.

Significant risk transfer (SRT) securitization is increasingly used by major EU banks for risk and capital management. It provides flexible, reasonably priced capital, improving balance sheets and capital ratios. Supervisors assess risk transfer for capital relief. The SRT market has grown substantially and is a key tool for European banks.

The Global Cybersecurity Outlook 2025 reveals escalating cyber risks due to geopolitical tensions, technological advancements, and supply chain vulnerabilities. Over 50% of organizations cite supply chain risks as their top concern. Experts stress updating technology, redefining risk management, and fostering collaboration to address growing cybercrime, AI threats, and regulatory challenges.

This lecture explores how probability theory can quantify uncertainty, chance, and even ignorance. He demonstrates methods to measure the quality of these quantified uncertainties. He also humorously admits a miscalculation during the lecture regarding paired comparisons within the audience.

Generative AI (GAI) is transforming banking risk management, improving fraud detection by 37%, credit risk accuracy by 28%, and regulatory compliance efficiency by 42%. GAI enhances stress testing but faces challenges in privacy, explainability, and skills gaps. Its adoption, led by larger banks, demands holistic strategies for equitable industry impact.