A new Activity Risk Index (ARI) measures each activity's contribution to overall project risk during execution, allowing project managers to focus on high-risk activities. Unlike existing metrics, ARI is based on Schedule Risk Baseline, provides real-time insights, and offers a normalized 100% view across all activities.
“... the design of optimal parametric insurance depends on whether the parameter vector and the basis risk are independently distributed or not, and we analyze how it is affected by the attitude toward risk of the policyholder.”
The paper proposes a novel approach using Monte Carlo Simulation to quantitatively prioritize project risks based on their impact on project duration and cost, addressing limitations of traditional risk matrices and enabling project managers to differentiate critical risks according to their specific impact on time or cost objectives.
“This paper looks at global and regional efforts to come up with strategies and regulatory frameworks for AI governance. Chief amongst them include the OECD AI Principles; the EU AI Act; and the NIST AI RMF. The common thread among these frameworks or legislations is identifying and categorizing AI developments and deployments according to their risk levels and providing guidelines for ethical and trustworthy AI with considerations for human safety and innovation.”
"The risk measures contain some premium principles and shortfalls based on entropy. The shortfalls include the Gini shortfall, extended Gini shortfall, shortfall of cumulative residual entropy and shortfall of cumulative residual Tsallis entropy with order α."
“This paper discusses and analyses the regulatory approach underlying the AI Act, the main issues surrounding the proposed regulation, and the implications for the AI Act's ability to achieve its goals.”
“ Through an analysis of self-governance practices, including internal controls, ethical conduct, transparency, compliance, board oversight, risk management, auditing, and whistleblower protection, the article elucidates how organizations can effectively combat fraudulent activities.”
"Private businesses are making actuarial decisions, assessing that some locations are just too vulnerable to insure. At the same time, this insurance retreat also poses a policy challenge for states as they react to the mounting insurance gaps left by exiting private insurers."
New estimators for generalized tail distortion (GTD) risk measures are proposed, based on first-order asymptotic expansions, offering simplicity and comparable or better performance than existing methods. A reinsurance premium principle using GTD risk measure is tested on car insurance claims data, suggesting its effectiveness in embedding safety loading in pricing to counter statistical uncertainty.
Cyber risk presents significant challenges to society, yet its statistical behavior remains insufficiently understood. This paper analyzes three databases to study cyber risk dynamics. It identifies increasing frequency and severity, particularly in malicious events since 2018. Persistent heavy-tailedness across risk categories implies lower insurance demand and potentially heightened risk levels for firms.