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Robust convex risk measures

"We study the general properties of robust convex risk measures as worst-case values under uncertainty on random variables. We establish general concrete results regarding convex conjugates and sub-differentials. We refine some results for closed forms of worstcase law invariant convex risk measures under two concrete cases of uncertainty sets for random variables: based on the first two moments and Wasserstein balls."

Application of Natural Language Processing in Financial Risk Detection

This paper introduces Natural Language Processing (NLP) concepts, text mining, and model design principles, detailing text preprocessing and feature extraction. Empirical research shows the model's excellent performance in risk identification and prediction, enhancing financial risk management accuracy and efficiency.

DORA: Challenges and Some Reflections on the Adequacy of Europe’s Architecture for Financial Supervision

The paper reviews the DORA Regulation, highlighting challenges in supervisory convergence, solution centralization, and oversight fragmentation. It argues that despite DORA's positive steps for digital resilience, Europe's fragmented supervision system hampers its effectiveness. The authors suggest that a more centralized, cross-sectoral supervisory approach is needed for better regulation and supervision.

Digital Innovation and Banking Regulation

The EU aims to foster digital transformation across sectors by 2030 through legislation on AI, cloud computing, and crypto-assets. However, compared to ESG, banking regulation lacks a clear framework for managing digital risks and supervisory assessment. This paper discusses digital innovation in banking, proposing risk-based Pillar 2 prudential framework and harmonized Pillar 3 disclosures to address this gap.

Project Risk Management from the bottom‑up: Activity Risk Index

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.

Beyond probability‑impact matrices in project risk management: A quantitative methodology for risk prioritisation

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.

Artificial Intelligence (AI) Governance: An Overview

“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.”