Proactive cyber-risk assessment is gaining importance due to its potential benefits in preventing cyber incidents across various sectors and addressing emerging vulnerabilities in cyber-physical systems. This study presents a robust statistical framework, using mid-quantile regression, to assess cyber vulnerabilities, rank them, and measure accuracy while dealing with partial knowledge. The model is tested with simulated and real data to support informed decision-making in operational scenarios.
“The #eu draft for an #euaiact is a legal medley. Under the banner of #risk-based #regulation, the AI Act combines two repertoires of EU law, namely #productsafety and #fundamentalrights protection. However, the proposed medley can fail if it does not account for the structural differences between the two legal repertoires…”
This paper introduces new characterizations for certain types of law-invariant star-shaped functionals, particularly those with stochastic dominance consistency. It establishes Kusuoka-type representations for these functionals, connecting them to Value-at-Risk and Expected Shortfall. The results are versatile and applicable in diverse financial, insurance, and probabilistic settings.
“Gaps in the data available for assessing cyber risk have limited the development of metrics that would help the public and private sectors prevent and recover from cyberattacks and reduce systemic risk. Cyber incident disclosure rules, introduced to close the data gaps, help but fall short in supporting the effective management of cyber risk. This article examines current and proposed reporting requirements, especially in the financial sector, where they are the most advanced.”
ESG scores and climate policy uncertainty affect default risk in ESG and non-ESG firms. The study uses various metrics and machine learning models to analyze default risk over 20 years, offering policy insights for risk management in corporations and government.
This qualitative study involving eight bank executives explored self-perceived factors affecting operational resilience and strategies for improvement. Themes that emerged included financial stability, technology, risk management, remote capabilities, effective communication, and customer engagement. These strategies aimed to enhance operational resilience in the banking industry during crises.
The paper explores the use of machine learning, particularly deep learning techniques, in insurance pricing by modeling claim frequency and severity data. It compares the performance of various models, including generalized linear models and neural networks, on insurance datasets with diverse input features. The authors use autoencoders to process categorical variables and create surrogate models for neural networks to translate insights into practical tariff tables.
The rise of generative AI and chatbots has brought Artificial General Intelligence (AGI) closer. The EU AI Act mentions general-purpose AI systems. While technical and ethical challenges in AGI are debated, organizational risk management is crucial. This paper suggests using LLCs as business entities for AGI systems to mitigate investor risks and promote AGI businesses through vertical and horizontal liability shields.
Amid growing cyber threats, research on cyber insurance risk has been limited by data constraints. This paper addresses this gap by utilizing overlooked public data from U.S. state Attorneys General, offering insights into the actual scope of cyber insurance risk. The data, derived from mandatory data breach reporting, provides valuable information for pricing, reserving, underwriting, and experience monitoring in the cyber insurance industry.
Implementing Agenda 2030 and its global Sustainable Development Goals (SDGs) requires a concerted effort from institutions and the private sector. Sustainable Finance plays a crucial role in achieving this. International directives like Sustainability Reporting are shaping the landscape, emphasizing ESG criteria. This paper compares various sustainability frameworks and highlights the importance of ESG criteria for sustainability analyses and portfolio selection. It also suggests an integrated ERM framework to align sustainability with financial decisions, enhancing coherence with SDGs and facilitating cross-framework integration.