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General Purpose AI Systems in the AI Act: Trying to Fit a Square Peg Into a Round Hole

The AI Act, initially overlooking multifunctional AI like foundation models, led to debates. Industry sought exemption, civil groups pushed for inclusion, foreseeing safety gaps and burdens on users. "General Purpose AI systems" (GPAIS) emerged in discussions, aiming to extend Act requirements to adaptable models, addressing operator responsibility. Current debate focuses on adapting the Act to cover these advanced AI, revealing its initial limitations. The paper will delve into this evolution, highlighting challenges and proposing policy adjustments for GPAIS regulation within the AI Act's framework.

Cyber Risk and Bank Fragility

"Using a novel firm-level measure of cybersecurity, we find that cybersecurity risk increases the probability of bank default. The effect is larger for banks with deposit withdrawal, but less pronounced for banks with liquidity buffer. Our results are robust to using an instrumental variable approach and to using alternative measures. "

A multistate approach to disability insurance reserving with information delays

A new model for disability insurance tackles delays in claims by evolving in real-time. Unlike traditional methods, it adjusts reserves based on immediate information. By proposing modified reserves and estimators, it addresses delays effectively, demonstrated with real data, offering practical solutions for disability insurance schemes.

Strategic Risk‑Modelling by Banks: Evidence from Inside the Black Box

Bank regulators link capital to risk, but accurately measuring risk poses challenges. Banks use internal models, impacting Value-at-Risk (VaR) predictions and their exceedance frequency. Analyzing data, we find varied VaR and violations due to simulation methods, historical data, and holding periods. Banks’ modeling choices can reduce capital requirements strategically, potentially compromising the system's stability.

Measures of Resilience to Cyber Contagion -- An Axiomatic Approach for Complex Systems

“While the main discussion of the paper is tailored to the management of systemic cyber risk in digital networks, we also draw parallels to similar risk management frameworks for other types of complex systems.”

Capital ratios and bank portfolio allocation: revisiting the 1990s "Credit Crunch" with a Bayesian discrete choice approach

The study explores the link between capital ratios and bank portfolio choices during financial strain using a unique approach. By treating portfolio adjustments as discrete decisions and comparing expected correlations to Bayesian model estimates, it identifies primary factors guiding banks' responses. Analyzing US commercial banks during the 1990s Credit Crunch, it suggests that while Basel Accord's risk-based capital requirements weren't the primary driver, banks likely responded to capital shocks, navigating constraints from leverage ratio requirements, and reacting to economic conditions.

Unravelling the Three Lines Model in Cybersecurity: A Systematic Literature Review

The Three Lines of Defence model (based on defence-in-depth approaches) has become one of the primary risk management frameworks. Yet, its application in the cybersecurity space, one of the fastest-growing areas of risk for modern organisations, has been fragmented at best. In this article, we conducted a systematic literature review on the application of this model in cybersecurity.

Principal Component Copulas for Capital Modelling

A new copula class, Principal Component Copulas, merges copula-based methods with principal component models. It excels in modeling tail dependence in multivariate data by leveraging key directions. These copulas resemble factor copulas but exhibit distinct technicalities. They offer advantages in complex dependency modeling, especially in high dimensions, as demonstrated in simulations and applied to return data. Notably, they mitigate dimensionality issues in large models and excel in assessing tail risk, crucial for capital modeling.

Optimal Reinsurance Maximising Dividends: An Infinite‑Dimensional Optimisation Approach and Numerical Results

The study designs optimal reinsurance contracts maximizing insurer dividends under budget and solvency constraints. Dynamic scenarios simplify to static problems. Tailored dividend rules add complexity, solved through infinite-dimensional Lagrangian problems. Multi-layer contracts, determined by Lagrangian multipliers, are approximated using a linear programming algorithm for practical application in reinsurance design.

Cyber Insurance and Post‑breach Services: A Normative Analysis

The study investigates how opting for cyber insurance impacts firms' risk management. It reveals that while cyber insurance often decreases proactive risk prevention (ex-ante moral hazard), it enhances post-breach mitigation efforts, improving outcomes. The key lies in contract design balancing breach coverage and co-insurance rates, emphasizing the need for a robust risk mitigation market in cybersecurity management.