Nos derniers articles

" Predictive machine learning algorithms used in banking environments, especially in risk and control functions, are generally subject to regulatory and technical constraints limiting their complexity. Knowledge distillation gives the opportunity to improve the performances of simple models without burdening their application, using the results of other - generally more complex and better-performing - models."

"... we contribute both empirically and conceptually to a better understanding of the nexus of AI and regulation and the underlying normative decisions. A comparison of the scientific proposals with the proposed European AI regulation illustrates the specific approach of the regulation, its strengths and weaknesses."

"... a growing domestic emphasis from the central government on promoting innovation through weakening checks will undermine the efficacy and ethical permissibility of initiatives. Likewise, the success of AI governance initiatives will be heavily influenced by decisions made in other jurisdictions, including the European Union. If left unaddressed, these factors risk transforming the UK into a reluctant follower, rather than a global leader, in AI governance."

"We apply Weick’s (1995) sensemaking framework to examine four foundational tensions of cyber-resilience: a definitional tension, an environmental tension, an internal tension, and a regulatory tension. We then document how these tensions are embedded in cyber-resilience practices at the preparatory, response and adaptive stages. We rely on qualitative data from a sample of 58 cybersecurity professionals in the financial sector..."

"Cost-benefit analysis embodies techniques for the analysis of possible harmful outcomes when the probability of those outcomes can be quantified with reasonable confidence. But when those probabilities cannot be quantified (“deep uncertainty”), the analytic path is more difficult. The problem is especially acute when potentially catastrophic outcomes are involved, because ignoring or marginalizing them could seriously skewing the analysis. Yet the likelihood of catastrophe is often difficult or impossible to quantify because such events may be unprecedented (runaway AI or tipping points for climate change) or extremely rare (global pandemics caused by novel viruses in the modern world). OMB’s current guidance to agencies on unquantifiable risks is now almost twenty years old and in serious need of updating. It correctly points to scenario analysis as an important tool but it fails to give guidance on the development of scenarios."

"This Article is the first to examine and compare a number of recently proposed and enacted AI risk regulation regimes. It asks whether risk regulation is, in fact, the right approach."

"We document the impact of having a risk committee (RC) and a chief risk officer (CRO) on bank risk using the passage of the Dodd Frank Act as a natural experiment... Overall, we find no evidence that the RC or CRO have a causal impact on bank risk."

"The objective of this paper is to discuss the underlying principles and assumptions of valuation under Solvency II and to analyse concepts such as the best estimate and the cost-of-capital risk margin, hedgeable and non-hedgeable risks, market value of risk, as well as economic capital and expected and unexpected losses."

" A model is set up which assumes that banks’ decisions regarding capital and risk are made endogenously in a dynamic pattern."

"We conclude that the purchase of cyber insurance is indicative of an overall higher risk profile, but that having that insurance after experiencing a breach and formalizing cyber risk oversight within the audit committee reduces auditors’ perceptions of risk."