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"We find that bank capital and probability of default PD impact each other, where the total influence of the latter on the former is stronger. PD also affects capital via risk-taking but the opposite effect (i.e., from capital to PD via risk) is not identified, which challenges one of the main assumptions underlying capital regulation."
"After shortly summarising the origin, context and main characteristics of the prospective regulation, this article explores whether the ‘Brussels Effect’ will manifest in ground-breaking AI regulation, or whether the Union and its Member States run the risk of hastily adopting an incapable legal framework for a technology whose effects on society are still insufficiently understood."
"Insurance fraud has been a long-lasting issue in actuarial modeling. Policyholders are prone to hide their true status in their best interest when disclosing their information for insurance pricing purposes. However, from the insurers' point of view, it is either time-consuming or laborious to verify the true status of such risk factors. There is thus a strong incentive to build models accounting for potential misrepresentation, which contributes to a more robust ratemaking system."
"These attacks are unknown to the human eye due to malicious intent to harm any underlying infrastructure. So, to overcome the problems and make a flexible solution, we propose a framework where machine learning algorithms are applied to find relevant features from the existing dataset."
" Adopting a risk-based approach towards AI, the EU chose to understand trustworthiness of AI in terms of the acceptability of its risks. This conflation of trustworthiness with acceptability of risk invites further reflection. Based on a narrative systematic literature review on institutional trust and the use of AI in the public sector, this paper argues that the EU adopted a simplistic conceptualisation of trust and is overselling its regulatory ambition."
"... ESG, properly understood, is merely a collection of quite disparate risks that corporations face, from climate change to human capital to diversity to relations among the board, management, shareholders, and other stakeholders."
" 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."
"... our empirical evidence indicates that political risk significantly a firm’s operational risk strategy in terms of managing its customer concentration risk."
"This paper first reports on proposed and enacted transatlantic AI or algorithmic audit provisions. It then draws on the technical, legal, and sociotechnical literature to address the who, what, why, and how of algorithmic audits, contributing to the literature advancing algorithmic governance."
"Our findings show that demand is overall higher to insure separate risks than to cover all risks together in a bundled insurance policy in the UK, whereas no significant difference is found between demand for bundled insurance and single policy insurance in the Netherlands. This difference in preference across the two countries is partly associated with whether individuals have been flooded in the past, which is more often the case in the UK than the Netherlands."