Fat Tails and Asymmetric Time Horizons: Dealing With Systemic Climate‑Related Uncertainty

"Even pioneering forward-looking stress tests cannot feasibly capture all possible tail risks. We propose supplementing the existing capital requirements regime by giving it a stronger precautionary and macroprudential focus, paying particular attention to the prevention of environmental tipping points to avoid systemic and catastrophic impacts on the financial system and macroeconomy."

Artificial Intelligence for Sustainable Finance: Why it May Help

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"This paper reviews the use of AI in the ESG field: textual analysis to measure firms’ ESG incidents or verify the credibility of companies’ concrete commitments, satellite and sensor data to analyse companies’ environmental impact or estimate physical risk exposures, machine learning to fill missing corporate data (GHG emissions etc.)."

Mapping the Literature of Internal Auditing in Europe

" The study focused on evaluating and analysing the characteristics of literature and the themes investigated with a focus on four key aspects: governance, the effectiveness of IA, the relationship between internal auditors and other parties, and risk management to provide directions for future research."

Bank Capital, Risk‑Taking and Stability: The Relationships Assumed in Capital Regulation?

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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."

European AI Regulation: Brussels Effect versus Human Dignity?

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"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."

Multivariate Poisson Model Adjusting for Unidirectional Covariate Misrepresentation

"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."