Nos derniers articles

This paper explores the #uncertainty around when #data is considered "#personaldata" under #dataprotection#laws. The authors propose that by focusing on the specific #risks to #fundamentalrights that are caused by #dataprocessing, the question whether data falls under the scope of the #gdpr becomes clearer.

This paper explores the optimal #reinsurance design for an #insurer with multiple lines of business, where the dependence structure between #risks is unknown. The study considers Value-at-Risk (#var) and Range-Value-at-Risk (#rvar) as #riskmeasures and applies general premium principles. The optimal reinsurance strategies are obtained under budget constraint and expected profit constraint.

"#annuities, #longtermcareinsurance and #reversemortgages remain unpopular to manage #longevity, medical and housing price #risks after #retirement. We analyze low demand using a life-cycle model structurally estimated with a unique stated-preference survey experiment of #canadian households."

The paper discusses the risks posed by #artificialintelligence (#ai) systems, from biased lending algorithms to chatbots that spew violent #hatespeech. The author argues that policymakers have a responsibility to consider broader, longer-term #risks from #aitechnology, such as #systemicrisk and the potential for misuse. While #regulatory proposals like the #eu #aiact and the #whitehouse AI Bill of Rights focus on immediate risks, they do not fully address the need for #algorithmicpreparedness. It proposes a roadmap for algorithmic preparedness, which includes five forward-looking principles to guide the development of regulations that confront the prospect of algorithmic black swans and mitigate the harms they pose to society. This approach is particularly important for general purpose systems like #chatgpt, which can be used for a wide range of applications, including ones that may have unintended consequences. The article emphasizes the need for #governance and #regulation to ensure that #aisystems are developed and used in ways that minimize risk and maximize benefit, and it references the #nist AI #riskmanagement Framework as a potential tool for achieving this goal.

"... studies in various findings suggests a positive link between ESG and the financial performance of an organization."

"We ... estimate the quarterly evolution of expected losses (Capital at Risk) for the UK banking sector, and via Monte Carlo simulations the stochastic distribution of UK banks’ losses to study the severity and likelihood of tail-events (Conditional Capital at Risk). In the end, we provide insights on the impact of the Covid-19 pandemic on UK banking system’s loss distribution by decomposing the sources of average and tail risks."