29 résultats
pour « risks »
This paper discusses the role of public policy in #regulating the development of #ai, #ml, and #robotics, and the potential #risks of different approaches to #governance. It explores the tension between precautionary principles that prioritize risk avoidance and permissionless innovation that encourages entrepreneurship, and advocates for a more flexible, #bottomup governance approach that can address risks without hindering innovation.
While #financialrisks, #politicalrisks, #compliancerisks, and #cyberrisks are more easily quantifiable, #esgrisk presents a challenge for boards to identify, assess, and develop plans to its #riskmitigation. Using #nestlé USA as a case study, the article highlights how #esg#risks can migrate across different pillars: what initially appeared as #supplychainrisk moved across pillars into #litigation and #businessrisk before settling as ongoing ESG risk proper.
This paper that explores the design of #climate#stresstests to assess #macroprudential#risks from #climatechange in the #financialsector. The authors review current climate stress #scenarios employed by #regulators, highlighting the need to consider dynamic policy choices, better understand feedback loops between climate change and the economy, and explore compound #riskscenarios. They argue that more research is needed to identify channels through which plausible scenarios can impact credit risks, incorporate #bank-lending responses to #climaterisk, assess the adequacy of climate #riskpricing in #financialmarkets, and better understand the process of expectations formation around the realizations of climate risks.
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."