#insurers have discretion to determine #solvencyii #capitalrequirements. We find that long-term guarantees measures substantially influence the reported solvency ratios. The measures are chosen particularly by less solvent insurers and firms with high interest rate and credit spread sensitivities. Internal #models are used more frequently by large insurers and especially for #risks for which the firms have already found adequate immunization strategies.
Private sector #ai applications can lead to unfair results and loss of informational #privacy, such as increasing #insurancepremiums. Addressing this involves exploring the philosophical theory of fairness as equality of opportunity.
"We analyze #esg scores of worldwide #propertyandcasualtyinsurance during 2012-2022, and show that more sustainable #insurers have high operating leverage, although their combined ratios and z-scores reveal that they are financially stable."
"This paper presents a continuous-time dynamic model of market adoption of #cybersecurity. Individuals choose whether and when to make a precautionary investment in self-protection against the evolving security #risk of direct attack and indirect contagion. The equilibrium adoption path has a ``tipping point'': individual users will invest to get protected all at once when a critical mass of the infected has been reached."
This research studies the impact of #socialmedia on shareholder response to #esg-related #reputationalrisk.
The paper promotes better #riskmanagement and the fair allocation of #liability in #ai-related accidents.
This paper explores #digitalsovereignty in the #eu, examining two of its dimensions: #economic and #normative. Five obstacles are identified: private actors, foreign interference, a #ruleoflaw crisis, #digitalgovernance, and #digitalliteracy. The paper concludes by noting the hard balances needed in #digitalpolicy.
#machinelearning #algorithms are increasingly for #riskassessment in the #insuranceindustry, with hybrid methods often outperforming individual ones. Research has identified challenges such as tackling imbalanced datasets, selecting features, and improving interpretability. Newer methods such as #deeplearning and ensembles may further improve accuracy.
#bayesian data imputation is a technique used to fill in missing data in a variety of fields, including #riskmanagement. By employing imputation techniques to fill in the gaps, #riskmanagers can obtain a more comprehensive and reliable understanding of the underlying #risk factors, enabling them to make informed decisions and develop effective strategies for #riskmitigation.
The paper explores the potential inclusion of #climatechange #risks in the #prudential #regulatoryframework, specifically discussing adjustments to #capitalrequirements and changes to the #riskmanagement and #governance framework. The paper argues in favor of the latter but is more cautious regarding the former.