#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.
This study explores the use of #ai #foundationmodels, specifically #chatgpt, in #auditing #esgreporting for #compliance with the #eu #taxonomy.
The findings suggest a positive association between #insurers larger exposures to #risk and higher holdings of #brownassets with higher sensitivity to #climatechange and #transition risk.
"... its ability to provide relevant #riskmitigation strategies was identified as its strongest aspect. However, the research also revealed that #chatgpt's consistency in #riskassessment and prioritization was the least effective aspect. This research serves as a foundation for future studies and developments in the field of #ai-driven #riskmanagement, advancing our theoretical understanding of the application of #aimodels like ChatGPT in #realworld #risk scenarios."
This paper discusses the potential of #ai #largelanguagemodels (#llms) in the #legal and #regulatorycompliance domain.
"This article provides an insightful overview of the challenges encountered by the #insuranceindustry when applying the requirements of #ifrs17 to #reinsurance contracts... By delving into specific challenges and offering potential solutions, the article aims to shed light on the intricacies of implementing IFRS 17 and the resulting mismatches in #financialreporting, including their impact on #solvencyii practices."
This is a note on the #gdpr and the use of #us-based #cloudservers. The note raises concerns about the #risk of US #intelligenceagencies having access to #data transferred to any US cloud from the #eu, or directly accessed by US agencies, even while still in the EU / #eea or while in transit. The note discusses cases in #france, the #netherlands, and #germany that have addressed these issues, concluding that the legality of the use of US cloud servers and solutions remains problematic.
"Approximating the #tail #risk #measure by its sample average approximation, while appealing due to its simplicity and universality in use, requires a large number of samples to be able to arrive at risk-minimizing decisions with high confidence. This is primarily due to the rarity with which the relevant tail events get observed in the samples. In simulation, Importance Sampling is among the most prominent methods for substantially reducing the sample requirement while estimating #probabilities of #rareevents."
This paper examines the impact of #databreach #disclosure laws (DBDL) on companies' voluntary #financial disclosure behaviors. The authors use a difference-in-differences analysis to show that firms have a higher propensity of disclosing non-#gaap earnings after the adoption of DBDL, suggesting that such mandatory disclosure #regulation on #cybersecurity stimulates firms' voluntary disclosure of non-GAAP earnings.