"... 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.
The study proposes a method to assess #demographic #risk within the #solvencyii #regulations, using compact formulas to analyse #insurance portfolio inflows and outflows. It recommends a market-consistent valuation of liabilities for traditional and equity-linked policies. This includes evaluation of the Solvency #capitalrequirement of idiosyncratic and systematic risk, with a formula for the former and an algorithm for the latter.
This paper analyzes the constraints on the #insuranceindustry in providing larger capacity for #cyberrisk #insurance. The authors argue that cyber risk is unique in that it is both information-intensive to underwrite and heavy-tailed, leading to a tension between the need to raise large amounts of external capital to finance heavy-tailed risks and the high compensation demanded by capital providers due to information frictions.
This paper analyzes the characteristics of #cyber #loss #events and how they evolve over time. The authors use three large databases to address the problem of #report #delay and analyze the #frequency and #severity of different categories of #cyberevents . They find that the frequency of malicious cyber events has grown exponentially in the past two decades, but there is no significant change in loss severity.
This article examines the #legal and #regulatory issues, as well as #ethical and #socialjustice questions, raised by the growth of #fintech, particularly in the context of the dispute between the #occ and the New York Department of Financial Services (#nyfds) over the Office's Fintech Charter Decision.