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This paper critically assesses the proposed #euaiact regarding #riskmanagement and acceptability of #highrisk #ai systems. The Act aims to promote trustworthy AI with proportionate #regulations but its criteria, "as far as possible" (AFAP) and "state of the art," are deemed unworkable and lacking in proportionality and trustworthiness. The Parliament's proposed amendments, introducing "reasonableness" and cost-benefit analysis, are argued to be more balanced and workable.
Textual and cluster analysis of 10-K documents reveals three #riskculture classes linked to #riskstrategies, decisions, and recruitment. Firms with a strong risk culture show better #financialperformance and more diverse boards. #regulatory #supervision can help #insurers improve #risk behaviors.
The article discusses the use of #deeplearning and #datamining in business intelligence protocols to optimize data-driven decision-making and improve efficiency. The authors focus on the use of Graph Neural Network and Autoencoders Models to process large amounts of data and model #fraud behaviors. They suggest that deep learning can be used to control #moneylaundering in financial institutions and improve visibility and transparency in businesses.
#financialinstitutions are increasingly using #machinelearningalgorithms for credit risk mgmt., #fraudprevention, and #aml. This paper presents robust evidence of using logistic regression, linear discriminant analysis, and neural networks for accurately predicting and classifying financial transactions for Volcker Rule #compliance. It provides a scalable minimum viable product to automate #controls testing.
#Insurers, #reinsurers and #regulators struggle to #quantify and #manage the #financialimpact of #climatelitigation. This report provides a toolkit to help analyze the #risks, and outlines a simple climate litigation #riskmodel.
Local communities exposed to #fraudulent #investmentadvisory firms tend to withdraw deposits from their affiliated #banks, even though the banks are not involved in the #misconduct. The #reputationalrisk is more significant when banks share names with fraudulent advisory firms or are located in areas with high social norms. The author establishes causality by exploring a quasi-natural experiment in which #fraud is likely exogenously revealed.
#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."