Distrust Spillover on Banks: The Impact of Financial Advisory Misconduct

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.

Discretionary Decisions in Capital Requirements under Solvency II

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#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.

Market Adoption of Cybersecurity: A Dynamic Analysis

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"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."

Digital Sovereignty in the European Union: Five Challenges from a Normative Perspective

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.

Hybrid Machine Learning Algorithms for Risk Assessment in Insurance Industry: Empirical Review

#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.