Nos derniers articles

Insurance decisions range from trivial to significant, accumulating impact over time. Intuition can mislead, especially when premiums rise due to risk. Key factors include hazard size, wealth, risk aversion, and insurer margins. Greater transparency in insurance margins can help families make informed choices, improving financial well-being and societal welfare.

This article also has links to a calculator and spreadsheet which apply the framework described herein.

Advanced #machinelearning models were found to be more effective than #linearregression in predicting firm performance under #naturaldisaster #risks. The study suggests that textual data in #financialreports can be used to measure the perceived natural disaster risk and predict its effects on firm performance.

The article delves into #ethical concerns with #aitools in #legal and #tax research, addressing #output #quality, #bias, #verifiability, #liability, and #privacy #risks. It explores #regulatory, #tech, and professional solutions, offering practical advice for tax professionals to safely navigate AI's challenges with #riskmitigation.

The framework presents a method to quantify #uncertainty propagation in #dynamic #scenarios, focusing on discrete #stochastic processes over a limited time span. These dynamic uncertainty sets encompass various uncertainties like distributional ambiguity, utilizing tools like the Wasserstein distance and $f$-divergences. Dynamic robust #risk #measures, defined as maximum #risks within uncertainty sets, exhibit properties like convexity and coherence based on uncertainty set conditions. $f$-divergence-derived sets yield strong time-consistency, while Wasserstein distance leads to a new non-normalized time-consistency. Recursive representations of one-step conditional robust risk measures underlie strong or non-normalized time-consistency.

This study employs an agent-based #model to explore how #climate shocks spread within #supplychains, linking #climateimpacts to firms' #default #risks. Integrating supply chain and financial models, it outlines a framework to simulate physical risk transmission, downstream effects, and increased default risk. Findings underscore supply chains' role in #climaterisk propagation, advocate adaptation measures, and identify vulnerable sectors. The research underscores the necessity of climate #resilience in supply chains.

Companies use #ai tools for #hr decisions, but they face a balance between benefits and #risks. With limited federal #regulation and complex state laws, employers seek guidance. The #model#riskmanagement#mrm framework, adapted from #finance, aids in managing #airisks for #employment choices. Proportionality lets employers adjust validation to risks and tech changes. Objective analysis and a competent MRM team ensure AI tools align with design and legal requirements, fostering trust and #compliance.

In March 2023, rapid #bankruns led to the failures of #siliconvalleybank, Signature Bank, and First Republic Bank. Uninsured depositors lost confidence due to higher interest rates and their investment model. Other banks are also experiencing deposit outflows. A book by #nyustern faculty and others analyzes the situation, offering a diagnosis and policy proposals for #financialresilience, emphasizing adaptable and robust #banking policies amidst changing #risks.

#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.

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.

The paper explores the challenges of building a #safetyculture for #ai, including the lack of consensus on #risk prioritization, a lack of standardized #safety practices, and the difficulty of #culturalchange. The authors suggest a comprehensive strategy that includes identifying and addressing #risks, using #redteams, and prioritizing safety over profitability.