"… we find that the #uncertainty premium is negatively correlated with #riskaversion at all sizes and #probabilities of #risks. This leads to a selection effect: individuals who purchase #insurance are not necessarily the most risk averse. We show that the resulting #misallocation of insurance leads to large #welfare#losses."
This paper explores the #reputationalrisk associated with #esg investments and provides a formal theoretical valuation system for ESG reputation. The authors argue that ESG criteria adoption has multiple positive dimensions and outcomes, but the analysis of the #risks related to #sustainability is uncommon. They model ESG reputational risk using paradigms of #behaviouralfinance, defining it by subjective probabilities framed in a #probability function based on potential trustees' preferences. The paper highlights the need for accurate evaluation of reputational risks related to ESG investments by firms and other institutions, including #insurance companies and #pensionfunds.
This paper examines the Bowley solution in the context of #insurance contracts using the expected utility framework. Specifically, the paper analyzes a sequential game between a #policyholder and an #insurer, in which the policyholder selects the optimal #indemnity function and the insurer adjusts the pricing kernel to maximize expected #netprofit. The paper finds that the optimal safety loading factor increases with the policyholder's #riskaversion level and the #probability of zero loss. However, the paper also shows that the Bowley solution is #pareto dominated, meaning that both parties' interests can be further improved.
This commentary discusses the role of #accounting in addressing #climaterisk and promoting #sustainabilityreporting. #regulators are pushing for climate risk #disclosure standards, focusing on #non_financial and forward-looking information.
This paper discusses the role of public policy in #regulating the development of #ai, #ml, and #robotics, and the potential #risks of different approaches to #governance. It explores the tension between precautionary principles that prioritize risk avoidance and permissionless innovation that encourages entrepreneurship, and advocates for a more flexible, #bottomup governance approach that can address risks without hindering innovation.
In November 2022, new #legislation was enacted to strengthen penalties following large-scale #databreaches. However, there are concerns that current reform proposals for the #australian#privacyact do not distinguish between useful and essential changes. This #submission identifies the most important proposed changes, including expanding the definition of #personalinformation, removing exemptions for small business and strengthening #individualrights. It also advocates for the prohibition of unfair and unreasonable processing activities and for the right to opt-out of #directmarketing.
While #financialrisks, #politicalrisks, #compliancerisks, and #cyberrisks are more easily quantifiable, #esgrisk presents a challenge for boards to identify, assess, and develop plans to its #riskmitigation. Using #nestlé USA as a case study, the article highlights how #esg#risks can migrate across different pillars: what initially appeared as #supplychainrisk moved across pillars into #litigation and #businessrisk before settling as ongoing ESG risk proper.
This article discusses the need for #regulation of #robots and #ai in #europe, focusing on the issue of #civil #liability. Despite multiple attempts to harmonize #eu#tort #law, only the liability of producers for defective products has been successfully harmonized so far. The #aiact, published by the #europeancommission in 2021, aims to #regulate AI at the European level by classifying #smartrobots as "high risk systems", but does not address liability rules. This article explores liability issues related to AI and robots, particularly when using #deeplearning #machinelearning techniques that challenge the traditional liability paradigm.
This study investigates the factors affecting the #capitaladequacy of commercial #banks in #bangladesh using panel data from 28 banks over the period of 2013-2019. The study employs three analytical methods, including the Fixed Effect model, Random Effect model, and Pooled Ordinary Least Square (POLS) method, to analyze the Capital Adequacy Ratio (#car) and #tier1#capitalratio. The study finds that capital adequacy is significantly influenced by several factors, including #leverage, #liquidityrisk, #realgdp, net profit, size, and #inflation.
This study proposes a new approach to the analysis of #systemicrisk in #financialsystems, which is based on the #probability amount of exogenous shock that can be absorbed by the system before it deteriorates, rather than the size of the impact that exogenous events can exhibit. The authors use a linearized version of DebtRank to estimate the onset of financial distress, and compute localized and uniform exogenous shocks using spectral graph theory. They also extend their analysis to heterogeneous shocks using #montecarlo#simulations. The authors argue that their approach is more general and natural, and provides a standard way to express #failure#risk in financial systems.