"... the new Climate Risk Division will integrate climate risks into its supervision of regulated entities, support the industry’s growth in managing climate risks, coordinate with international, national, and state regulators, develop internal capacity on climate-related financial risks, support the capacity-building of peer regulators on climate-related supervision, and ensure fair access to financial services for all communities, especially those most impacted by climate change. "
This paper presents an extension of #statistical inference for smoothed quantile estimators from finite domains to infinite domains. A new truncation methodology is proposed for discrete loss distributions with infinite domains. #simulation studies using several distributions commonly used in the #insuranceindustry show the effectiveness of the methodology. The authors also propose a flexible bootstrap-based approach and demonstrate its use in computing the conditional five number summary (C5NS) for tail risk and constructing confidence intervals for each of the five quantiles that make up C5NS. Results using #automobile #accident #data show that the smoothed quantile approach produces more accurate classifications of tail #risk and lower coefficients of variation in the estimation of tail #probabilities compared to the linear interpolation approach.
"This paper examines the major causes of #svbcollapse collapse in March 2023 from a #regulatory and #riskmanagement perspective... Our analysis reveals major weaknesses in SVB’s risk management practice but also underlines weaknesses in the US regulatory regime [compared to #baseliii] reaching from reporting exemptions for small banks in the domain of liquidity and interest rate risks, non-sufficiently sensitive monitoring ratios, and misalignments between #accounting and risk management principles hindering effective oversight."
This paper discusses the limitations of traditional #asset#liability#management (#alm) techniques in #riskmanagement, particularly in high-interest rate environments, and proposes the application of #deep#reinforcement#learning (#drl) to overcome these limitations. The paper defines the components of #reinforcementlearning (#rl) that can be optimized for ALM, including the RL Agent, Environment, Actions, States, and Reward Functions. The study shows that implementing DRL provides a superior approach compared to traditional ALM, as it allows for increased #automation, flexibility, and multi-objective #optimization in ALM.
"… 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.