The paper discusses the proposed #climatechange #disclosure rules by the #sec, which would mandate companies to provide detailed disclosures on the impact of climate change on their financial performance and policies. The authors conducted a study using hand-collected data from 99 annual reports of 34 S&P 500 companies from 2019 to 2021, finding that 91% of the #annualreports included some disclosures on climate-related risks. The study found a positive relationship between climate-related disclosures and firms’ financial performance.
This paper focuses on the development of #bayesian classification and regression tree (#cart) models for claims frequency modeling in non-life #insurance pricing. The authors propose the use of the zero-inflated #poisson distribution to address the issue of imbalanced claims data and introduce a general MCMC algorithm for posterior tree exploration. Additionally, the deviance information criterion (DIC) is used for model selection. The paper discusses the applicability of these models through simulations and real insurance data.
This paper advocates for the use of #sandbox#regulation to complement a strict #liabilityregime in regulating #artificialintelligence (#ai). The #eu#regulators have already embraced this concept.
This study focuses on the #investmentdecisions and #riskattitudes of #generationz university students in #hungary. Generation Z is looking for secure, fast, and easy #financialsolutions and services that are virtually available at any time from their #mobilephones.
The paper discusses the risks posed by #artificialintelligence (#ai) systems, from biased lending algorithms to chatbots that spew violent #hatespeech. The author argues that policymakers have a responsibility to consider broader, longer-term #risks from #aitechnology, such as #systemicrisk and the potential for misuse. While #regulatory proposals like the #eu #aiact and the #whitehouse AI Bill of Rights focus on immediate risks, they do not fully address the need for #algorithmicpreparedness. It proposes a roadmap for algorithmic preparedness, which includes five forward-looking principles to guide the development of regulations that confront the prospect of algorithmic black swans and mitigate the harms they pose to society. This approach is particularly important for general purpose systems like #chatgpt, which can be used for a wide range of applications, including ones that may have unintended consequences. The article emphasizes the need for #governance and #regulation to ensure that #aisystems are developed and used in ways that minimize risk and maximize benefit, and it references the #nist AI #riskmanagement Framework as a potential tool for achieving this goal.
This paper discusses #decentralized#insurance and its various forms of #risksharing mechanisms developed worldwide. It highlights the need for a unified #mathematical framework to describe the commonalities and relationships between different forms of #peertopeer insurance. The framework allows for a comparison of existing practices and the design of hybrid and innovative #models .
This article applies the Insurance Performance Measure (IPM) model to a set of #indian#insurance companies over the period 2005-2016, which is the first study to apply this model on real industry data. The IPM was introduced as a better way to assess industry and company performance for insurance companies as traditional #financialaccounting analysis is not suitable for the unique format of insurance company financials. IPM incorporates #underwriting, investment, and #reinsurance along with a hurdle rate and is consistent with Warren Buffett's desire for a balanced overview of industry performance. The model could help in identifying the threshold limit for overall profitability and in negotiations for reinsurance renewals.Read
This paper discusses the origins of modern #riskmanagement concepts and applications in the #financialindustry, which were developed at Bankers Trust in the 1970s. The bank's "Resources Management" group applied #probability theory to measure #marketrisk, #creditrisk, #liquidityrisk, and #operationalrisk, which were later brought together in a metric called Risk Adjusted Return On Capital (RAROC). RAROC was used to evaluate profitability, guide strategic planning, capital allocation, and incentive compensation. The article also discusses how Bankers Trust's risk management culture deteriorated after 1995, leading to its acquisition by #deutschebank Bank in 1998.
This #china Wuhan University study proposes a Financial Event Evolution Knowledge Graph (FEEKG) to identify key risk sources by event association and clarify the path of #riskevents. The FEEKG has a multi-layer structure of "entity-event-risk" and includes a subgraph of about 112,000 entities and 78,500 relationships, an event evolution subgraph, and a dynamic evolution probability subgraph of topic risk events and risk types. The study analyzes the characters and rules of entity correlation, event evolution, and #risktransmission based on FEEKG and provides a new perspective for enterprises and #financialinstitutions to find the root of risks and formulate an effective #riskmanagement decision in time.
#audit is increasingly being called upon to provide assurance on #esg#claims made by their clients, in addition to assessing the accuracy of financial numbers. The concept of #doublemateriality, which involves assessing materiality from both financial and non-financial aspects, is becoming increasingly important in audits. This paper proposes an audit approach that incorporates a “double materiality” lens of financial and ESG data to evaluate the #compliancerisk of ESG #disclosure.