Nos derniers articles

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 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.

"We show that pairwise counter-monotonicity implies negative association, and it is equivalent to joint mix dependence if both are possible for the same marginal distributions. We find an intimate connection between pairwise counter-monotonicity and risk sharing problems for quantile agents."

"... we revisit the study of an optimal risk management strategy for an insurer who wants to maximize the expected utility by purchasing reinsurance and managing reinsurance counterparty risk with a default-free hedging instrument, where the reinsurance premium is calculated by the expected value principle and the price of the hedging instrument equals to the expected payoff plus a proportional loading."

"Our model yields richer separating Nash equilibria than pure moral hazard and pure adverse selection models, although separating Nash equilibria may not exist in some cases. It also retains some properties, for example, no full insurance and the positive correlation between insurance coverage and risk type, in those benchmark models. Our study on comparative statics indicates that, under some conditions and with some exceptions, the optimal indemnity and premium decrease with disutility from effort, increase with potential loss, and decrease with the initial wealth of the insured."

This article offers a #riskmanagement framework specifically designed for the #insurance and #reinsurance industries to analyze the #capitalallocation of risk, capital budgeting, and capital structure decisions.

"After reviewing the main characteristics of cyber risk, we consider the three layers of cyber space: hardware, software and psycho-cognitive layer."

"This architecture will improve board of directors’ decision-making, strengthen compliance and risk management protocols, empower gatekeepers such as lawyers and accountants to better monitor, and enhance the social contract between business and society. "

"We address the problem of sharing risk among agents with preferences modelled by a general class of comonotonic additive and law-based functionals that need not be either monotone or convex. Such functionals are called distortion riskmetrics, which include many statistical measures of risk and variability used in portfolio optimization and insurance."