Nos derniers articles

Climate risk modeling provides quantitative data on potential risks at various scales. However, integrating qualitative data and local knowledge can enhance and validate these assessments.

In 1921, Keynes and Knight stressed the distinction between uncertainty and risk. While risk involves calculable probabilities, uncertainty lacks a scientific basis for probabilities. Knightian uncertainty exists when outcomes can't be assigned probabilities. This poses challenges in decision-making and regulation, especially in scenarios like AI, urging caution for eliminating worst-case scenarios due to potential high costs and missed benefits.

This paper presents a fundamental #mathematical duality linking utility transforms and #probability distortions, which are vital in #decisionmaking under #risk. It reveals that these concepts are characterized by commutation, allowing for simple axiomatization with just one property. Additionally, rank-dependent utility transforms are further characterized under monotonicity conditions.

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.

Examining #us #bank holding companies, this research analyzes how #audit committee oversight influences financial reporting quality. Leveraging Section 165 h of the Dodd–Frank Act, which mandates separate #audit and #risk committees for large bank holding firms, the study employs a difference-in-differences approach. The separation leads to enhanced reporting quality due to improved audit committee focus stemming from reduced task complexity post-Section 165 h.

This study investigates the #riskmitigation and #internalcontrols organizations implement in their Robotic Process Automation (#rpa) deployments in #accounting. RPA #governance models range from being fully centralized to being entirely decentralized. RPA #risk and #control oversight includes unique #riskassessments for the RPA accounting environment.

The paper discusses #modeling #longevity #risk, focusing on assumptions in #demographic #forecasting to project past data into the future. #stochastic forecasts are crucial to quantify #uncertainty in cohort survival predictions, including process variance and parameter/model errors.

“The origins of the discussion concerning the role of #risk in #datatransfers are difficult to trace. Despite this, #schrems II, a recent decision of the European Court of Justice (#cjeu), has given the topic new traction. This paper explores the risk-based approach (#rba) hypothesis for data transfers from a different perspective: the consequences of applying the 'two-step test' stated in Article 44 of #gdpr. The main goal is to present the challenges of applying this test and the various questions it raises.”

"There is a well-known conflict of interest between #liabilityinsurance #insurers and policyholders with respect to the decision to settle or litigate a #claim. This short note provides a simple graphical explanation for the problem and grounds it in the way the structure of the parties’ payouts drives their attitudes towards #risk. An optional appendix links the insights to the elementary mechanics of financial options.

This study addresses #climate-induced decline in #honey production, a significant #risk for #beekeepers. A #parametricinsurance policy is discussed, using #weatherdata to trigger payouts for losses due to adverse conditions. The approach is evaluated using random forests, comparing beekeepers' losses to #insurance benefits under various weather #scenarios, alongside traditional methods. An #italian case example demonstrates pricing for different regions.