154 résultats pour « riskmanagement »

Application of Deep Reinforcement Learning in Asset Liability Management

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This paper introduces the application of Deep Reinforcement Learning (#drl) in #alm, addressing limitations of traditional methods reliant on human judgement. The findings highlight the potential of DRL to enhance #riskmanagement outcomes for #insurers, #banks, #pensionfunds, and #assetmanagers, providing improved adaptability to changing market conditions.

Using Differential Privacy to Define Personal, Anonymous and Pseudonymous Data

This paper introduces the concept of differential privacy (DP) as a novel technical tool that can quantifiably assess the identification #risks of #databases, thereby aiding in the classification of data. By allocating a privacy budget in advance, data controllers can establish auditable and reviewable boundaries between #personal, #anonymous, and #pseudonymous data, while integrating this framework into broader data #riskmanagement practices.

Correlation Pitfalls With ChatGPT: Would You Fall for Them?

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"This paper presents an intellectual exchange with #chatgpt, … , about correlation pitfalls in #riskmanagement. … Our findings indicate that ChatGPT possesses solid knowledge of basic and mostly non-technical aspects of the topic, but falls short in terms of the mathematical goring needed to avoid certain pitfalls or completely comprehend the underlying concepts."

Multivariate risk measures for elliptical and log‑elliptical distributions

"This paper introduces the multivariate range Value-at-Risk (MRVaR) and multivariate range covariance (MRCov) as #risk#measures for #riskmanagement in #regulation and investment… Frequently-used cases in industry, such as normal, student-t, logistic, Laplace, and Pearson type VII distributions, are presented with numerical examples."

What are Large Global Banks Doing About Climate Change?

"From a #riskmanagement perspective, it is challenging to #model physical and #transitionrisks given the #uncertainty around #climaterisk drivers, such as changes in #governmentpolicy aimed at reducing #greenhousegasemissions, the pace of technological change, and uncertainty around the transmission channels. A dearth of in-house modeling tools and reliance on #thirdparty vendors also hamper #banks’ ability to properly understand and manage #risks. The most recent #boe climate biennial exploratory scenario (#cbes) noted that “banks varied in their ability to scrutinize and understand the strengths and weakness of third-party models, and adapt them appropriately to the CBES.” As a result, projected #losses for banks varied widely, suggesting a high degree of uncertainty about the magnitude of climate risks as well as a limited ability to accurately reflect such risks in business decisions."

The Capital‑on‑Capital Cost in Solvency II Risk Margin.

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This paper explores potential revisions to the calculation of the #solvencyII#risk margin (RM) and contributes to the ongoing discussion by formally defining the concept of capital-on-capital cost. The paper highlights the need for practitioners to consider capital-on-capital costs in their #lifeinsurance#riskmanagement frameworks and for policymakers to carefully evaluate the potential impact of any revisions to the calculation of the RM.