Nos derniers articles

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.

The US-EU divide on #esg policies for businesses stems from differing economic factors, notably the US stock market's influence on retirement funds and the #us's oil production dominance versus the #eu's oil imports. To address this, a "Net Zero Transformation rating" should separate #climate concerns from other ESG aspects. Shifting corporate activism towards heavy users like utilities and key producers like car manufacturers, rather than focusing solely on fossil fuel producers, could accelerate a #netzerotransition.

The study analyzes how #cybersecurityrisk impacts #clawback policy adoption in #us listed firms from 2008-2018. It finds that rising cybersecurity risk increases clawback adoption, influenced by business goals, management preferences, and market efficiency. Stronger tech commitment and non-co-opted boards reduce this effect, showing firms consider clawbacks as preventive against #misconduct, incorporating cybersecurity risk.

Corporate #riskmanagement encompasses both financial hedging and #operationalrisk #riskmitigation. This study investigates how #laborlaw #breaches during surprise inspections impact supplier choices in major #us firms.

Recent #ai developments, particularly in Natural Language Processing (#nlp) like #gpt3, are widely used. Ensuring safety and trust with increasing NLP use requires robust guidelines. Global AI #regulations are evolving through initiatives like the #euaiact, #unesco recommendations, #us AI Bill of Rights, and others. The EU AI Act's comprehensive regulation sets a potential global benchmark. NLP models are subject to existing rules, such as #gdpr. This paper explores AI regulations, GDPR's application to AI, the EU AI Act's #riskbasedapproach, and NLP's role within these frameworks.

This is a note on the #gdpr and the use of #us-based #cloudservers. The note raises concerns about the #risk of US #intelligenceagencies having access to #data transferred to any US cloud from the #eu, or directly accessed by US agencies, even while still in the EU / #eea or while in transit. The note discusses cases in #france, the #netherlands, and #germany that have addressed these issues, concluding that the legality of the use of US cloud servers and solutions remains problematic.

"We examine the impact of the U.S. withdrawal from the #parisagreement on the relationship between #climaterisk and #systemicrisk of #us #globalbanking. We find that after 2017, investors stopped pricing climate risk into U.S. systemic risk directly, consistent with domestic investors expecting climate risk #deregulation. However, climate risk still indirectly impacts the U.S. systemic risk through the internal capital markets of U.S. #global #banks operating abroad."

"We use the recently failed #svb as a case study. Our [#machinelearning #textanalysis] findings indicate a weaker emphasis on #riskgovernance by SVB and an environment, particularly after 2011, where the #ceo became more dominant in influencing SVB’s #riskculture. We also show that despite recognition of the portfolio problems, SVB’s CEO’s tone indicated that #regulatorycompliance and #riskstrategy of the #bank would #mitigate these #risks. We observe an alignment between the #riskculture of SVB and other banks with the highest uninsured deposits as well as with two #us #gsibs."

This research evaluates different regression models to predict #flood-induced #insuranceclaims, using the #us #national #floodinsurance Program (#nfip) dataset from 2000 to 2020. The models studied include #neuralnetworks (Conditional Generative Adversarial Networks), #decisiontrees (Extreme Gradient Boosting), and #kernel-based regressors (#gaussian Process). The study identifies key predictors for regression, highlighting factors that influence flood-related financial damages.

"We use #naturallanguageprocessing to #measure #supplychainrisk (#scr) faced by #us firms, as expressed in narratives of quarterly earnings conference calls."