Nos derniers articles

The paper examines climate litigation's growing impact on banks, noting limited current effects but a projected increase. Key risks include reputational damage and influences on risk management and investment decisions. Banks are urged to address climate litigation risks proactively to enhance resilience, with future research suggested on mitigation strategies.

“The study demonstrates the capability of certain public sector banks to bear operational risk on a particular level of regulatory capital. The ability of a bank to be successful under unfavorable conditions is related to its operational risk, regulatory capital and management processes.”

Examining the Great Depression, we use novel methods and data to show that despite 9,000 #bank closures, #risk increased instead of leaving the system. Healthier #banks acquired risk through mergers, with each acquisition raising the acquiring bank's risk by 25%. #financialcrises don't rapidly eliminate risk; merger policies affect #systemicrisk.

Local communities exposed to #fraudulent #investmentadvisory firms tend to withdraw deposits from their affiliated #banks, even though the banks are not involved in the #misconduct. The #reputationalrisk is more significant when banks share names with fraudulent advisory firms or are located in areas with high social norms. The author establishes causality by exploring a quasi-natural experiment in which #fraud is likely exogenously revealed.

"#banks take costly actions (such as higher #capitalization, #liquidity holding, and advanced #riskmanagement) to avoid financial distress and #bankruns ... We show that #prudential #regulations have an informational impact: sufficiently tight regulations can eliminate inefficient separating equilibria in banks’ signaling game, thereby changing the information available to creditors and their incentives to run."

This paper examines the use of #machinelearning methods in the context of #banks' #capitalrequirements, specifically the internal Ratings Based (#irb) approach. The authors discuss the advantages and risks of using machine learning in this domain, and provide recommendations related to #risk parameter estimations, #regulatory capital, the trade-off between performance and interpretability, international #banking competition, and #governance, #operationalrisk, and training.

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.

"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."

Well-capitalized #banks play a crucial role in supporting economic adaptation to #weather-induced #labor #productivity #risk.

This paper discusses the efficiency, effectiveness, and costs of #denmark's #antimoneylaundering (#aml) #compliance standards. Although the country has caught up with international standards, the current global AML compliance system is ineffective in deterring #moneylaundering by professional actors. The system imposes significant costs on #banks and society, while spending too much time on minor infractions. To improve the system, the author argues for a #risk-based approach that automates large portions of the compliance process and allows compliance staff to focus on investigations.