Quantifying ESG risks is challenging due to unique measurement issues beyond traditional financial risks, hindering firm-level and systemic analysis. Concentrated ESG investments by large institutions correlate with systemic risk, as their simultaneous decisions can destabilize markets. Regulatory frameworks promoting diversification are needed to address this "herd behavior." Further research should explore how ESG risks create hidden systemic vulnerabilities.
« Dans le contexte de la mise en œuvre de DORA, l’ACPR vient, à travers la mise à jour de sa FAQ, préciser certaines informations relatives aux nouvelles obligations qui s’appliquent aux entités financières concernant notamment : les modalités de remise du registre d’information, la réalisation de tests d’intrusion ou le champ d’application de cette nouvelle règlementation. »
This study analyzes ransomware negotiations through a social psychological lens, identifying three phases and distinct negotiation strategies. It offers practical insights for organizations to enhance resilience by understanding threat actor tactics and tailoring response protocols for effective negotiation.
The paper examines how managers strategically adjust the tone of soft information in ESG reports to maximize compensation. It highlights the trade-offs between exaggeration, internal controls, and future reputational costs. Strong incentives with weak controls lead to extreme biases, impacting regulatory decisions, corporate governance, and investor evaluations of ESG disclosures.
A structured IT outsourcing risk management policy is crucial for navigating third-party service complexities. This study proposes a framework integrating IT outsourcing principles with COBIT standards, covering risk identification, analysis, mitigation, and ongoing monitoring. Implementing this policy enhances organizational asset protection, operational continuity, and minimizes outsourcing risks. It improves information security and business process efficiency. This framework provides practical guidance for organizations to effectively manage risks and optimize IT outsourcing value.
EBA launched a climate risk dashboard based on banks’ Pillar 3 ESG disclosures. This tool provides centralized access to climate risk indicators, aiding assessment and monitoring across the EU/EEA banking sector. Data reveals that over 70% of bank exposures are linked to high climate-impact sectors, while less than 30% face elevated physical risk. Many loans secured by immovable property have high energy efficiency scores, though estimates are widely used. The dashboard, based on 2023-2024 data, marks the first step in a broader ESG risk framework, with regular updates planned.
The EBA's Q4 2024 Risk Dashboard shows EU/EEA banks maintaining strong performance. Return on equity rose to 10.5%, and return on assets reached 0.73%. Net interest margin declined slightly, but total income grew due to higher net fee and commission income. Loans to households and businesses increased, while cash balances fell. Non-performing loans decreased, except for commercial real estate. The CET1 ratio remained at 16.0%, reflecting strong capitalization. Liquidity and funding ratios stayed well above requirements. The loan-to-deposit ratio declined as deposits grew faster than loans. Overall, the banking sector remained stable and resilient.
The EBA published final draft ITS amending rules for internal model authorization under CRR, reflecting the EU Banking Package. Key changes include removing the use of internal models for operational risk (deleting AMA references) and updating references to supervisory college regulations. These ITS are based on CRR III amendments.
Increased cyber risk drives U.S. banks to diversify information sources, especially large, nationally chartered banks. This suggests cyber threats erode data confidence, forcing banks to seek verification. Specialized institutions are more vulnerable to data integrity disruptions.
The banking industry faces complex financial risks, including credit, market, and operational risks, requiring a clear understanding of the aggregate cost of risk. Advanced AI models complicate transparency, increasing the need for explainable AI (XAI). Understanding risk mathematics enhances predictability, financial management, and regulatory compliance in an evolving landscape.