L’ACPR et Tracfin actualisent leurs lignes directrices sur la vigilance et les déclarations liées à la lutte contre le blanchiment et le financement du terrorisme (BC-FT). Cette mise à jour intègre les évolutions législatives, les décisions récentes de la Commission des sanctions, les constats sur les dispositifs de surveillance automatisés, l’IA et les nouveaux risques. Elle précise les attentes envers les organismes financiers pour détecter, analyser les opérations atypiques et structurer les déclarations de soupçon afin d’en garantir la qualité. La dernière version datait de 2018.
Integrating Cyber Security (CS) with Enterprise Architecture (EA) offers a holistic approach to managing complex cyber risks. This study, through literature review, focus groups, and interviews, identified four key integration strategies: embedding CS in EA frameworks, leveraging agile secure development, enhancing knowledge exchange, and aligning CS/EA functions. Implementing these can improve Cyber Risk Management efficiency and reliability.
The Format for Incident Reporting Exchange (FIRE) is a framework developed by the FSB to standardize the reporting of cyber and operational incidents across borders. FIRE, created with private sector collaboration, aims to promote consistency, improve communication, and address the challenges of reporting to multiple authorities. It offers standardized information items and flexibility for various operational and cyber incidents, and can be used by third-party service providers and organizations outside the financial sector. The FSB provides a downloadable taxonomy package to facilitate FIRE's global adoption and plans to review its implementation in 2027.
The EU prioritizes cybersecurity and data protection due to rising cyber threats and digital transformation. It employs regulations like GDPR for personal data and the NIS Directive for critical infrastructure resilience. This study analyzes their impact, challenges, and interplay, also comparing them globally to assess effectiveness in safeguarding digital security and fostering trust.
“This update is based on the EBA reporting framework version 4.0 and covers indicators on institutions' profitability, solvency and operational risk, among others. The update also includes a new sets of risk indicators laid down in the Banking Package (Capital Requirements Regulation and Capital Requirements Directive - CRR3/CRD6), indicators related to Environmental, Social and Governance (ESG), and those already used in the context of the Minimum Requirement for Own Funds and Eligible Liabilities (MREL).”
Fairness in machine learning is vital, especially as AI shapes decisions across sectors. In insurance pricing, fairness involves unique challenges due to regulatory demands for transparency and restrictions on using sensitive attributes like gender or race. Traditional fairness methods may not align with these specific requirements. To address this, the authors propose a tailored approach for building fair insurance models using only privatized sensitive data. Their method ensures statistical guarantees, operates without direct access to sensitive attributes, and adapts to varying transparency needs, balancing regulatory compliance with fairness in pricing.
In 2024, the Joint Committee remained key in analyzing cross-sectoral financial risks, publishing joint risk reports in spring and autumn. The spring report warned of elevated risks from weak growth, uncertain rates, and geopolitical tensions, with concerns over rising credit risk and potential market corrections. The autumn report emphasized ongoing economic uncertainty, market volatility, and the effects of high interest rates. It highlighted inflation risks, operational and cyber threats, and included a detailed focus on credit risk, urging financial institutions to maintain strong risk management, provisioning, and adaptability in facing evolving challenges.
This study analyzes resource provisioning with strict reliability demands. It characterizes optimal cost scaling in chance-constrained problems as reliability increases. It reveals limitations of common distributionally robust optimization methods, proposes improvements using marginal distributions or f-divergences, and offers a line search for near-optimal solutions, overcoming data sample limitations.
AI could revolutionize UK sectors, enhancing productivity and decision-making, notably in finance by automating processes and refining decisions like underwriting. However, its rapid evolution raises uncertainties and financial stability risks, including systemic issues from flawed AI models, market instability, and cyber threats. The Financial Policy Committee (FPC) is assessing these risks to ensure safe AI adoption, supporting sustainable growth through vigilant monitoring and regulation.
EIOPA advocates for smarter, harmonized EU regulation and stronger supervision to simplify rules and reduce administrative burdens, boosting European competitiveness. This balanced approach aims to create a thriving Single Market while protecting consumers and ensuring financial stability. EIOPA has already taken steps in this direction and emphasizes that simplification should prioritize EU interests and avoid creating new national burdens.