This article argues that there is an increasing erosion of the traditional public-private divide, which is a key principle of liberalism and the rule of law. The authors identify a gradual shift, starting with the "responsibilization" of private actors and progressing to risk-based regulation like the GDPR. They contend that the DSA and AI Act represent a new milestone, as they delegate regulatory powers to private companies, effectively turning them into regulators of their TPSPs. This “privatization of public action” is seen as a serious threat to the rule of law because it removes public action from public scrutiny. To address this, the authors suggest connecting the rule of law more closely with democracy, which could help set boundaries for the legislative conferral of regulatory powers to private entities.
This study presents the Bayesian Component Encoder Analysis (BCEA) method for identifying financial crime. Integrating FinBERT, principal component analysis (PCA), and Bayesian networks, BCEA uses financial texts, images, and transaction records. FinBERT extracts semantic features, PCA reduces data complexity, and Bayesian networks model features for probabilistic reasoning. The authors claim BCEA achieves 94.35% accuracy and a 12.78-second recognition time, surpassing LSTM and BERT models. The authors state that the method demonstrates potential for financial supervision and risk management, with possible applications in complex financial scenarios, based on experimental results validating its effectiveness.
AI is not just an incremental improvement but a "paradigm shift" in regulatory compliance. By automating KYC, AML, and transaction monitoring, financial institutions can achieve unprecedented levels of efficiency, accuracy, and risk management. However, this transformative potential comes with significant responsibilities regarding data governance, ethical considerations, and maintaining human oversight. Success in this evolving landscape will hinge on strategic AI implementation, continuous adaptation to regulatory changes, and strong collaboration across the industry and with regulatory bodies. The long-term goal is a more "secure and resilient financial ecosystem."
On 12 August 2025, the European Banking Authority (EBA) published a report on the use of supervisory technology (SupTech) in anti-money laundering and counter-terrorist financing (AML/CFT) oversight. It draws on a November 2024 survey of 31 competent authorities across 25 EU member states (plus three outside) and a January 2025 workshop with the European Commission’s AMLA Task Force.
Global Regulation Tomorrow
. The report notes that 47 % of SupTech tools are already in production, 38 % are under development, and 15 % are exploratory. Benefits include improved data quality, analytics, efficiency and collaboration, while challenges involve limited resources, governance issues, legal uncertainties and organizational readiness.
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This paper 𝗲𝘅𝗮𝗺𝗶𝗻𝗲𝘀 𝘁𝗵𝗲 𝗲𝘀𝗰𝗮𝗹𝗮𝘁𝗶𝗻𝗴 𝘁𝗵𝗿𝗲𝗮𝘁 𝗼𝗳 𝗔𝗜-𝗱𝗿𝗶𝘃𝗲𝗻 𝗳𝗿𝗮𝘂𝗱 𝗮𝗻𝗱 𝗰𝘆𝗯𝗲𝗿𝗰𝗿𝗶𝗺𝗲, highlighting how criminal organizations are rapidly adopting advanced AI, particularly generative AI, to execute sophisticated attacks. It details how these malicious uses lead to 𝗶𝗻𝗰𝗿𝗲𝗮𝘀𝗲𝗱 𝗳𝗶𝗻𝗮𝗻𝗰𝗶𝗮𝗹 𝗹𝗼𝘀𝘀𝗲𝘀, 𝗺𝗼𝗿𝗲 𝗶𝗻𝘁𝗿𝗶𝗰𝗮𝘁𝗲 𝗰𝗿𝗶𝗺𝗲 𝗽𝗮𝘁𝘁𝗲𝗿𝗻𝘀, 𝗮𝗻𝗱 𝗻𝗼𝘃𝗲𝗹 𝘀𝗰𝗮𝗺 𝘁𝘆𝗽𝗼𝗹𝗼𝗴𝗶𝗲𝘀, such as deepfakes and advanced phishing. The document also 𝗲𝘅𝗽𝗹𝗼𝗿𝗲𝘀 𝘁𝗵𝗲 𝗰𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲𝘀 𝗳𝗮𝗰𝗲𝗱 𝗯𝘆 𝗳𝗶𝗻𝗮𝗻𝗰𝗶𝗮𝗹 𝗶𝗻𝘀𝘁𝗶𝘁𝘂𝘁𝗶𝗼𝗻𝘀 𝗶𝗻 𝗱𝗲𝗳𝗲𝗻𝗱𝗶𝗻𝗴 𝗮𝗴𝗮𝗶𝗻𝘀𝘁 𝘁𝗵𝗲𝘀𝗲 𝘁𝗵𝗿𝗲𝗮𝘁𝘀, citing issues like slow AI adoption, outdated risk management frameworks, and underinvestment in defense systems. Ultimately, it 𝗮𝗱𝘃𝗼𝗰𝗮𝘁𝗲𝘀 𝗳𝗼𝗿 𝘁𝗵𝗲 𝘂𝗿𝗴𝗲𝗻𝘁 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 𝗼𝗳 𝗮𝗴𝗶𝗹𝗲, 𝗔𝗜-𝘃𝗲𝗿𝘀𝘂𝘀-𝗔𝗜 𝗱𝗲𝗳𝗲𝗻𝘀𝗲 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗲𝘀 and emphasizes the critical need for industry-wide cooperation to counteract the evolving landscape of AI-enabled financial crime.
The EU Cyber Resilience Act (CRA) establishes cybersecurity standards for connected digital products across the EU. The act aims to enhance transparency and reduce vulnerabilities through risk-based assessments and a CE (Conformité Européenne) marking scheme. While the CRA is seen as a crucial step to address systemic digital risks and regulatory gaps, this analysis suggests it is premature and underdeveloped. The paper raises concerns about the feasibility of its implementation, particularly for small and medium-sized enterprises (SMEs), and highlights challenges with standardized norms and third-party assessment frameworks. The CRA's success, the paper concludes, will depend on its adaptability and sensitivity to economic realities, suggesting it could otherwise hinder innovation.
This paper analyzes a bivariate optimal dividend problem for an insurer with two collaborating business lines under a diffusion model with correlated Brownian motions. The framework incorporates dividend payouts, proportional reinsurance, and inter-line capital transfers to prevent bankruptcy. The authors provide complete analytical solutions, identifying three scenarios with closed-form value functions and optimal strategies. Results show a threshold dividend policy, with the more important line having a lower threshold. Optimal reinsurance decreases with aggregate reserves and stabilizes after a switching point. Correlation between lines affects reinsurance, and the capital transfer rule is consistent across scenarios.
The draft strengthens governance arrangements, clarifies management body roles, and enhances oversight of internal control, risk management, and compliance functions. It incorporates ICT and security risk management in line with DORA, requiring institutions to integrate digital operational resilience into governance frameworks. The revisions also address anti-money laundering, conflicts of interest, and gender-neutral remuneration. Stakeholders can submit feedback until October 2025, with final guidelines to replace the 2017 version.
There is an increasing AI use in insurance—50% in non-life, 24% in life. To address emerging risks, undertakings must clarify supervisory responsibilities, maintain full accountability, and implement proportionate governance. Risk managers should conduct impact-based assessments, emphasizing data sensitivity, consumer impact, and financial exposure. Strong governance includes fairness, data quality, transparency, cybersecurity, and human oversight. Oversight extends to third-party providers, with contractual safeguards required. AI systems must align with existing frameworks like ERM and POG, ensuring traceability, explainability, and resilience throughout their lifecycle. Supervisory convergence across the sector remains a key regulatory goal.
This study explores how natural disasters challenge traditional risk management and insurance mechanisms. Researchers developed a three-strategy evolutionary game model to examine the competition among formal index insurance, informal risk sharing, and non-insurance. The model incorporates insurance company profits to aid optimal pricing. Findings suggest that basis risk and loss ratios strongly influence insurance adoption. Low basis risk and high loss ratios favor index insurance, while moderate loss ratios lead to informal risk sharing. Low loss ratios often result in no insurance uptake. Accurately estimating risk aversion and risk sharing ratios is essential for forecasting index insurance market trends.