In this issue, we look at the latest developments in EU data protection and AI legislation, the bundling of supervision by the BfDI and the consultation on clearing thresholds under EMIR 3. These topics not only affect compliance practice, but also the strategic direction of companies in the coming months.
Inhalt
- EU Commission – Guidelines for Europe’s AI leadership with the AI Continent Action Plan
- BfDI – Pooling supervision for greater efficiency and clear responsibilities
- EDPB – Risks and mitigation strategies related to AI and data protection
- EMIR 3.0: ESMA launches consultation on clearing thresholds
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EU Commission – Guidelines for Europe’s AI leadership with the AI Continent Action Plan
Summary:
The European Commission has presented the “AI Continent Action Plan” – a package of measures to establish Europe as a leading location for artificial intelligence (AI) worldwide. The plan is based on five strategic pillars: Building large-scale AI and computing infrastructures (AI Factories & Gigafactories), improving access to data (Data Labs and Data Union Strategy), promoting industry-specific AI applications (Apply AI Strategy), developing AI specialists (AI Skills Academy, Talent Pool) and regulatory facilitation for the implementation of the AI Act (e.g. AI Act Service Desk). At the same time, the Commission is launching several public consultations on the design of the measures and is calling for participation.
Opinion:
This action plan marks a turning point: the EU not only wants to regulate, but also actively shape and scale – a signal to companies, researchers and compliance officers to develop AI strategies in specific business areas. This is particularly relevant for compliance and data protection departments: The AI Act is being operationalized – through a central service desk and accompanying guidelines. Companies should initiate internal implementation projects at an early stage, especially if they already have AI applications or plans. At the same time, the funding architecture (e.g. AI Factories, InvestAI) offers opportunities for projects that rely on trustworthy AI.
Source
BfDI – Pooling supervision for greater efficiency and clear responsibilities
Summary:
The Federal Commissioner for Data Protection and Freedom of Information (BfDI) has presented a new structure for the supervision of data protection in Germany. This change aims to better bundle the responsibilities and cooperation within the data protection supervisory authorities in order to increase the efficiency and transparency of supervision. The measure is based on the provisions of the coalition agreement and is intended to improve the work of the supervisory authorities and simplify cooperation with companies and citizens.
Opinion:
For data protection officers in Germany, the bundling of supervision means a clear improvement in communication and clarity in cooperation with the supervisory authorities. This adjustment should facilitate processes in medium-sized companies in particular, which will be able to respond to inquiries more quickly and efficiently thanks to a clear allocation of responsibilities. However, the adjustment also offers the opportunity to optimize existing data protection processes in order to be able to react more quickly to regulatory requirements. Companies should therefore ensure that their internal processes continue to comply with the new supervisory requirements and make adjustments where necessary.
EDPB – Risks and mitigation strategies related to AI and data protection
Summary:
The EDPB has published a report addressing the risks of the nexus between AI and data protection. It proposes measures to mitigate the risks and promote data protection in AI applications. Key recommendations include transparency, data minimization, regular privacy impact assessments and strong risk management.
Opinion:
The EDPB’s recommendations highlight the importance of integrating data protection requirements right from the development stage of AI technologies. In concrete terms, this means that companies must carry out data protection impact assessments (DPIAs) from the outset and update them regularly – especially when introducing new AI systems. Data protection risks can be significantly reduced through data minimization and the use of anonymization techniques. This not only protects the privacy of users, but also minimizes potential legal risks for companies. Another key element of the recommendations is the promotion of transparency: companies should disclose how their AI models collect and process data in order to gain the trust of users and regulators. Compliance departments must therefore ensure that not only legal requirements are met, but also that a culture of responsible and transparent data handling is created.
EMIR 3.0: ESMA launches consultation on clearing thresholds
Summary:
ESMA has launched a consultation on the new clearing thresholds under EMIR 3. This consultation concerns the definition of thresholds for mandatory trading and clearing of derivatives. The aim is to increase the stability of the financial market and minimize the risks posed by derivatives trading by enabling broad participation of market participants and accurate analysis of market conditions.
Opinion:
ESMA’s consultation on the clearing thresholds under EMIR 3 is of key importance for companies in the area of compliance and financial market regulation. Clearing obligations affect not only banks and financial institutions, but also companies involved in derivatives transactions. The establishment of new thresholds could have far-reaching effects on the market structure and risk management practices of companies. These developments require a continuous review of internal processes and an adjustment of risk management strategies to ensure that the new requirements are implemented in a timely manner.
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Your Riscreen team