EU Regulator’s Priorities for 2027 Include AI and Tokenization
The European Union’s securities regulator plans to make artificial intelligence and tokenization a supervisory priority starting in 2027, signaling a broader regulatory focus on how emerging technologies are being used across financial services. The European Securities and Markets Authority (ESMA) said it will work with national regulators to examine how regulated financial firms use AI […] The…
The European Securities and Markets Authority (ESMA) intends to prioritize artificial intelligence (AI) and tokenization as supervisory concerns beginning in 2027. This signals a broader focus on how emerging technologies are integrated across financial services. ESMA is collaborating with national regulators to examine the use of AI and tokenized products in core activities, such as products and processes that directly impact customers.
The initiative, dubbed "Innovation with investor safeguards," will concentrate on enhancing regulators' ability to oversee new technologies while evaluating firms' governance, data reliability, and customer outcomes.
European regulators aim to map where financial institutions currently use or plan to implement AI and tokenization. They will also conduct preliminary assessments on a subset of firms most affected by these technologies and identify emerging areas of tokenization in financial markets. This effort follows the EU's expansion of attention beyond establishing rules for crypto assets.
The EU's Markets in Crypto-Assets (MiCA) framework went into effect in 2024, while ESMA's new initiative will investigate how AI and tokenization are incorporated into the wider securities industry.
Firms are increasingly employing AI and tokenized products in everyday financial services, according to ESMA. The regulator also acknowledges that technological innovation can present both advantages and risks. ESMA has previously expressed concerns about AI's potential risks in investment services, including algorithmic bias, data-quality issues, opaque decision-making, and excessive reliance on technology by firms or clients.
Privacy and security concerns related to the extensive data required by AI systems have also been highlighted.
AI applications in investment services may encompass customer support, fraud detection, risk management, compliance, investment advice, and portfolio management, as outlined by ESMA.
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