On 29 June 2020, the European Banking Authority (EBA) and the European Securities and Markets Authority (ESMA) issued their respective responses to the European Commission’s consultation on a new EU Digital Finance Strategy.

In its response the EBA highlights the importance of technological neutrality in regulatory and supervisory approaches as a means to facilitate innovation in the financial sector and support scaling cross-border. The EBA states that this requires comprehensive and ongoing monitoring of the application of innovative technologies to enable the timely identification of opportunities and risks and adjustments as appropriate to regulatory and supervisory approaches. In this context, the EBA supports proposed enhancements to coordination mechanisms, such as the EBA’s FinTech Knowledge Hub and the European Forum for Innovation Facilitators, to facilitate a stronger dialogue between industry and regulatory and supervisory authorities on innovation-related issues.

ESMA’s key point in its response is that cooperation around financial innovation at the EU level is key to removing fragmentation in the digital financial services market. ESMA believes that certain specific initiatives would support this goal, such as developing Digital Financial Identities that are usable and recognised throughout the EU, based around the existing ISO 17442 global standard of the Legal Entity Identifier.

ESMA focuses on a number of issues in its response including promoting a well-regulated data-driven financial sector. It argues that key requirements for efficient and easy use of data are data standardisation and harmonisation, security of IT-systems and legal certainty regarding pertinent responsibilities, liabilities and usage permissions. For publicly available data to be easily usable, ESMA states that they need to be subject to unrestricted access in a timely manner. Data quality issues should be addressed through robust verification mechanisms, and text data need to be in machine-readable format. An area of interest for ESMA is the potential for AI-based tools (such as machine learning) to support the authority’s statistics-related activities.