Can the European Financial Data Space remove bias in financial AI development? Opportunities and regulatory challenges

Abstract

Abstract The EU data economy’s growth hinges on access to extensive data, with open banking initiatives encouraging data sharing in the financial services industry. Artificial intelligence (AI)-driven tools play a vital role in harnessing the potential of this data, but training these systems carries inherent risks, including the introduction of new or the perpetuation of existing biases. This article examines the role of the European Financial Data Space (EFDS) in AI training, using consumer creditworthiness evaluation as a case study. It investigates whether the EFDS facilitates responsible AI development, considering data protection concerns like legal basis, transparency and control. The objective is to enhance the regulatory proposal for the EFDS, ensuring a well-founded legal framework for utilizing AI responsibly in the financial sector within the broader context of European Data Spaces.

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