Top EU Court Rules Against Use of Automated Decision-Making Algorithms in Credit Information Industry

December 11, 2023

The Court of Justice of the EU (CJEU) ruled on December 7th that the GDPR prohibits the use of automated scoring if it significantly impacts people’s lives. The case concerns SCHUFA, Germany’s largest private credit agency, which rates people according to their creditworthiness with a numerical score. Article 22 of the GDPR establishes that the data subject has the right not to be subject to a decision based solely on automated processing, including profiling, which produces legal effects concerning the data subject at issue. The CJEU ruled that the automated creation of a “probability value based on personal data concerning his or her ability to meet payment commitments in the future” by a credit information agency constitutes an “automated individual decision-making” within the meaning of Article 22 when the value will be sent to a third party that uses that value to establish, implement, or terminate a contractual relationship with that person. The case was remanded to determine if this interpretation of Article 22 implicates SCHUFA’s scoring system.

Over the last decade, EPIC has consistently advocated for the adoption of clear, commonsense, and actionable AI regulations in the United States. EPIC has published two major reports on the United States government’s use of automated decision making algorithms, spanning over two years of research and open records requests on government procurement practices. Additionally, EPIC has published a report on the harms of generative AI as well as a report on criminal risk assessments that use similar models to credit worthiness algorithms. Furthermore, EPIC has sent comments to the Consumer Financial Protection Bureau (CFPB) in response to its Request for Information regarding financial institutions’ use of AI and machine learning systems and in response to the CFPB’s Request for Information on data brokers. Finally, EPIC has also published blog posts related to algorithmic scoring.

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