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Austrian Court Rules Credit Agency Violated GDPR Transparency Laws

The court ordered the agency to comply within four weeks, emphasizing the need for transparency in algorithmic systems that impact consumers.

This is a paper. On this something is written.
This is a paper. On this something is written.

Austrian Court Rules Credit Agency Violated GDPR Transparency Laws

The Austrian Federal Administrative Court has ruled that a credit information agency violated GDPR transparency requirements. The May 28, 2025, decision found the agency failed to provide sufficient details about its automated decision-making processes and processing purposes.

The court determined that the agency's general statements about 'providing credit information' and 'providing marketing information' were insufficient under Article 15(1)(a) GDPR. It also found that the agency had breached Article 15(1)(h) GDPR by denying automated decision-making despite using automated score calculation for third-party contract decisions.

The court emphasized that data subjects must receive meaningful information about automated decision-making, including which personal data was used and how it influenced specific outcomes. This ruling comes amidst increased scrutiny of automated decision-making across Europe, with the UK modernizing its data protection framework and studies revealing accuracy issues in AI-powered systems. The agency processed data from multiple sources but failed to clearly indicate which specific data served which purposes.

The court ordered the agency to provide compliant information within four weeks or face execution proceedings. It partially upheld a data protection complaint filed on December 19, 2018, finding breaches of Article 15 GDPR. This enforcement approach contrasts with recent criticism of other European data protection authorities for insufficient GDPR enforcement.

The Austrian Federal Administrative Court's ruling reinforces the importance of transparency in algorithmic systems that affect consumers. Companies using automated scoring for advertising personalization, customer segmentation, or conversion optimization must now provide more detailed explanations about their automated decision-making logic and processing purposes.

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