Stripe uses your transaction history, device data, and other personal information to train its fraud detection algorithms and other AI/machine learning systems.
This analysis describes what Stripe's agreement states, permits, or reserves. It does not constitute a legal determination about enforceability. Regulatory applicability and practical outcomes may vary by jurisdiction, enforcement context, and individual circumstances. Read our methodology
The clause establishes a direct operational basis for processing transaction data beyond real-time fraud prevention, extending to model development and refinement activities that may involve historical data analysis and algorithmic improvement cycles.
Removal of specific disclosure about using transaction data for machine learning model training, reducing transparency about automated decision-making and model development practices.
View full change record →Your transaction data and device information feed into Stripe's machine learning fraud models, meaning automated systems trained on your behavior may make decisions about whether future transactions — including those of other consumers — are flagged as fraudulent, with limited ability to contest such decisions.
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We may use aggregated, de-identified data derived from your use of our services, including document metadata and usage patterns, to develop, train, and improve our artificial intelligence and machine learning models and product features.
engage in any of the foregoing in connection with any use, creation, development, modification, prompting, fine-tuning, training, testing, benchmarking or validation of any artificial intelligence or machine learning tool, model, system, algorithm, product or other technology ("AI Tool").
We are simplifying our Terms of Use, including clarifications around the use of AI tools, and their data use. We have moved the terms that describe AI Features, which were previously written for a Creator audience and located under the AI-Based Tools Supplemental Terms and Disclaimer, into the User ...
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"We use Personal Data to detect and prevent fraud, and to develop and improve our fraud detection models and other machine learning systems. This may include using transaction data, device information, and other Personal Data to train and refine our systems.— Excerpt from Stripe's Stripe Privacy Policy
REGULATORY FRAMEWORK: GDPR Art. 22 restricts automated decision-making with legal or similarly significant effects, requiring either explicit consent (Art. 6(1)(a)), contractual necessity (Art. 6(1)(b)), or specific member state law authorization; affected individuals have the right to human review. GDPR Art. 5(1)(b) purpose limitation requires that use of data for ML training be compatible with the original collection purpose. The EU AI Act (Regulation 2024/1689) classifies certain fraud detection systems as high-risk AI, imposing transparency and conformity assessment obligations. FTC Act Section 5 applies to deceptive AI practices.
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The clause establishes a direct operational basis for processing transaction data beyond real-time fraud prevention, extending to model development and refinement activities that may involve historical data analysis and algorithmic improvement cycles.
Your transaction data and device information feed into Stripe's machine learning fraud models, meaning automated systems trained on your behavior may make decisions about whether future transactions — including those of other consumers — are flagged as fraudulent, with limited ability to contest such decisions.
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