Stripe had 11 patents in artificial intelligence during Q1 2024. Stripe Inc filed patents in Q1 2024 for machine learning models to detect fraudulent transactions, determine suitable thresholds for merchants, and continuously monitor training data for various transaction types. The patents also include a method for generating a user interface based on user context and a data structure representing a user interface layout. GlobalData’s report on Stripe gives a 360-degree view of the company including its patenting strategy. Buy the report here.

Stripe grant share with artificial intelligence as a theme is 18% in Q1 2024. Grant share is based on the ratio of number of grants to total number of patents.

Recent Patents

Application: Machine learning for fraud tolerance (Patent ID: US20240095742A1)

The patent filed by Stripe Inc. describes a method and system for fraud detection in transactions using machine learning models. The first machine learning model predicts the likelihood of fraud in a transaction, while a separate model determines a suitable threshold for a merchant based on historical transaction data. This threshold can be automatically applied or recommended to the merchant for acceptance or rejection. The second machine learning model evaluates potential transactions based on features extracted from historical data, the decline score from the first model, and the fraud tolerance threshold assigned to the merchant.

The system further includes operations for transforming features before passing them to the second machine learning algorithm, evaluating transactions to allow or block them, measuring the results of the model's decisions, and retraining the model based on these results. The second machine learning model is also designed to optimize revenue by assigning merchants to segments with common fraud tolerance levels. Overall, the patent outlines a comprehensive approach to fraud detection and prevention in transactions, utilizing machine learning models to enhance security and efficiency for merchants.

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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.