Plaid. has been granted a patent for a system that secures digital transactions by authenticating user accounts with external systems. The method involves storing user credentials, processing transaction details, and utilizing machine learning to assess and enhance transaction execution based on retrieved account data. GlobalData’s report on Plaid gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on Plaid, EMV tokenization was a key innovation area identified from patents. Plaid's grant share as of June 2024 was 52%. Grant share is based on the ratio of number of grants to total number of patents.
Digital transaction assessment and security method
The patent US12026704B2 outlines a method and system for securing digital transactions through a multi-step process involving user account authentication and machine learning assessments. The method begins with a computing platform receiving user account credentials, which are stored alongside an authentication token. This token is communicated to an external application service. Upon receiving a transaction initiation request that references the authentication token and includes details about the transaction, the system instantiates a virtualized application instance to emulate user interface access with the external system. The user account is programmatically authenticated using the stored credentials, allowing the retrieval of account data and identification of related user accounts. This data is then processed in conjunction with the transaction details to generate a digital transaction assessment.
The assessment informs the execution of the digital transaction, enabling the system to determine whether to skip certain processes or configure additional ones. The method also allows for the initiation of the transaction based on the assessment, which can include permitting or prohibiting the transaction between the originator and recipient accounts. Furthermore, the system can update its machine learning model based on interaction feedback, enhancing its ability to evaluate future transactions. The claims also encompass the retrieval of user information, account balances, and transaction histories, ensuring a comprehensive approach to transaction security. Overall, the patent presents a sophisticated framework for enhancing the security and efficiency of digital transactions through advanced authentication and machine learning techniques.
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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.
