Envestnet. has been granted a patent for a system that synthesizes user transactional data to de-identify sensitive information. The method involves clustering users based on similar transactional behaviors and generating synthesized data by shuffling and perturbing their transactional information. GlobalData’s report on Envestnet 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 Envestnet, was a key innovation area identified from patents. Envestnet's grant share as of June 2024 was 39%. Grant share is based on the ratio of number of grants to total number of patents.
De-identifying sensitive user transactional data through synthesis
The granted patent US12032721B2 outlines a method and system for processing transactional data from multiple users to generate synthesized transactional data. The core functionality involves identifying transactional data, clustering users based on their transactional behaviors, and creating groups of users with similar patterns. The system generates synthesized data by selecting a subset of the original transactional data, shuffling it among users within each group, and sampling transactions based on the number and category of transactions associated with each user. This process ensures that the synthesized data maintains the same structure as the original data while allowing for variations through perturbation techniques.
Additionally, the patent details various methods for perturbing the shuffled transactional data to enhance privacy and data utility. This includes techniques such as perturbing transaction amounts, shuffling elements of transaction descriptions, and masking personally identifiable information (PII) using deep learning methods. The system is designed to ensure that the number of transactions sampled matches the original data's characteristics, thereby preserving the integrity of the synthesized data. The patent emphasizes the importance of maintaining user privacy while enabling the analysis of transactional behaviors, making it relevant for applications in financial services and data analytics.
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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.
