Synchrony Financial‘s patented method involves dynamically extracting subsets of transaction datasets from multiple data stores in real-time, merging them into an output dataset, analyzing for patterns, and generating alerts. The system continuously adapts to new transaction data, providing real-time insights for improved decision-making. GlobalData’s report on Synchrony Financial gives a 360-degree view of the company including its patenting strategy. Buy the report here.

According to GlobalData’s company profile on Synchrony Financial, was a key innovation area identified from patents. Synchrony Financial's grant share as of February 2024 was 45%. Grant share is based on the ratio of number of grants to total number of patents.

Dynamic extraction and analysis of transaction data in real-time

Source: United States Patent and Trademark Office (USPTO). Credit: Synchrony Financial

A recently granted patent (Publication Number: US11922516B2) outlines a method for dynamic extraction and analysis of data. The method involves receiving identification of multiple data stores storing transaction datasets, generating scripts based on parameters and a filtering scheme, extracting subsets of transaction datasets in real-time, merging these subsets into an output dataset, analyzing the output dataset to recognize patterns such as fraud attempts or trends, and outputting alerts based on the recognized patterns. The method also includes features like automatically correcting disparities, normalizing datasets, and utilizing machine learning models for pattern recognition.

Furthermore, the patent includes claims for a system and a non-transitory computer-readable storage medium implementing the dynamic data extraction and analysis method. The system comprises components like a communication transceiver, memory, and processor to carry out the steps of identifying data stores, generating scripts, extracting subsets, merging datasets, analyzing patterns, and issuing alerts. The computer-readable storage medium contains a program executable by a processor to perform the method, including features like identifying fraud attempts, trends, disparities, and deviations in transaction data. Overall, the patent presents a comprehensive approach to dynamically extracting, analyzing, and alerting based on patterns in transaction datasets in real-time, with potential applications in fraud detection, trend analysis, and data reconciliation across various data store platforms and structures.

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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.