MetLife. has been granted a patent for a predictive contextual transaction scoring system that analyzes feedback data from person-to-person transactions. The system matches service requesters with providers based on contextual characteristics and predicts transaction scores to enhance marketplace interactions. GlobalData’s report on MetLife 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 MetLife, was a key innovation area identified from patents. MetLife's grant share as of June 2024 was 60%. Grant share is based on the ratio of number of grants to total number of patents.
Predictive scoring system for person-to-person transactions
The patent US12002057B2 describes a predictive contextual transaction scoring system designed to enhance marketplace interactions by analyzing historical transaction data. The system comprises network interfaces, a processor, and memory that stores executable instructions. These instructions enable the system to receive contextual feedback data related to past transactions, identify unique preferences of requesting parties, and analyze attributes of service providers. Upon receiving a new service request, the system predicts a feedback score for potential service providers based on the alignment of their attributes with the requesting party's preferences. If the predicted score exceeds a baseline transaction score, the system recommends the service provider to facilitate the transaction.
Additionally, the patent outlines specific details that contextual transaction data may include, such as time of day, service duration, location, and cost. The system can also prioritize preferences based on their impact on transaction outcomes and assign service providers based on their availability. The method and system aim to improve the efficiency and satisfaction of transactions in a marketplace by leveraging data-driven insights to match service providers with the unique needs of requesting parties.
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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.
