Nice had one patents in mobile during Q4 2023. Nice Ltd has developed a system that automatically analyzes clusters of suspicious transactions by grouping them based on risk factors, computing cluster means and standard deviations, identifying low standard deviation risk factors, and generating a ranked list for further investigation. GlobalData’s report on Nice gives a 360-degreee view of the company including its patenting strategy. Buy the report here.
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Nice grant share with mobile as a theme is 0% in Q4 2023. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Automated transaction clustering based on rich, non-human filterable risk elements (Patent ID: US20230334496A1)
The patent filed by Nice Ltd. describes a system and methods for automatically analyzing clusters of suspicious transactions. The system includes a processor that receives risk factors and suspicious transactions, assigns transactions to data clusters based on risk factor values, computes cluster means and standard deviations for each risk factor, identifies risk factors with low standard deviations, and generates a list of these factors ranked by standard deviation. The system can display this list to a user, initiate automated actions based on the list, and suggest next transactions or clusters to users.
The system and method outlined in the patent aim to efficiently analyze suspicious transactions by clustering them based on risk factors and identifying factors with low variability. By automating this process, the system can assist users in taking appropriate actions such as blocking transactions, alerting customers, or suggesting resolution actions. Additionally, the system can handle numerical and categorical risk factors using a K prototype clustering algorithm, providing a comprehensive approach to transaction analysis. Overall, the patent presents a detailed framework for analyzing and managing clusters of suspicious transactions effectively.
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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.
