Nice. has filed a patent for a system that automatically evaluates a service provider’s compliance with data masking rules. The system uses natural language processing to analyze interactions between the provider and customers, identifying any unmasked private data elements and issuing related outputs. GlobalData’s report on Nice gives a 360-degree view of the company including its patenting strategy. Buy the report here.

According to GlobalData’s company profile on Nice, Intelligent contact centers was a key innovation area identified from patents. Nice's grant share as of January 2024 was 60%. Grant share is based on the ratio of number of grants to total number of patents.

Automated system for evaluating compliance to data masking rules

Source: United States Patent and Trademark Office (USPTO). Credit: Nice Ltd

The patent application (Publication Number: US20240020408A1) describes a system and method for automatically evaluating compliance with data masking rules by a service provider. The system includes a processor and a computer-readable medium with instructions to receive a list of private data elements, analyze transcripts of interactions between the service provider and customers using natural language processing, and determine if any private data elements are unmasked based on compliance rules. If unmasked data is identified, the system issues an output related to the violation, such as a mask compliance coaching module or instructions for accessing it. The system can also compute compliance statistics for interactions and issue evaluations or reports comparing the service provider's compliance to others.

Furthermore, the method involves receiving private data elements, analyzing transcripts to identify unmasked data, and issuing outputs based on compliance rules. The method can compute compliance statistics, such as the total number of masked or unmasked private data elements, and provide coaching or rewards based on the compliance score. Outputs may include evaluations of the service provider's compliance, comparisons to other providers, or links to coaching modules. The patent application also mentions the use of rule-based machine learning algorithms like learning classifier systems or artificial immune systems in the evaluation process. This system and method aim to ensure data privacy and compliance with regulations by automating the monitoring and enforcement of data masking rules during interactions between service providers and customers.

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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.