IP Library › Granted Patent US 12,730,925
Granted Patent B2
US 12,730,925 · App. 17/862,465 · Granted Sep 8, 2026

Masking compliance measurement system

Inventors: Sourav Chauhan (New Delhi, IN); Kunal Khanvilkar (Pune, IN); LeAnn Hopkins (Lake Worth/Wellington, FL)
Assignee: NICE LTD
G06F21/6245G06F18/217G06N5/025G06F2221/2141
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Quick Facts
Patent No.
US 12,730,925
App. No.
17/862,465
Filed
Jul 12, 2022
Granted
Sep 8, 2026
Kind
B2
Art Unit
2497
USPC
726/26
Abstract

A system is adapted to automatically evaluate compliance to data masking rules by a service provider. The system includes a processor and a non-transitory computer readable medium carrying instructions. The instructions include receiving a list of private data elements for which masking is required, and receiving a transcript of a particular interaction between the service provider and a customer, where the transcript includes data elements, at least of which is a private data element. The instructions also include analyzing the transcript with natural language processing to identify times or locations within where private data elements are recorded; determining, based on a set of compliance rules and the analyzed transcript, whether any private data element are unmasked at the identified times or locations; and, if a private data element is unmasked, issuing an output related to the unmasked private data elements.

Claims (32)

1 . A system adapted to automatically evaluate compliance to private data masking rules by a contact center service provider, the system comprising:

a processor and a non-transitory computer readable medium operably coupled thereto, the computer readable medium comprising a plurality of instructions stored in association therewith that are accessible to, and executable by, the processor, to perform operations which comprise:

receiving a list of private data elements for which masking is required;

receiving a customer-service provider interaction transcript of a particular interaction between the service provider and a customer, wherein the transcript comprises a plurality of data elements that includes at least one private data element of the list of private data elements;

analyzing the transcript with natural language processing to identify times or locations within the transcript where the at least one private data element is recorded;

determining based on a set of compliance rules and the analyzed transcript whether, at the identified times or locations, any private data element of the at least one private data element is unmasked;

based on a private data element of the at least one private data element being unmasked, incrementing a mask miss counter, wherein the mask miss counter tracks a total number of unmasked private data elements; and

based on the mask miss counter divided by a total number of expected masked data elements exceeding a threshold, issuing an output to a display of an agent, manager, or supervisor, wherein the output is related to the at least one unmasked private data element.

2 . The system of claim 1 , wherein the transcript includes a recording of at least one of a text interaction, a text translation of a voice interaction, or computer screen activity.

3 . The system of claim 1 , wherein the list of private data elements includes at least one of a social security number, a national identification number, a credit card number, a person's name, a company name, an organization name, a phone number, a postal code, a date of birth, an email address, a physical address, a postal address, an income level, a net asset value, a purchase history, or medical information.

4 . The system of claim 1 , wherein the output comprises a mask compliance coaching module, a link to the mask compliance coaching module, or instructions for accessing the mask compliance coaching module.

5 . The system of claim 1 , wherein the operations further comprise computing a compliance statistic for at least one of the particular interaction or a plurality of interactions including the particular interaction.

6 . The system of claim 5 , wherein the output comprises an evaluation of the service provider or a report comparing the service provider to another service provider.

7 . The system of claim 1 , wherein at least one private data element of the list of private data elements is required to be private by a law or government regulation.

8 . The system of claim 5 , wherein the compliance statistic comprises at least one of a total number of private data elements, a total number of masked private data elements, a total number of unmasked private data elements, a ratio, fraction, or percentage of private data elements that are masked, or a ratio, fraction, or percentage of private data elements that are unmasked, an average of any of the foregoing, or a ratio between any two of the foregoing.

9 . The system of claim 5 , wherein the compliance statistic comprises a compliance score for the service provider.

10 . The system of claim 9 , wherein based on the compliance score for the service provider being below a first threshold value, issuing a coaching output comprising at least one of a mask compliance coaching module, a link to the mask compliance coaching module, or instructions for accessing the mask compliance coaching module.

11 . The system of claim 9 , wherein based on the compliance score for the service provider being above a second threshold value, issuing a reward or recognition output.

12 . A computer-implemented method adapted to automatically evaluate compliance to private data masking rules by a contact center service provider, the method comprising:

receiving a list of private data elements for which masking is required;

receiving a customer-service provider interaction transcript of a particular interaction between the service provider and a customer, wherein the transcript comprises a plurality of data elements that includes at least one private data element of the list of private data elements;

with natural language processing, analyzing the transcript to identify times or locations within the transcript where the at least one private data element is recorded;

based on a set of compliance rules and the analyzed transcript, determining whether, at the identified times or locations, any private data element of the at least one private data element is unmasked; based on a private data element of the at least one private data element being unmasked, incrementing a mask miss counter, wherein the mask miss counter tracks a total number of unmasked private data elements; and

based on the mask miss counter divided by a total number of expected masked data elements exceeding a threshold, issuing an output to a display of an agent, manager, or supervisor, wherein the output is related to the at least one unmasked private data element.

13 . The computer-implemented method of claim 12 , wherein the transcript includes a recording of at least one of a text interaction, a text translation of a voice interaction, or computer screen activity.

14 . The computer-implemented method of claim 12 , wherein the list of private data elements includes at least one of a social security number, a national identification number, a credit card number, a person's name, a company name, an organization name, a phone number, a postal code, a date of birth, an email address, a physical address, a postal address, an income level, a net asset value, a purchase history, or medical information.

15 . The computer-implemented method of claim 12 , further comprising computing a compliance statistic for at least one of the particular interaction or a plurality of interactions including the particular interaction.

16 . The computer-implemented method of claim 15 , wherein the compliance statistic comprises at least one of a total number of private data elements, a total number of masked private data elements, a total number of unmasked private data elements, a ratio, fraction, or percentage of private data elements that are masked, or a ratio, fraction, or percentage of private data elements that are unmasked, an average of any of the foregoing, or a ratio between any two of the foregoing.

17 . The computer-implemented method of claim 15 , wherein based on the compliance statistic being below a first threshold value, the output comprises a coaching output comprising at least one of a mask compliance coaching module, a link to the mask compliance coaching module, or instructions for accessing the mask compliance coaching module.

18 . The computer-implemented method of claim 15 , wherein based on the compliance statistic being above a second threshold value, the output comprises a reward or recognition output.

19 . The computer-implemented method of claim 15 , wherein the output comprises an evaluation of the service provider including the compliance statistic or a report comparing the compliance statistic to a second compliance statistic of a second service provider.

20 . The computer-implemented method of claim 19 , wherein the rule-based machine learning algorithm is a learning classifier system, association rule learning system, or artificial immune system.

Assignments (2)
SECURITY INTEREST Recorded Feb 26, 2026
From: NICE LTD; NICE SYSTEMS INC.; NICE SYSTEMS TECHNOLOGIES INC.; INCONTACT, INC.
To: JPMORGAN CHASE BANK, N.A., AS ADMINISTRATIVE AGENT
Reel/Frame 074986/0208 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 12, 2022
From: CHAUHAN, SOURAV; KHANVILKAR, KUNAL; HOPKINS, LEANN
To: CORY, MOTY
Reel/Frame 060480/0191 →
Continuity (1)
Related Publication 20240020408A1 · Jan 18, 2024
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