Tag Extraction from Free Text for Compliance
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
There is a need for systems and methods that can extract and review pre-approved tags from free-written text by Member Service Representatives (MSRs) to ensure compliance with company policies, particularly for content that may be uncomfortable for legal departments.
Innovation Solution
Systems and methods for generating and utilizing metadata by comparing MSR-entered text to pre-approved tags, allowing MSR to amend or replace identified tags, and storing associations between tags and customers, enabling efficient identification of customer interactions and anticipated activities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If MSRs are empowered to associate free-written notes with customers, then the ability to capture customer information is improved, but the risk of containing problematic content increases
Solution Approach 1:
The system performs preliminary action by pre-approving a set of tags before MSRs use them. The tags are pre-vetted by legal or compliance departments to ensure they meet company policies, eliminating the risk of problematic content before it enters the system.
Solution Approach 2:
The system extracts only the approved tags from the free-written text rather than using the entire text. By separating the problematic free-form content from the approved tag structure, the system retains the information capture capability while removing harmful elements.
2Adaptability or versatility
If free-written text is used to capture customer notes, then the flexibility to express information is improved, but the organization and review process becomes more complex
Solution Approach 1:
The system segments the note-taking process into two distinct parts: the flexible free-written text entry (which can capture any customer information) and the structured approved tags (which provide organized, reviewable metadata). This segmentation allows both flexibility and structure to coexist.
Solution Approach 2:
The approved tags act as an intermediary between the MSR's free-written notes and the company's compliance requirements. The tags translate and rephrase the informal notes into standardized, pre-approved terminology that meets legal and organizational standards.
3Reliability
If pre-approved tags are used instead of free-written text, then compliance with company policies is improved, but the ability to capture nuanced information may be reduced
Solution Approach 1:
The system makes the tag system universal by providing a comprehensive set of pre-approved tags that can represent various nuances, tones, and types of customer information. The tags are designed to cover diverse scenarios while maintaining compliance, eliminating the need to choose between compliance and nuance.
Solution Approach 2:
By pre-creating a comprehensive set of approved tags that capture nuanced information scenarios in advance, the system ensures that when MSRs select tags, they can accurately represent nuanced customer situations while maintaining compliance. The preliminary creation of these nuanced tags eliminates the need for ad-hoc free-form writing.
Data Source
AI summary
Described herein are systems and methods for supplementing and/or replacing free-entered text with tags, which may be phrases and/or individual words. The tags are then associated with an individual, such as a customer, and the association is stored in a database. At least in part because of the association of the tag with a customer, the tags may be required to be pre-approved. Additionally, a representative that entered the text, and to whom the tags are at least initially displayed, may be given the option of deleting the tag and/or identifying replacement tag(s).