Video Policy Analysis With Risk-Based Storage Segmentation
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Solution Overview
Problem
Video communication content is difficult to manage for compliance with regulatory requirements due to the challenge of applying context and content-aware policies, and the high cost and complexity of long-term storage of large video files.
Innovation Solution
A system that analyzes video content to apply regulatory policies by extracting metadata, classifying the content, and applying appropriate processing steps such as compression and encryption based on risk scales, ensuring compliance and reducing storage costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If video communication content is stored in full resolution and detail for compliance purposes, then regulatory compliance is ensured, but storage costs and system complexity increase significantly
Solution Approach 1:
The patent applies different quality levels to different portions of video content based on their compliance importance. High-risk segments (e.g., those containing sensitive information or policy violations) are stored in full resolution, while low-risk segments are compressed or archived at lower quality, thereby reducing overall storage costs while maintaining compliance for critical content.
Solution Approach 2:
The video communication content is divided into multiple segments based on risk assessment. The system identifies and segments high-risk portions (such as segments containing PII, financial information, or policy violations) and applies different storage and retention policies to each segment, rather than treating all video content uniformly.
2Reliability
If all video communication content is archived in high quality for audit purposes, then data integrity is maintained, but storage infrastructure complexity and costs increase
Solution Approach 1:
The patent implements dynamic retention and quality policies that adjust based on the assessed risk level of video content. High-risk videos maintain high data integrity with minimal compression, while low-risk videos can be archived with greater compression ratios. The system dynamically adjusts storage parameters based on content analysis results, participant roles, and policy requirements.
3Measurement precision
If context-aware policy analysis is applied to all video content, then compliance accuracy is improved, but processing time and computational resources increase
Solution Approach 1:
The patent applies full context-aware policy analysis only to video segments identified as high-risk, while applying lighter or no analysis to low-risk segments. The system performs initial risk assessment on all content, then applies comprehensive policy analysis selectively to segments that require it, thereby reducing overall processing time while maintaining compliance accuracy for critical content.
4Reliability
If video content is retained for long durations to meet regulatory requirements, then compliance coverage is improved, but storage costs and data management complexity increase
Solution Approach 1:
The patent segments video content and applies different retention durations to different segments based on their risk level and compliance requirements. High-risk segments are retained for the full regulatory-required duration, while low-risk segments may be archived or deleted after shorter periods, reducing overall storage costs while maintaining required compliance coverage.
Data Source
AI summary
The disclosed invention provides methods supporting systems that processes video communication(s) provided by an organization subject to internal or external regulations such as a specific financial services firm or a specific consumer product goods company. In various embodiments, video content is analyzed through a pipeline process of multiple extraction scripts, programs, and/or services and processes the content for participant likeness through facial recognition, voice recognition, and voice-to-text and stores the output in a normalized, searchable data store. A policy analysis is performed based on the stored data and external regulatory compliance, internal rules such as acceptable use policies, community-based regulations, or any combination thereof, to determine a risk score.