Cross-Border Data Transfer Visualization System
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Solution Overview
Problem
There is a growing need for improved systems and methods to manage personal data in compliance with privacy and security policies, as frequent breaches and misuse of personal data have increased, and individuals seek tools to minimize data processing entities and comply with varying global regulations.
Innovation Solution
A computer-implemented method for generating visualizations of data transfers, assessing risks, and determining relative readiness in personal data management, involving data asset identification, risk scoring, and compliance reporting, which includes analyzing data elements, determining relevant regulations, and generating visual representations of data transfers and risk scores.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If organizations implement comprehensive data transfer monitoring and analysis systems to identify risks and ensure regulatory compliance across multiple jurisdictions, then data security and compliance capability are improved, but system complexity and implementation difficulty increase
Solution Approach 1:
The system segments data transfer monitoring into distinct functional modules: data asset identification module, data element analysis module, physical location determination module, regulation identification module, and risk scoring module. Each module handles a specific aspect of the compliance process, making the overall complex system more manageable and maintainable while comprehensively monitoring data transfers across jurisdictions.
Solution Approach 2:
The patent introduces a centralized data processing system that acts as an intermediary between various data assets, communication systems, and regulatory requirements. This intermediary system coordinates the identification, analysis, and compliance verification processes, reducing the complexity burden on individual components while maintaining comprehensive monitoring capability.
2Reliability
If organizations implement comprehensive data transfer monitoring and analysis systems to identify risks and ensure regulatory compliance across multiple jurisdictions, then compliance capability is improved, but implementation difficulty increases
Solution Approach 1:
The system performs preliminary actions by proactively identifying data assets, analyzing data elements, and determining physical locations before data transfers occur. The regulation identification module pre-establishes the regulatory framework for each jurisdiction, enabling the system to automatically assess compliance requirements and generate risk scores without manual intervention during actual data transfers.
Solution Approach 2:
The automated risk scoring mechanism enables the system to self-assess compliance status by automatically comparing identified data transfers against determined regulatory requirements. The system generates its own compliance reports and risk assessments without requiring external manual analysis, reducing implementation difficulty while maintaining high compliance capability.
3Measurement precision
If detailed analysis of data elements and their physical locations is performed to determine regulatory compliance, then measurement precision of compliance assessment is improved, but processing time increases
Solution Approach 1:
The system performs preliminary identification and cataloging of data assets, their physical locations, and applicable regulations before compliance assessment is needed. This pre-processing creates a ready-reference framework that enables rapid, precise compliance evaluation when actual data transfers occur, reducing processing time while maintaining high measurement precision.
Solution Approach 2:
The risk scoring mechanism applies a standardized scoring framework that evaluates the most critical compliance factors with appropriate weightage. Rather than analyzing every possible detail equally, the system focuses computational resources on the most significant compliance determinants, achieving high precision in compliance assessment while minimizing unnecessary processing time.
Data Source
AI summary
In particular embodiments, a Cross-Border Visualization Generation System is configured to: (1) identify one or more data assets associated with a particular entity; (2) analyze the one or more data assets to identify one or more data elements stored in the identified one or more data assets; (3) define a plurality of physical locations and identify, for each of the identified one or more data assets, a respective particular physical location of the plurality of physical locations; (4) analyze the identified one or more data elements to determine one or more data transfers between the one or more data systems in different particular physical locations; (5) determine one or more regulations that relate to the one or more data transfers; and (6) generate a visual representation of the one or more data transfers based at least in part on the one or more regulations.