Automated Regulatory Change Detection and Policy Impact Analysis
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Solution Overview
Problem
Current systems lack an efficient method for automatically detecting regulatory changes and their impacts across various domains, leading to potential compliance issues and delays in updating policies.
Innovation Solution
A system that monitors publications for regulatory changes, identifies affected topics and objects, and generates alerts based on the likelihood of policy impact, utilizing a processor to analyze comments and build dynamic linkages for cross-domain inference and sentiment analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual monitoring of regulatory publications is used, then detection accuracy can be maintained, but time consumption and labor resources increase significantly
Solution Approach 1:
The patent replaces manual mechanical monitoring with an automated computer-based system that uses natural language processing and machine learning algorithms to detect regulatory changes. The system automatically crawls publications, analyzes text for regulatory changes, and generates alerts without human intervention, thereby maintaining detection accuracy while eliminating time consumption associated with manual monitoring.
Solution Approach 2:
The system enables self-service by automatically performing the entire regulatory monitoring process including publication crawling, change detection, impact analysis, and alert generation. The automated system serves itself by continuously monitoring without requiring external human resources, thus resolving the contradiction between maintaining accuracy and reducing time loss.
2Reliability
If comprehensive analysis of all publications is performed, then detection completeness improves, but system complexity and computational resources increase
Solution Approach 1:
The patent segments the regulatory monitoring process into distinct modular components: publication crawling module, natural language processing module, regulatory change detection module, impact analysis module, and alert generation module. Each module handles a specific aspect of the analysis, allowing comprehensive monitoring while managing system complexity through modular architecture that can be independently configured and maintained.
Solution Approach 2:
The system applies partial action by focusing computational resources on identifying and analyzing only the relevant portions of publications that contain regulatory changes. Rather than processing every word of every publication equally, the system uses natural language processing to identify key sections and concepts, thereby achieving detection completeness while reducing unnecessary computational complexity.
3Productivity
If automated detection systems are implemented, then processing speed increases, but detection precision may deteriorate due to false positives
Solution Approach 1:
The patent implements feedback mechanisms where the system continuously learns from user interactions with generated alerts. When users mark alerts as true positives or false positives, the machine learning model adjusts its parameters to improve future detection accuracy. This feedback loop allows the system to maintain high processing speed while progressively improving detection precision by reducing false positives over time.
Solution Approach 2:
The system performs preliminary action by pre-training machine learning models on large datasets of regulatory publications before deployment. This pre-training establishes a baseline level of detection precision that allows the automated system to operate at high speed from the outset, rather than requiring extensive post-deployment tuning to achieve acceptable accuracy levels.
Data Source
AI summary
An embodiment of the invention provides a method comprising monitoring publications for regulatory changes with a monitoring device, and identifying at least one regulatory change based on the monitoring of the publications. The monitoring device monitors published comments to the identified regulatory change. A processor connected to the monitoring device identifies one or more topics and/or objects in the regulatory change and/or the published comments. An alert generating device connected to the processor generates an alert including one or more policies above a threshold level of likelihood that the policy will be affected by the regulatory change.