Automated Regulatory Citation Identification System
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Companies in highly-regulated industries face challenges in efficiently identifying and accessing relevant regulatory documents due to the manual and time-consuming process of tracking changes across multiple sources, which is prone to errors and inefficiencies.
Innovation Solution
A system and method that utilizes scraping, pattern recognition, and document processing to automatically identify and highlight relevant regulatory citations within enforcement documents, allowing for rapid access and navigation through a user interface that connects citations to regulatory requirements and mandates, even for image-based documents.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual tracking of regulatory documents is performed, then legal advisors can identify regulatory citations, but the process is time-consuming and error-prone
Solution Approach 1:
The patent replaces the manual mechanical process of reading and analyzing regulatory documents with an automated optical character recognition (OCR) system and machine learning-based classification system. The OCR engine converts images of documents into searchable text, and the classification system automatically identifies and categorizes regulatory citations, eliminating the need for manual tracking while improving both speed and accuracy.
Solution Approach 2:
The system enables self-service by allowing legal advisors to upload regulatory documents without manual processing. The automated system independently performs OCR scanning, text extraction, classification, and citation identification, freeing legal advisors from the time-consuming manual tracking task while maintaining high identification accuracy through machine learning algorithms.
2Loss of information
If regulatory documents are densely packed with information, then comprehensive regulatory coverage is achieved, but identifying relevant portions becomes difficult
Solution Approach 1:
The patent extracts only the relevant portions of densely packed regulatory documents by using classification systems to identify and isolate specific regulatory citations. The system separates relevant citation information from the rest of the document content, presenting only the extracted relevant portions to legal advisors, thus maintaining comprehensive regulatory coverage while dramatically improving ease of access.
Solution Approach 2:
The system segments regulatory documents into distinct classified categories based on regulatory topics and citations. By dividing the dense document content into organized segments with clear classifications, the system makes it easy for legal advisors to navigate and access specific relevant portions without being overwhelmed by the complete dense information.
3Reliability
If multiple sources of regulatory documents are tracked, then comprehensive monitoring is achieved, but the complexity of managing these sources increases
Solution Approach 1:
The patent implements a universal multi-functional system that can process regulatory documents from multiple different sources through a single integrated platform. The OCR engine and classification system are designed to handle various document formats and sources uniformly, eliminating the need for separate management processes for each source while maintaining comprehensive monitoring coverage.
Solution Approach 2:
The system merges multiple regulatory document sources into a single unified processing pipeline. By combining the OCR scanning, text extraction, and classification functions into one integrated system that handles all sources simultaneously, the patent reduces the complexity of managing multiple sources while maintaining complete and reliable monitoring of all regulatory documents.
Data Source
AI summary
Disclosed herein are system, method, and computer program product embodiments for rapid identification and access to relevant regulatory documents. A data model relating regulatory mandates and requirements to citations appearing within an enforcement document is used to rapidly access specific citations within an enforcement document. In the case of image-based enforcement documents, the originality of these documents is preserved while allowing a user to see where the relevant citations appear in the document images.