Automated Regulatory Compliance Manual Generation
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Solution Overview
Problem
Current systems for regulatory compliance are inefficient, prone to errors, and unable to dynamically generate relevant data, leading to significant costs and inefficiencies for companies due to the rapid increase in complex regulatory laws in the United States.
Innovation Solution
A system that uses an attribute-based classification system and intelligent taxonomy structure to query users for specific information, parse qualitative data into instructional strings, and automatically generate regulatory compliance information tailored to a company's operations, including a graphical user interface for task management and real-time updates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If current manual regulatory compliance processes are used, then companies can identify relevant regulations, but the process is inefficient, error-prone, and costly
Solution Approach 1:
The patent replaces manual mechanical review processes with an automated natural language processing system that uses machine learning algorithms to analyze regulatory texts and identify applicable requirements, thereby improving both efficiency and reliability simultaneously
Solution Approach 2:
The system enables companies to automatically generate their own compliance assessments by inputting their operational data, which the system then processes through the taxonomy framework to identify relevant regulations without requiring external legal expertise
2Reliability
If comprehensive regulatory analysis is performed manually, then all regulations can be reviewed, but research and transaction costs spiral
Solution Approach 1:
The system extracts only the specific regulatory requirements relevant to each company's operations by comparing company data against the taxonomy framework, eliminating the need to manually review all regulations and significantly reducing research costs while maintaining complete coverage of applicable requirements
Solution Approach 2:
The patent changes the parameter of regulatory analysis from a static manual review process to a dynamic automated system that adapts to different companies' operational parameters, allowing comprehensive analysis at minimal marginal cost
3Stability of the object's composition
If static compliance documentation is used, then initial compliance can be established, but the system cannot respond to ever-changing regulatory landscape
Solution Approach 1:
The patent implements a dynamic system where the regulatory taxonomy and company operational data are continuously updated, allowing the compliance assessment to automatically adapt to new regulations and changing business operations while maintaining a consistent analytical framework
Solution Approach 2:
The system incorporates feedback loops where compliance assessments are continuously monitored and updated based on new regulatory inputs and changes in company operations, ensuring both consistency of the framework and responsiveness to changes
4Adaptability or versatility
If generic compliance systems are deployed, then broad regulatory coverage is achieved, but company-specific tailored compliance information cannot be generated
Solution Approach 1:
The patent segments the regulatory framework into a hierarchical taxonomy structure and divides company operational data into comparable categories, enabling customized compliance assessment for each company while using a standardized analytical approach that manages system complexity
Data Source
AI summary
A system is provided for generating compliance manuals from modularized data and taxonomy-based classifications of regulatory obligations. The system comprises a plurality of databases storing regulatory compliance data and a plurality of processors that process the regulatory compliance data to generate business requirements for complying with regulatory obligations and corresponding compliance information related to the business requirements. A taxonomy engine receives business operating parameters related to a first business and identifies a subset of the business requirements and compliance information related to the business operating parameters of the first business. The taxonomy engine further aggregates the business requirements and the compliance information related to the business operation parameters and generates a compliance manual containing the business requirements and the compliance information for use by the first business.


