Compliance Analysis Using LLM Chunk Similarity Mapping
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Solution Overview
Problem
Large companies face challenges in identifying and addressing compliance gaps across multiple jurisdictions due to complex and lengthy laws, which are difficult to map to their policies, leading to inefficiencies and increased costs.
Innovation Solution
A system utilizing large language models (LLMs) to transform laws and policies into data, compare relevant sections, and identify gaps through similarity analysis, vectorization, and threshold-based scoring to present compliance risks and recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual analysis of compliance laws and policies is used, then accuracy in identifying compliance gaps can be maintained, but time consumption and cost increase significantly
Solution Approach 1:
The patent replaces manual mechanical analysis with an automated system that uses natural language processing and machine learning algorithms to compare compliance laws and policies. The system automatically processes text documents, identifies relevant sections, and detects compliance gaps without human intervention, thereby reducing time consumption while maintaining accuracy through sophisticated computational methods.
Solution Approach 2:
The compliance analysis system performs self-service by automatically analyzing its own inputs (laws and policies) to generate compliance assessments. The system uses embedded machine learning models that continuously process and compare documents autonomously, eliminating the need for manual review while maintaining high accuracy through automated decision-making algorithms.
2Reliability
If comprehensive analysis of all laws and policies is performed, then completeness of compliance coverage is improved, but complexity and cost of the analysis process increase
Solution Approach 1:
The patent extracts only the relevant portions of compliance laws and policies that are actually needed for analysis. The system uses natural language processing to identify and extract key sections, clauses, and requirements from large documents, then focuses the compliance assessment on these extracted elements rather than processing entire documents, thereby reducing complexity while maintaining comprehensive coverage.
Solution Approach 2:
The compliance analysis process is segmented into distinct automated stages: document ingestion, relevant section identification, policy comparison, and gap detection. Each stage handles a specific portion of the overall analysis, breaking down the complex task into manageable computational steps that can be executed systematically without increasing overall complexity.
3Measurement precision
If detailed mapping of laws to policies is performed, then precision in compliance assessment is improved, but manual effort and time required increase
Solution Approach 1:
The patent replaces manual mapping and comparison processes with automated machine learning algorithms that perform precise alignment between laws and policies. The system uses natural language processing to understand semantic relationships, automatically maps relevant sections, and conducts detailed compliance assessments without manual intervention, thereby achieving high precision while eliminating manual effort.
Data Source
AI summary
Various systems and methods for analyzing business compliance are described herein. An electronic online system is configured to receive, from a user of the electronic online system, an indication of a law for analysis; parse the law to produce law chunks; receive, from the user, an indication of a business policy for analysis; parse the business policy to produce policy chunks; compare the law chunks with the policy chunks to determine similarity scores for respective pairs of law chunks and policy chunks; and present law chunks that have similarity scores less than a threshold similarity score to the user.