Control Test Result Summarization for Automated Compliance Audits
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Solution Overview
Problem
Existing systems lack efficient methods for summarizing and evaluating control test results to ensure compliance with organizational policies and security standards, particularly in multi-tenant systems, leading to potential compliance failures and resource wastage.
Innovation Solution
A system utilizing a transformer-based neural network to process structured queries for control tests, analyze supporting information, and generate summaries or reports based on vector representations, enabling efficient evaluation and compliance auditing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual evaluation of control tests is performed, then detailed analysis can be conducted, but time consumption and resource wastage increase significantly
Solution Approach 1:
The patent replaces manual mechanical evaluation processes with an automated system that uses machine learning models and natural language processing to evaluate control tests. The system automatically collects evidence, performs analysis, and generates compliance reports, eliminating the need for manual review while maintaining or improving evaluation accuracy.
Solution Approach 2:
The patent introduces an intermediary automated evaluation system that acts as a bridge between control test data and compliance decisions. This intermediary system processes large volumes of control test information, applies evaluation criteria, and produces structured results that can be directly used for compliance auditing, significantly reducing time loss while preserving measurement precision.
2Reliability
If comprehensive control tests are conducted across all controls, then compliance assurance is improved, but system complexity and resource requirements increase
Solution Approach 1:
The patent segments the comprehensive control test evaluation into modular components: control identification, evidence collection, evaluation execution, and report generation. Each module handles specific aspects of the evaluation process independently, reducing overall system complexity while maintaining comprehensive coverage for reliable compliance assurance.
Solution Approach 2:
The patent creates a universal automated evaluation system that can handle multiple control types and compliance requirements through a single platform. The system uses configurable evaluation criteria and adaptable machine learning models that can be applied across different control domains, reducing the need for separate specialized systems while ensuring comprehensive compliance assurance.
3Measurement precision
If detailed evidence collection is performed for each control test, then evaluation accuracy is improved, but data processing volume and resource consumption increase
Solution Approach 1:
The patent performs preliminary actions by pre-collecting and organizing evidence data before formal evaluation begins. The system proactively gathers relevant control evidence, validates its completeness, and structures it for efficient processing during the actual evaluation phase. This preliminary preparation reduces the data processing volume during evaluation while maintaining high evaluation accuracy through thorough evidence collection.
Data Source
AI summary
A system evaluates controls established for an organization. The system efficiently summarizes results of evaluation of controls established for an organization. The system receives description of a set of controls and identifies a set of control tests associated with the set of controls. The system collects a set of supporting information related to the controls. For each supporting information and for each control test, the system evaluates the supporting information with respect to the control test. For each control test, the system summarizes results of evaluating each supporting information applicable to the control test. For each control test group, the system obtains a control test group result by summarizing results of control tests belonging to the control test group. The system summarizes all control test group results to obtain an overall summarization result. The system performs an action based on the overall summarization result.