AI Process Integrity Evaluation for Unstructured Document Workflows

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Solution Overview

Problem

Existing process integrity analysis for unstructured business processes is labor-intensive and relies on intuitive human judgment, leading to inaccuracies and inefficiencies due to the complexity of handling various data formats and unpredictable process steps.

Innovation Solution

A process integrity evaluation system that uses AI techniques, such as entity extraction, relationship reconstruction, and machine learning to automatically verify the integrity of unstructured processes by parsing documents, resolving entity conflicts, and calculating an integrity assurance score based on similarity comparisons across multiple data sources.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If manual auditing methods are used for unstructured processes, then human judgment and knowledge can be applied to evaluate process integrity, but the process becomes labor-intensive, inaccurate, inconsistent and inefficient

Engineering Contradiction:

Improveaccuracy of process integrity evaluationVSAvoidauditing efficiency

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The patent replaces manual mechanical auditing processes with an automated computer-based system that uses natural language processing, machine learning, and data analytics to evaluate unstructured processes. The system automatically parses documents, extracts entities, identifies process steps, and generates integrity assessments without human intervention, thereby eliminating labor-intensive manual work while maintaining or improving accuracy through consistent algorithmic evaluation.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Extent of automation

If automated verification is implemented for structured processes, then information can be automatically verified at different process steps, but unstructured processes require labor-intensive manual review of materials from multiple data sources

Engineering Contradiction:

Improveautomation of process verificationVSAvoidcomplexity of handling various data formats

Core Design Contradiction:

Extent of automationVSDevice complexity

Solution Approach 1:

The patent creates a universal automated system capable of handling multiple data formats and unstructured process types through a single multi-functional platform. The system uses natural language processing and machine learning models that can adapt to different document formats (PDFs, Word documents, emails, spreadsheets) and various unstructured process domains, eliminating the need for separate manual review procedures for each data type while maintaining high automation levels.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The patent introduces an intermediary layer of natural language processing and entity extraction technology that mediates between diverse unstructured data sources and the verification logic. This intermediary automatically parses and standardizes information from multiple data formats into a unified structure, enabling automated verification without requiring manual intervention to handle format complexity.

Inventive Principle:

Principle #24Intermediary (Mediator)

3Reliability

If comprehensive control and auditing are applied to ensure process integrity, then accurate and consistent processes can be maintained, but the auditing process becomes labor-intensive for unstructured data sources

Engineering Contradiction:

Improveconsistency of process informationVSAvoidtime required for auditing

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The patent implements continuous automated monitoring and verification of unstructured processes through real-time data parsing and analysis. The system continuously processes documents and data sources as they become available, maintaining consistent process integrity checks without interruption or manual batch processing, thereby ensuring reliability while minimizing the time loss associated with periodic manual audits.

Inventive Principle:

Principle #20Continuity of useful action

Data Source

PatentUS11574204B2Integrity evaluation of unstructured processes using artificial intelligence (AI) techniques

Publication Date: 2023.02.07 ACCENTURE GLOBAL SOLUTIONS LTD

AI summary

A process integrity evaluation system ensures integrity of unstructured processes. The process integrity evaluation system handles structured, semi-structured, and unstructured data at massive and large scale. The system provides scalability, secure storage, indexing, knowledge storage, and visualizations of processes by information retrieval, natural language processing, cloud computing, large scale machine learning, knowledge discovery, and other artificial intelligence techniques. Self-provided data, systematically gathered data, and potentially related data from additional sources are incorporated in the process integrity evaluation system which provides the core capabilities of data integrity checking, entity extraction, entity resolution, entity categorization, entity relationship extraction, processes extraction and reconstruction based on knowledge storage, such as knowledge graphs, inference functions, and evaluation computations. After extracting and reconstructing unstructured processes successfully, machine learning functions compute an integrity assurance score, e.g., a similarity, between extracted documents and the internal records in addition to an evaluation result, which can ensure the integrity of the unstructured processes.