Semantic Data Ingress Tool for Financial Audit Automation

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Solution Overview

Problem

Traditional financial data audits are labor-intensive and costly, requiring significant professional labor to review large datasets, with limited sampling leading to potential missed risks due to inconsistent data formatting and entry across various accounting systems.

Innovation Solution

A data ingress tool that semantically analyzes financial data to detect formats, convert data into a compatible format for analysis tools, and perform necessary data manipulation operations to ensure compatibility, such as grouping entries, generating transaction IDs, and formatting dates and amounts correctly.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If manual data review and formatting is performed by database professionals, then data compatibility with analysis tools is achieved, but significant time and cost are consumed

Engineering Contradiction:

Improvedata compatibilityVSAvoiddata preparation time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system enables self-service by allowing the data analysis tool to automatically detect unknown data formats through semantic analysis and perform the necessary data manipulation operations without requiring manual intervention from database professionals. The tool independently identifies formatting issues, determines appropriate transformations, and executes the conversions to achieve data compatibility.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces the mechanical manual process of data formatting with an automated computational system. The data analysis tool uses semantic analysis algorithms and automatic format detection mechanisms to substitute human database professionals in the data preparation process, significantly reducing time and cost while maintaining compatibility.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Reliability

If manual data formatting is performed by database professionals, then data can be processed by analysis tools, but the process is limited by professional skills and may still be insufficient

Engineering Contradiction:

Improvedata compatibilityVSAvoidmanual processing complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system dynamically changes the operational parameters of data processing by automatically detecting data formats and adapting the analysis approach accordingly. Instead of relying on fixed manual formatting procedures, the system adjusts its data manipulation operations based on the detected format characteristics, overcoming the limitations of skilled professionals.

Inventive Principle:

Principle #35Parameter changes

3Adaptability or versatility

If data is entered by humans across various accounting systems, then diverse data sources can be captured, but data consistency and formatting uniformity deteriorate

Engineering Contradiction:

Improvedata source diversityVSAvoiddata formatting consistency

Core Design Contradiction:

Adaptability or versatilityVSStability of the object's composition

Solution Approach 1:

The patent applies universality by designing a data analysis tool that can handle multiple data formats from diverse accounting systems through a single automated interface. The tool performs semantic analysis that works across different data structures, nomenclatures, and formatting conventions, enabling one system to universally process varied data sources without requiring separate manual formatting procedures for each source.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

Inventive Principle:

Principle #35Parameter changes

4Productivity

If sampling of financial data is used in traditional audits, then review time is reduced, but the ability to identify high-risk transactions is limited

Engineering Contradiction:

Improveaudit speedVSAvoidrisk identification accuracy

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The patent replaces the mechanical sampling approach with an automated data analysis system that processes complete datasets. The tool uses semantic analysis and automatic anomaly detection to evaluate all transactions rather than relying on statistical sampling, thereby maintaining high processing speed while significantly improving the accuracy of risk identification.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS10839163B2Method and apparatus for shaping data using semantic understanding

Publication Date: 2020.11.17 MINDBRIDGE ANALYTICS INC

AI summary

Methods are provided for semantic processing of data files including detecting formats of data embedded in the data files and converting the data to formats compatible with a data analysis tool. The method may comprise semantically analyzing components of the data files to assess formatting across a required set of criterions needed by the data analysis tool and determining sets of data manipulation operations to perform to convert the data file to a compatible format. Semantic analysis of values in criterions across data entries may allow for groups of entries to be associated together with transaction ID values common to and unique to the groups of entries associated with a common transaction. The method may group data entries based on values in criterions, test potential groupings based on a behavior test to assess characteristics of entries when grouped in the proposed manner, and generate a new transaction ID criterion in each of the data entries.