Graph Visualization for Audit Risk Data Integration
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Solution Overview
Problem
Auditors face inefficiencies and errors in risk-based financial audits due to the need to enter repetitive data across multiple forms, making it difficult to identify and manage risks effectively, which can lead to liability issues.
Innovation Solution
A computer-implemented method for visualizing financial audit risk data by retrieving and mapping data elements from a database, displaying vertices and edges representing financial statement, risk, and control data, and their relationships, allowing for a graphical representation of audit risk data to enhance risk identification and management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If auditors complete audit requirements by filling out multiple independent forms, then all audit documentation requirements are met, but data entry redundancy increases and error propagation risk increases
Solution Approach 1:
The patent merges multiple independent audit forms into a single integrated digital form that collects all necessary audit data in one unified structure. This eliminates the need for auditors to repeatedly enter the same data across multiple separate forms, reducing data entry time while maintaining complete audit documentation through the integrated form's comprehensive data capture.
Solution Approach 2:
The integrated digital form serves multiple audit documentation functions simultaneously - it captures financial statement data, risk assessments, audit procedures, and conclusions all in one universal interface. This multi-functional approach replaces multiple specialized forms while ensuring all audit requirements are met through the form's comprehensive data collection capabilities.
2Reliability
If audit data is spread across multiple independent forms, then comprehensive audit coverage is achieved, but risk identification difficulty increases
Solution Approach 1:
The patent combines data from what would traditionally be spread across multiple independent forms into a single integrated digital form with unified data structure. This consolidation maintains comprehensive audit coverage through the form's complete data capture capabilities while dramatically improving risk identification by presenting all audit data in one accessible location with clear relationships between data elements.
Solution Approach 2:
The integrated digital form acts as an intermediary that organizes and connects audit data elements in a structured manner, using data relationships and visualizations to bridge the gap between comprehensive data collection and easy risk identification. The form's architecture serves as a mediator that preserves audit completeness while enabling efficient risk detection through its organized data presentation.
3Measurement precision
If multiple independent forms are used for audit documentation, then detailed risk assessment is possible, but information integration complexity increases
Solution Approach 1:
The patent merges the functionality of multiple independent audit forms into one integrated digital form that maintains detailed risk assessment capabilities through its structured data fields and validation rules. The integration complexity is reduced by using a unified form architecture with automated data relationships, eliminating the need to manually integrate data across multiple separate forms while preserving precise risk assessment through the form's comprehensive data capture.
4Quantity of substance
If auditors manually enter data across multiple forms, then data can be collected comprehensively, but error propagation risk increases
Solution Approach 1:
The patent combines multiple data collection points into a single integrated digital form that captures all necessary audit data comprehensively in one process. This eliminates error propagation by ensuring data is entered once into a unified structure with automated validation and consistency checks, rather than being manually re-entered across multiple independent forms where errors could occur and propagate.
Data Source
AI summary
Methods, software, and computing devices for displaying a graph visualizing financial audit risk data are disclosed. A database stores data elements storing financial audit data, including financial statement data and risk data. A computing device determines a significance of data elements, and displays a vertex representing each data element with a prominence corresponding to its significance. The database also stores relationships between data elements, and the computing device displays the relationships by displaying an edge linking each two related data elements.