Business Process Flow Mapping for Missing Audit Evidence
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional business process audits rely heavily on the general ledger (GL) as the primary source of truth, which captures only about 20% of the overall data, leaving 80% untapped for insights, leading to errors, misinterpretations, and inefficiencies in audits due to the corruption or omission of input data.
Innovation Solution
A data-driven business process model (DDBPM) that analyzes a data set to identify common elements, maps process flows, and provides insights into absent or missing elements, using a supradata repository to consolidate and contextualize supporting documentation, enabling a more comprehensive audit.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the general ledger is used as the primary source of truth, then the audit process is simplified and standardized, but 80% of the data remains untapped and errors in the GL cannot be detected
Solution Approach 1:
The system segments the data source into multiple components: the general ledger (20% of data) and supporting documentation (80% of data). By analyzing these segments separately and then integrating their findings, the system preserves the simplicity of GL-based auditing while capturing the additional insights from supporting documents, thereby resolving the contradiction between operational simplicity and information completeness.
Solution Approach 2:
The system merges the general ledger data with supporting documentation analysis results. The GL provides the primary audit trail while supporting documents provide corroborating evidence and additional context. This combination allows auditors to maintain standardized GL-based procedures while simultaneously accessing the full 80%+20% data landscape for error detection and validation.
2Reliability
If auditors manually search for corroborating documents, then they may discover errors, but significant time and cost are wasted searching for evidence that may not exist
Solution Approach 1:
The system performs preliminary analysis of supporting documentation before the manual audit search begins. By pre-processing and indexing documents, extracting key information, and establishing relationships with GL entries in advance, the system prepares the audit trail so that when auditors search for corroborating evidence, they can quickly locate and validate relevant documents rather than manually searching through entire document repositories.
Solution Approach 2:
The system provides feedback to auditors during the search process by automatically identifying which GL entries have supporting documentation and which do not. This feedback mechanism guides auditors directly to relevant evidence or highlights potential errors where documentation is missing, significantly reducing the time spent searching while maintaining high error detection capability.
3Reliability
If the general ledger is corrupted or contains deleted entries, then errors go undetected, but expanding the data source to 80%+20% increases system complexity
Solution Approach 1:
The system introduces an intermediary layer between the general ledger and the supporting documentation. This intermediary automatically correlates GL entries with their supporting documents, manages the relationships between the 20% GL data and 80% supporting data, and handles the complexity of data integration. By placing this intermediary in place, the system achieves high data accuracy through comprehensive validation while shielding users from the underlying system complexity.
4Productivity
If auditors rely solely on the general ledger, then the audit process is efficient, but catastrophic errors may go undetected
Solution Approach 1:
The system implements partial automation where the majority of audit procedures continue to rely on the efficient general ledger-based approach, while additional automated analysis of supporting documentation is applied to specific high-risk areas and GL entries. This partial application of enhanced analysis maintains overall audit efficiency while providing targeted error detection capability where it is most needed, avoiding the need to overhaul the entire audit process.
Data Source
AI summary
A method is disclosed for analysing a data set to determine a first processes. Common elements within the data are identified and associated with the first processes. The common elements are mapped within the first processes to provide an estimated process flow for the first process. Another process is evaluated to determine an absence of one or more common elements common to the estimated process flow. A map is then provided of the process flow indicating events and documents forming the similar processes.