Auditing Business Controls Using Analytic Control Tests
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Solution Overview
Problem
Traditional business control auditing methods rely on sampling techniques, which can lead to erroneous conclusions and are costly due to the burden on processing, data storage, and bandwidth in computer-based systems, failing to transparently qualify the extent and impact of issues in business processes.
Innovation Solution
A data-driven auditing framework that performs direct and indirect analytic control tests (ACTs) on business process data to evaluate the operating effectiveness of business controls by calculating error rates and coefficients of variation, comparing these results against established thresholds to determine the integrity and efficiency of business controls.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional sampling techniques are used to audit business controls, then the auditing process is simpler and faster, but the conclusions may be erroneous and do not transparently qualify the extent and impact of issues
Solution Approach 1:
The patent replaces traditional mechanical sampling methods with analytic control tests that process entire populations of data. Instead of mechanically selecting samples, the system performs direct tests on all data records to calculate actual error rates and coefficients of variation, eliminating the uncertainty inherent in sampling while maintaining computational efficiency through algorithmic processing.
Solution Approach 2:
The patent changes the fundamental parameters of audit measurement from sample-based statistical estimates to population-based actual error rate calculations. By transforming the audit approach from sampling to comprehensive analysis, the system achieves precise measurement of control effectiveness without the reliability concerns of sampling methods.
2Reliability
If all data is reviewed using typical auditing techniques, then complete coverage of business controls is achieved, but the cost and processing burden on computer-based systems increases significantly
Solution Approach 1:
The patent replaces resource-intensive manual review processes with automated analytic control tests. The system performs direct and indirect ACTs that algorithmically analyze data patterns, error rates, and coefficients of variation, significantly reducing the processing and storage resources required compared to traditional comprehensive data review methods.
Solution Approach 2:
The system enables self-service auditing by automatically performing control effectiveness tests without requiring extensive manual intervention. The analytic control tests self-evaluate business controls by processing data according to predetermined criteria, reducing the need for human resources and computational overhead while maintaining comprehensive coverage.
3Productivity
If sampling methods are used for auditing, then processing resources are conserved, but sample risks lead to erroneous conclusions and lack of transparent qualification
Solution Approach 1:
The patent replaces sampling-based auditing with direct analytic control tests that process entire data populations. This substitution eliminates sample risks and provides transparent information about the actual extent and impact of control issues through precise calculation of error rates and coefficients of variation across all data records.
Solution Approach 2:
The system performs preliminary analysis by calculating actual error rates and coefficients of variation before drawing conclusions about business control effectiveness. This preliminary computation of comprehensive metrics provides transparent qualification of issues before final audit determinations are made, eliminating the information loss associated with sampling.
Data Source
AI summary
Systems and methods for auditing business controls are disclosed. The system may receive or retrieve data from one or more data sources corresponding to a business control. The system may perform a direct analytic control test (ACT) or an indirect ACT on the data. The system may compare a direct ACT result or an indirect ACT result to an ACT threshold. The ACT threshold may comprise separate direct ACT thresholds and indirect ACT thresholds. Based on the comparison, the system may determine an operating effectiveness of the business control.