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Audit Sampling with MindBridge Ai Auditor

The fundamental problem addressed by sampling is that it is not feasible to apply auditor judgment and expertise to the entire set of data. Sampling provides an objective basis for the claim that audit findings have “reasonable assurance”, but this assurance comes at the cost of restricting the application of the auditor’s judgment and expertise to just the inputs of the sampling procedure. In the ideal situation, the auditor would examine every transaction; she would come to understand which sorts of transactions represented ordinary business and which sorts of transactions are unusual and deserve closer attention. Although this is not feasible for an auditor, artificial intelligence can be applied to assess every transaction to determine which transactions are most anomalous and in need of auditor attention.

Download this whitepaper to learn how MindBridge Ai Auditor delivers comprehensive analysis that can be used by the auditor at multiple stages of the audit process, and how the auditor can use the analysis provided by Ai Auditor to form an enriched sample set and to identify non-compliant transactions in the sample set.

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