A Fundamental Requirement for Ensuring Sound Decision-Making & Effective Control Testing

Internal audit teams in SME’s have more data-driven than earlier. Data quality is often overlooked by the vast amounts of data available for testing controls. End-users assume that the data they are using is free of corruption, errors, or omissions as it is sourced from a database. However, this is not always the case as data integrity errors are frequently detected, sometimes after the delivery of the final audit report. This session we will raise awareness of the multiple possible causes of data issues and how to identify them using automated data analysis techniques that are familiar to auditors. Timely and appropriate detection will allow them to ensure that their decision-making is based on data that has been comprehensively vetted. With the emerging technologies in the Data Analytics software, this session is of particular value to internal auditors at small and medium sized enterprises as they are reliant on data to support their annual audit plan.

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