AUD 3.10 - Audit Data Analytics Flashcards
Data analytic techniques that enable auditors to analyze and review both financial and nonfinancial data to discover patterns, relationships, and anomalies during audit
Audit data analytics
ADAs can be used to perform:
Risk assessment procedures, test of controls, substantive procedures, and overall conclusion of the audit
4 broad categories of ADAs:
Descriptive analytics
Diagnostic analytics
Predictive analytics
Prescriptive analytics
Explains what happened or what is happening with data
Descriptive analytics
Utilized when an organization wants to understand the underlying cause of results, essentially why something happened with the data:
Diagnostic analytics
Uses historical data and facts to make predictions, estimations, and assertions about future events
Predictive analytics
Built on predictive analytics and shifts the focus from addressing what will happen to how to make something happen. The most advances and complex category of ADA
Prescriptive analytics
When sourcing data, ensure that it is:
Complete
Accurate
Relevant
Reliable
Audit evidence to be used in ADAs may come from:
Information systems
Data storage functions (database, data mart, data lakes, etc)
Internal and reporting sources
External sources
Two types of data
Structured and unstructured
Organized, has consistent data types and formats and is easily searchable. Can be found in spreadsheets, databases, and information systems.
Structured data
Usually in its original, unmodified form that is not organized. Difficult to sort. Examples are social media posts, transcripts, videos, images.
Unstructured data
Used to test sufficient internal controls related to the informations systems and its functions
General IT control (GITC)
Allows to evaluate relationship between variables. It shows the direction and strength of the relationship.
Regression analysis
How is a regression analysis usually displayed?
Scatter plot