What can data analytics assist with?
How can data analytics improve audit quality?
Do the results of data analytics still need to be evaluated using the professional skills and judgement of the auditor in order to analyse the results and draw conclusions?
YES
Data analytics: Potential problems
Examples of data analytics routines
Comparing the last time an item was bought with the last time it was sold, for cost/NRV purposes
Inventory ageing and how many days inventory is in stock by item
Receivables and payables ageing and the reduction in overdue debt over time by customer
Analyses of revenue trends split by product or region
Analyses of gross margins and revenues, highlighting items with negative margins
Matches of orders to cash and purchases to payments
‘Can do, did do testing’ of user codes to test whether segregation of duties is appropriate, and whether any inappropriate combinations of users have been involved in processing transactions
Detailed recalculations of depreciation on non-current assets by item
Analysis of capital expenditure vs repairs and maintenance
Three-way matches between purchase/sales orders, goods received/despatched notes and invoices.
Most common data analytics procedures
Risk analysis
Transaction/controls testing
Analytical procedures
Support judgements made
Confirm business insights
Use of Ai in data analytics
Starting point for investigation