Acca aa s21 Notes

1.2 Test data
Test data
is used to investigate the operations of client programs. The auditor designs 'dummy' data 
that is then processed by the client’s programs. This enables the auditor to check whether or not the 
client’s programs are operating correctly and as expected, and whether or not the various controls 
which were supposed to be present are actually operating. For example what happens if a dispatch is 
entered for a zero quantity or for a non-existing product or for a non-existing customer, or would raise 
the balance on the customer’s account to above the credit limit? Test data is specially chosen data to 
check that the controls are present. There would be some normal error-free items, some unusual 
items and some extreme or unexpected items.
The auditor should predict what the client’s program should do and then compare those predictions 
with what the client’s program actually produces.
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A problem with test data is that the auditor is processing dummy data. Therefore it is usual for test 
data to be run using copies of files (ie 'dead').
Audit programs
Examine client
data
Test data
Tests client 
programs
2. Data analytics
In general terms, data analytics is “the science of examining 
raw
data to draw conclusions”. So an 
obvious audit application is in 
analytical procedures
for risk assessment and as a substantive 
procedure (Chapter 10). 
Commonly used data analytics tools or routines include:
๏
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.
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Analyses of revenue trends split by product or region.
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Analyses of gross margins and sales, highlighting items with negative margins.
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Matches of orders to cash and purchases to payments.
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‘Can do did do testing’ of user codes to test segregation of duties and whether any 
inappropriate combinations of users have been involved in processing transactions.
๏
Detailed recalculations of depreciation on an item-by-item basis using the entire data set and 
exact dates.
๏
Analyses of capital expenditure vs repairs and maintenance.
๏
Three-way matches between purchase/sales orders, goods received/despatched 
documentation and invoices.