- May 30, 2016 at 10:58 am #318109
To confirm completeness of REVENUE which of the following procedure is correct?
i) On a sample basis select some sales invoices and agree back to the GDNs and sales orders.
ii) On a sample basis select some sales orders and follow through to sales invoices and general ledger.May 30, 2016 at 2:58 pm #318158
(ii) is correct. You expect orders to produce revenue, so tracing form orders to invoices will give evidence about the completeness of invoices and revenue.
(ii) if not invoice has been raised, no revenue will have been recorded. Therefore tracing form the invoices that exist will give no evidence of completeness. If the invoice is missing you will never try to trace from it. This test will give evidence that the sale/revenue exists ie it stems from an order and despatch.May 30, 2016 at 3:17 pm #318162
Select a sample of assets from NCA register and agree these to the assets held at client’s premises.
The above procedure is to confirm the existence or comleteness of assets?May 30, 2016 at 8:17 pm #318197
Existence. If the records are not complete, you will never know using this test.
To test completeness you would have to select some physical assets then ensure that they could be found in the NCA records.May 31, 2016 at 7:53 am #318294
Can i perform the following substantive procedures regarding damaged inventory?
i) Cast the schedule of damaged inventory given by the management.
ii) Discuss with management the possible scrap value of these damaged stock.
iii) Review that the damaged inventory is valued at lower of its cost and NRV.
Thanx Sir Ken, you are really helping me. Iam too week in substantive.May 31, 2016 at 5:32 pm #318472
Those are all fine. You should also inspect all inventory looking out for damage in case management’s assessment of it is not complete.
Also, just discussing with management the likely scrap value is rather weak evidence. It would also be good if they had already sold some scrap so that you could inspect the invoices. That is better evidence about scrap values.May 31, 2016 at 7:52 pm #318509
Oooh Thanx alot Sir…
Sir, Can I perform Predictive tests over REVENUE and compare the results with actual results to identify any significant difference.June 1, 2016 at 12:25 am #318523
What do you mean by a ‘predictive test over revenue’?June 1, 2016 at 4:20 am #318535
A test performed by an auditor where he predicts that this year the revenue should b around this amount.
This is done by taking previous revenues as a base.June 1, 2016 at 8:03 am #318560
I don’the quite see on what basis the auditor would make the prediction. It would depend on information given by management so becomes a self-fulfilling prophecy.
You might be talking about an analytical procedure where you compare actual to last year and to budget. Then you seek explanations for discrepancies.
You might also be talking about proofs in total. So if you knew the number of passengers on a bus service last year and this you can estimate revenue.
If figures are in line with expectations then this is substantive evidence. If there are discrepancies then explanations are needed.June 1, 2016 at 8:40 am #318568
Thanx. Yes I am talking about the analytical procedure.
There is a direct correlation between the
the data and the quality
of the expectation derived from the data.
Generally, the more precise an expectation
is for an analytical procedure, the greater
will be the potential reliability of
procedure. The use of
(eg number of
rates, units produced) in developing an
expectation may increase the auditor’s
ability to predict account relationships.
However, the information is subject to data
reliability considerations mentioned aboveJune 1, 2016 at 8:44 am #318569
that was written in technical articles.
so, is my procedure over revenue is correct?
“perform Predictive tests over REVENUE and compare the results with actual results to identify any significant difference”June 1, 2016 at 8:48 am #318571
It could be, but read the first sentence you quoted:
There is a direct correlation between the predictability of the data and the quality of the expectation derived from the data.
My point is that the strength of the evidence based on a predictability test depends on how predictable the data is. Is sales are up and down, all over the place at random, then the test is of hardly any use. If sales are really stable and you know of nothing that should change that, then the evidence would be much stronger.
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