Sample transactions for audit

Your Auditor get paid for their independent opinions on your financial statements and company accounts. This is their job.

Before your Auditor could express their opinions on whether your company accounts and financial statements give a true and fair view of the state of your business affairs, they would have to do their audit first.

It would be unreasonable to expect your Auditor to check every single transaction on your accounting records for accuracy. They can do it if you want them to but that’s going to cost you a lot. You better off hired an in house accountants with past auditing experience to lead your finance department.

Your Auditor sample your business transactions for audit tests based on the level of risks they identified in your business operations. Auditor is prudent in their audit approach because if someone rely on your financial statements based on their opinions and disaster happened and the someone may sue your Auditor. That’s why Auditor can be a pain sometime. Forgive them. They are just doing their job and you pay them for it, is it not?

Audit sampling methods

Your Auditor would have audit objectives to achieve and they would use combination of the following audit sampling methods when come to selecting samples of transactions for audit tests.

All of your business transactions may not be 100% audited but every single transaction has the equal chance of being picked for audit testing.

Haphazard

Simply choosing items subjectively but avoiding bias. Bias might come in by tendency to favour items in a particular location or an accessible file or conversely in picking items because they appear unusual. This method is acceptable for non-statistical sampling but is insufficiently rigorous for statistical sampling.

Simple random

All items in the population have (or are given) a number. Numbers are selected by a means which gives every number an equal chance of being selected. This is done using random number tables or computer or calculator generated random numbers.

Stratified

This means dividing the population into sub populations (strata = layers) and is useful when parts of the population have higher than normal risk such as high value items, overseas debtors. Frequently high value items form a small part of the population and are 100% checked and the remainder are sampled.

Cluster sampling

This is useful when data is maintained in clusters (in groups or bunches) as wage records are kept in weeks or sales invoices in months. The idea is to select a cluster randomly and then to examine all the items in the cluster selected. The problem with this method is that this sample may not be representative.

Random systematic

This method involves making a random start and then taking every item at the determined interval thereafter. This is a commonly use method which saves the work of computing random numbers.

However the sample may not be representative as the population may have some serial properties.

Multi stage sampling

This method is appropriate when data is stored in two or more levels. For example stock in a retail chain of shops. The first stage is to randomly select a sample of shops and the second stage is to randomly select stock items from the chosen shops.

Block sampling

Simply choosing at random one block of items such as all June invoices. This common sampling method has none of the desired characteristics and is not popular or recommended.

Value weighted selection

This method uses the currency unit value rather than the items as the sampling population . It is now very popular and it is also known as Monetary Unit Sampling.