Background

Tens of millions of state government financial transactions occur each year. Agencies are required to maintain suitable policies and financial controls to ensure that these transactions are justified and approved.

However, policies, controls and well-trained staff do not guarantee that these transactions will not involve errors or fraud. They just reduce the probability of occurrence.

Our normal testing of controls and transactions during our annual financial audits aims to identify ‘material’ errors. That is, an error that would cause a line item in a financial statement to be materially misstated. So, while our sampling of transactions supports the material accuracy of the financial statements and gives an understanding about the reliability of controls, its purpose is not to specifically test for fraud.

In this audit, we have used data analytics to test for fraud or errors.

Data analytics can be used to search large volumes of transactions and data for unusual items, patterns and events that could indicate fraud. We then further investigate the items or events to identify errors or potential fraud.