About our data
Where does this data come from?
Public organisations detect the fraud...
Public organisations are responsible for preventing and detecting fraud. They do so largely by maintaining a culture of integrity supported by strong internal controls. When public organisations suspect that fraud might have been committed, they need to protect any evidence they might have and consider the most appropriate next steps – including quickly informing their auditor.
... tell their Appointed Auditor...
In turn, as part of their professional obligations (see auditing standard AG ISA (NZ) 240), the Appointed Auditors are required to tell us.
... and we report it
Because we depend on the information that public organisations provide, we probably won't know the full extent of fraud in the public sector. That said, we see value in sharing what we do know, because that might help public organisations to consider where their risks might lie.
Each year, we will share information on the incidents of fraud that auditors have reported to us. As the data increases, we might see trends or patterns for different types of public organisations, which could also be useful in mitigating risk. We also use the data to help auditors, by identifying risk factors for their audits.
Understanding the data
This set of data begins from July 2012, immediately after our fraud survey was reported in June 2012.
We've grouped data into the broader categories or types of public organisations and summarised:
- the type of fraud;
- the main reasons the fraud was committed; and
- how the fraud was identified.
Because fraud can be complex, one incident could fall into multiple categories.
The types of fraud reported to us
We've tried to name the types of fraud as plainly as possible. If any of these categories need more explanation, please let us know. The types of fraud are:
- theft of cash
- theft of plant or equipment (e.g. computers or personal items)
- theft of inventory
- other thefts (e.g. intellectual property or identity crime)
- fraudulent expense claim
- fraudulent misuse of credit cards or fuel cards
- false invoicing
- payroll fraud
- paying or receiving backhanders or undeclared gifts
- other.
We will review the categories, and add more if need be, as the amount of data increases.
Page last updated: 28 February 2019