Fraud Auditing, Detection, and Prevention Blog
Fraud Analytics: Planning considerations
This blog is the first in a series of seven to explain how to perform fraud data analytics. It introduces a ten-step approach along with explaining the concept of fraud auditing.
For years, auditors, myself included, would launch a fraud detection project by getting the data and playing with the data. At least that was the expression. We hoped to trip across a fraud scheme. We had no specific plan, just a simple goal: Find fraud. We did not know what we were looking for, but we were looking. Eventually, we hoped to find something. But, those days are over.
This is part two of a blog post series examining a worked exampled using fraud data analytics on a complex fraud scheme.
In this post we will look at how to use fraud data analytics designed to uncover the complex fraud scheme and the fraud audit procedures designed to provide creditable evidence that the scheme is being perpetrated by the budget owner.
Ghost employee schemes are a common fraud scheme during which there are people on the payroll who don’t work for the company in question but do collect a salary or remuneration.
Let’s take a closer look at how you can use fraud data analytics when creating an executing an audit program for ghost employees:
Shell companies are a common fraud scheme you might come across when carrying out a fraud audit. Let’s take a look at how you can implement fraud data analytics into your audit when approaching shell company schemes in particular as a worked example.