Fraud Auditing, Detection, and Prevention Blog

Using Fraud Data Analytics to Build a Fraud Data Profile

Mar 30, 2018 5:21:27 PM / by Leonard W. Vona

When it comes to fraud, no audit plan is going to fit all. Each fraud scenario in your audit scope needs its own fraud data analytics plan and fraud audit procedures. An audit plan isn’t just a document to create and file away as a matter of process – any auditor involved in future detection and prevention will need this to have the correct information that will allow them to find and reveal which fraud scenario is occurring. In short, your fraud audit plan is an essential component in detecting and preventing fraud. 

Once an auditor has a plan and the fraud scenarios at their disposal, the best approach to building a fraud data profile involves using fraud data analytics. For many, this might feel like no more than a buzzword in the industry that adds little value to conversations on fraud but when we talk about fraud data analytics at Fraud Auditing Inc., we mean something very specific, with measurable outcomes, which are essential to any fraud-based approach. 

Here’s a look at the best practices when it comes to data analytics and how it can add real value to your approach.

Fraud Data Analytics Basics

In essence, fraud data analytics is a sampling tool at your disposal to help you or your team finds and identify fraud. To illustrate let’s look at accounts payable.  Most commonly, we’d suggest initially using audit software to gather a sample of vendors consistent with the fraud data profile for an identified fraud scenario.

This occurs after you’d created the fraud data profile – arguably the most important step in any fraud audit – which is a sample of transactions which have the red flags associated with a specific fraud scheme. You will use this sample to perform fraud audit procedures, so it is important to make sure the transactions are discreet and bias. While fraud audit procedures can be highly effective, note that the best procedure in the world is worthless if the fraud data profile doesn’t include at least one fraudulent transaction. 

Fraud Data Analytics Plan Example

As an example of how to determine which data analytics plan to including during your audit, let’s examine a shell company scheme. 

When somebody sets up a false vendor, they may use their own home address to register the legal entity and so their home address will be on the records as the vendor address. This type of fraud could easily be caught by matching vendor addresses with employee addresses, and this informs your data analytics plan. 

In reality, fraudsters maybe more intelligent than using their home address as a vendor address, so a more realistic example would be the employee carrying out fraud using a PO Box in an out-of-state city. Because the employee is using a complex mail forwarding technique the simple matching routine used above is not going to find evidence of fraud in this case. For this, your routine instead needs to interpret patterns of vendor invoices, dates and amounts looking for illogical numbers based on the total dollars or nature of the vendor.


Advanced Techniques

After all of this, the process of fraud data analysis may begin. This is, put in simple terms, the process of extracting and interpreting complex information to identify transactions consistent with a fraud data profile.

The best fraud data analytics is carried out by teams who are highly alert, aware, and can creatively but accurately interpret data. While simple fraud scenarios can be detected via a properly designed a fraud data procedure, in reality fraud is complex. Any complex fraud scenario with a sophisticated concealment strategy requires the ability of your team to see through the concealment strategy and come up with routines that will be able to detect fraud. 

Fraudsters deliberately conceal their activities, and intentionally make data hard to interpret cohesively, so staying one step ahead of fraud scenarios like these can often mean calling in a fraud audit expert. Bringing in an expert is not in any way and indication of lack of effort from your team – rather a chance to increase the effectiveness of your team by recognizing the need for an experienced fraud specialist. At Fraud Auditing Inc. we have decades of experience in the industry. To find out how we can suit your training and consultation needs get in contact with us today

Book Fraud Training for Your Team

Topics: Fraud Data Analytics, Fraud Data Profile

Leonard W. Vona

Written by Leonard W. Vona

Leonard W. Vona has more than 40 years of diversified fraud auditing and forensic accounting experience. His firm, Fraud Auditing, Inc., advises clients in areas of fraud risk assessment, fraud data analytics, fraud auditing, fraud prevention and litigation support.