Digital Data Analysis to Find Fraud


In some ways, it seems like fraud has gotten easier in the age of the internet. People can hack into databases and get access to information they never could have gotten unless they traveled somewhere and physically broken into a building. Electronic banking and the ease of purchasing things on the internet also make it seem as though fraud is easier to commit.

In some ways, it may be easier to initiate a fraud. For example, it previously required someone’s signature on a check to get money out of a bank account. Now, with a push of a button, someone can initiate an electronic transfer to get money out of a bank account. In companies with poor internal controls, it may be incredibly easy to facilitate a fraud this way

Technology has changed the way fraud is committed, but it has also created “paper trails” that often make it easier to detect and investigate a fraud. Every digital transaction leaves behind a trail of digital evidence, which a fraudster may not necessarily be able to dissociate himself from. Commercially available software has made it possible for companies to analyze a huge amount of data in a very short period of time, increasing the chances that unusual activity will be detected quickly.

Software that analyzes accounting data can offer companies two key advantages in monitoring their systems and detecting fraud. One option is performing tests at various intervals on data sets from the company’s accounting system to detect anomalies or indicators of fraud. The software is designed to detect some of the most common signs of errors and irregularities, and companies can use the software on some or all of their transactions on a planned or surprise basis.

The second option is to use software to continuously monitor a company’s accounting systems. The software can help management detect control problems as they are occurring, and also help potential frauds to be identified almost in real time.

Some of the things that software might identify as problems include:

  • Unusually high number of transactions just below a certain level of authority for a supervisor
  • High number of manual disbursements
  • Frequently occurring transactions in large, round dollar amounts
  • Unusual patterns for write-offs or adjustments
  • Evidence of payment of duplicate invoices
  • Recurring instances of partial payments by customers
  • Identification of suspicious addresses when comparing data on employees, customers, and vendors
  • Vendor billings in excess of budgeted amounts due to improper coding of payments
  • Vendor price increases at a rate exceeding the rates of similar vendors
  • Changing purchasing patterns that suggest favoring a particular vendor, which may not be in line with management’s approved purchasing plan

The real advantage to data analysis with computer software is the ability to examine large data sets in a short period of time. Depending on the software used, there will be limitations, so analyzing the data digitally will not be foolproof. There can be cases in which a fraudulent payment to a vendor does not have any red flags that cause the software to identify it as irregular. There can also be problems with flagged items, in which tens of thousands of records are identified as irregular based on the software’s criteria, and someone has to manually examine each one.

Digital data analysis is only one step in finding fraud. Once the system flags transactions as irregular, someone has to analyze them to determine if there is evidence of fraud, or if the items identified are explained and supported by legitimate documentation. Digital data analysis is a tool used to find problems and enhance fraud investigations, but it is not a substitute for good investigative work.

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