New fraud prevention routine to detect false suppliers

Using data mining routines to detect fraud in corporate accounts payable data is a great way for organisations to protect themselves against fraud.

At Rushmore Forensic we have hundreds of data mining routines that can be implemented and we commonly run around 20 to 25 routines for each client.

Recently we added a new routine, which identifies all vendors that have been incorporated by ASIC for less than 2 years. Yes it’s that simple. The idea being that most companies our clients trade with would have been in existence for many years even if they had not been trading with our client directly.

A company that has only been recently created presents a much higher risk profile that the vendor is false. The forensic data mining routine uses the vendors name and ABN number from the Vendor Master File and compares this with the incorporation date from the ASIC website.  Whilst this data mining routine hasn’t detected a clear cut case of fraud to date it has raised some potential conflict of interest and process issues.

Most of Rushmore Forensic’s engagements use custom developed databases, programming and other techniques to analyse corporate data. We have a suite of over 200 data mining and analysis routines. These routines can scan 100% of accounts payable, payroll, exployee expense reimbursement and other applicable data sources.  This type of analysis commonly detects fraud, breaches of company policy and other anomalies. The reviews are regularly conducted for some of Australia’s largest companies.

About Rushmore Forensic

Andrew Firth is a Director of Rushmore Forensic. Andrew Firth specialises at using advanced data mining to detect fraudulent transactions and other improvements in an organisations processes.  He is a forensic accountant based in Sydney.

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