University of Waterloo - 5 th Symposium on Information Systems Assurance Oct , 2007

1 Agenda · Introduction · What’s not covered / What is covered · Approach and Findings · Conclusion

2 What’s not Covered · A discussion of the mathematical underpinnings What is Covered · An evaluation of the paper from a practitioner’s point of view · Using 3 datasets with known fraudulent entries · A practical application from South Africa with demonstrated success · Comments on the paper

3 Approach and Findings · Applied the concepts of second order tests to 3 datasets: –Extended Warranty Insurance company –Wake County Public School System procurement fraud –Journal entry training data · Results and conclusions of each

4 Extended Warranty Insurance Co. Fraud

5 Wake County Public School System - N Carolina - Procurement Fraud

6 Journal Entry Training Data

7 South African Example · “Using Benford’s Law To Predict Data Error and Fraud” – Dr, Adrian Saville, Chief Investment Officer, Cannon Asset Managers [ · Used Benford’s Law to predict the failure of several listed companies in SA based upon publicly available data · “ First, the tool has been used in a dumb and live environment with great success. By way of example, the tool identified Nedbank’s financials as failing a first order test of Benford’s law. Nedbank went on to report a series of investments that needed to restated and also had to go to shareholders for recapitalization. The implication for investors was costly. Further, the tool we employ identified two of South Africa’s large gold miners – JCI and Randgold – as producing questionable results and so steered us away from these companies as investment candidates.”

8 Conclusion · When looking at the second order test results alone it is not immediately evident that fraud exists in the first two datasets · More research and guidance is needed to aid the practitioner · There is no doubt that Benford Analysis is useful and is providing competitive advantage to many organizations