The Identification of Ponzi Schemes: Can a Picture Tell a Thousand Frauds?

Abstract

There is voluminous commentary on the origins of the Global Financial Crisis (GFC), international attempts to limit the contagion and the Herculean effort to stop the global economy sliding into a depression. However, in the fast moving world of the GFC, the debate shifted to the search for answers to most challenging question – can we stop this from occurring again? To date, a number of responses have been formulated, including the need for a more holistic approach to regulating the global financial system; more stringent controls on banks and new financial products; and, reform of executive remuneration practices that encourage excessive risk taking. This paper suggests an additional issue in the reform debate warrants consideration. The adequacy and implementation of fraud detection systems in the financial services industry must be addressed. The monthly returns from the largest feeder fund in the US$65billion Ponzi scheme overseen by Bernard L. Madoff are analysed to demonstrate how the performance characteristics of investment schemes can be used as a potential 'red flag' indicator in a broad system of fraud detection. It is argued that performance characteristic analysis is likely to play an important role as one tool within a collection of quantitative and qualitative assessment controls able to identify fraud perpetration in the financial services industry.