Crowdsourcing Fraud Detection to Expose the Next Madoff
A new paper from NERA Economic Consulting’s Marcia Kramer Mayer and Paul Hinton advocate the use of crowdsourcing to prevent future Ponzi schemes.
The magnitude and duration of Bernard Madoff’s Ponzi scheme establish the compelling need to dramatically improve the Security and Exchange Commission (SEC)’s ability to detect financial fraud. Perhaps Wikipedia can help or, more precisely, some of the ideas behind it.
Fraud detection is a tedious task that can involve sifting through large amounts of data seeking a signature pattern of discrepancies. This is where crowdsourcing, the chief concept underlying Wikipedia, may be quite useful. In the context of fraud detection, crowdsourcing entails making the relevant data available online and inviting the public to access it and report suspected irregularities.
This approach has already been used in Britain, where The Guardian newspaper created an online database of 700,000 expense claims by UK members of Parliament for anyone to search; the erroneous and outrageous expenses identified by some 20,000 participants fueled a national scandal.
How could crowdsourcing be used by the SEC? Assessing investment advisor performance claims and reviewing tips are two of the major tasks on Chairman Mary Schapiro’s plate that lend themselves to this approach. The investment community possesses crucial skills and information that could be brought to bear in getting the job done. These private sector resources go far beyond what is available to the SEC and would likely be volunteered in a suitably designed Internet application.
For more see:
Crowdsourcing Fraud Detection: Using Collective Wisdom to Expose the Next Madoff
Kramer and Hinton discuss the paper at the HBR blog.
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