Home > Publications > Crowdsourcing Fraud Detection: Using Collective Wisdom to Expose the N...

NERA PUBLICATIONS




Download >

RELATED EXPERTS:
Dr. Marcia Kramer Mayer

Crowdsourcing Fraud Detection: Using Collective Wisdom to Expose the Next Madoff

9 August 2010
By Dr. Marcia Kramer Mayer et al.

The magnitude and duration of Bernard Madoff's Ponzi scheme establish the compelling need to dramatically improve the Securities and Exchange Commission (SEC)'s ability to detect financial fraud. This note, published in the Harvard Business Review blog, The Conversation, suggests that crowdsourcing can help.
 
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. The authors argue that crowdsourcing could be used by the SEC to assess investment advisor performance claims and review tips, which are two of the major tasks on Chairman Mary Schapiro's plate that lend themselves to this approach.
 
The authors invite you to post comments to the HBR blog. The full version of the note can be downloaded via the link on the left-hand side of this page.