SEC Utilizes Big Data And Statistics To Target Trading Fraud

The Securities and Exchange Commission recently announced its first fraud charges derived from tracking behavior using data analytics of large volumes of investment advisors’ trade allocation detail.  The enforcement target is Welhouse & Associates Inc. and its owner Mark P. Welhouse.

Mr. Welhouse is accused of “cherry-picking”, a practice whereby one improperly allocates option trades that appreciated in value during the course of a trading day to personal and/or business accounts, while allocating those that depreciated in value to client accounts.  The SEC’s Division of Economic and Risk Analysis has been analyzing large volumes of such data to ascertain instances of seemingly disproportionate allocations, which thereby trigger further investigation.  While Mr. Welhouse’s personal trades in an S&P 500 exchange-traded fund named SPY averaged 6.28% first-day returns, his clients lost an average of 5.05% in the first day.

Fraudulent activity such as cherry-picking can often long go undetected.  The SEC’s ability to proactively identify possible perpetrators of fraud using data analytics (as described more fully in this related article) instead of waiting for whistleblower tips or other indicators of fraud will undoubtedly lead to more enforcement activity in this arena.

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