In September 2016, the SEC imposed an approximately $15 million penalty and disgorgement (in total) against UBS Financial Services Inc. (UBS) as part of a settled action alleging that UBS failed to adequately train its registered representatives. The representatives had sold complex financial products to UBS’s retail investors, many of whom had minimal investment experience and reported modest income and net worth.
The complex financial products at issue were risky, single stock-linked reverse convertible notes (RCNs), which contained embedded derivatives based on underlying stocks. To build its case, the SEC, along with its Enforcement Division’s Complex Financial Instruments Unit, used, for the first time, "big data" analysis tools to identify "platform-wide" sales patterns rather than engage in the more customary investor-by-investor review.
Here, the SEC’s data analytics ultimately led the SEC to conclude that UBS’s training materials were inadequate mainly because such materials did not fully explain the risks associated with the volatility of the underlying stock’s performance and the potential that the stock could close below the specified downside market protection level, or the availability of certain optionality features that could be exercised by the investor after the product’s issuance. The SEC also found that, because of inadequate training, education and supervision, UBS’s registered representatives did not fully comprehend the RCNs’ risks and rewards thereby causing them, in certain instances, to make unsuitable recommendations to individual retail investors. This conduct, the SEC noted, constitutes a fraud or deceit upon the purchaser in the offer or sale of the products in violation of Section 15(b)(4)(E) of the Exchange Act.
The SEC’s settled action against UBS enforces that broker-dealers who market complex and risky investment products to retail investors, particularly those with limited or no investment experience, must adequately train and supervise their sales staff on suitability determinations.