Securities Industry Commentator by Bill Singer Esq

The FINRA Expungement of A Customer Complaint That Was Not a Complaint Or From A Customer (BrokeAndBroker.com Blog)

Prepared Remarks at SEC Speaks by SEC Chair Gary Gensler

Five Traders Tell Us How to Survive a World of Disrupted Markets By Bloomberg News

Grand Blanc Man and Flint Woman Sentenced in Fraudulent Investment Scheme (DOJ Release)

SEC Awards $100,000 to Whistleblower

Order Determining Whistleblower Award Claim

SEC Awards 30% Bounty to Whistleblower

Order Determining Whistleblower Award Claim 

CFTC Charges Two Men and Their Companies with Commodity Pool Fraud, Other Violations (CFTC Release)

CFTC Charges North Carolina Companies and Their Owners in $1 Million Foreign Currency Fraud and Misappropriation Scheme / Federal Court Issues Restraining Order Against Defendants Freezing Assets and Preserving Records (CFTC Release)

JPMorgan Chase Wins Stunning Victory Against High-Profile Whistleblower

Johnny E Burris, Plaintiff, v. JPMorgan Chase & Company, et al., Defendants (DAZ Order)

Thank you. I'm happy to appear at SEC Speaks for the first time as Chair of the Securities and Exchange Commission.

This event provides great continuing legal education to lawyers, accountants, and other market professionals. It also gives a platform for dozens of the talented and dedicated SEC staff and directors to share some insights about our work.

I'd like to thank the Practising Law Institute for working with our agency on this program, and my colleagues Gurbir Grewal and Renee Jones for co-chairing this event.

As is customary, I will note I'm not speaking on behalf of the Commission or the SEC staff.

Today, I'd like to speak about the uses of digital analytics in finance.

As I wrote while researching these issues at the Massachusetts Institute of Technology,[1] "[f]inancial history is rich with transformative analytical innovations that improve the pricing and allocation of capital and risk." This ranges from Fibonacci's development of present value formulas in the 13th century to the development of the Black-Scholes options pricing model in the 1960s.  

I believe what we're currently witnessing is just as groundbreaking as Fibonacci. Predictive data analytics, including machine learning, are increasingly being adopted in finance - from trading, to asset management, to risk management. Though we're still in the early stages of these developments, I think the transformation we're living through now could be every bit as big as the internet was in the 1990s.

Across our economy, artificial intelligence, predictive data analytics, and its associated insatiable demand for data are shaping and will continue to reshape many parts of our economy. Sometimes, it seems platforms can predict things about us that we don't even know about ourselves.

When we text a friend about a new restaurant, we might see it advertised to us on another platform.

When we order dish soap online, the website might note that people who bought that soap purchased sponges, too.

When we stream music, a platform might start to suggest other albums we'd like, too.

On finance platforms, we've started to see these tools as well. Platforms can tune their marketing and make recommendations to us based on data.  

We might complete a trade, only to learn that other investors who bought that stock also traded a different stock. Robo-advisers suggest particular funds to us based upon automated algorithms, our particular data, and our stated preferences.

Regarding other modern digital platforms - from news outlets to social media sites - there have been debates about whether these companies optimize for our welfare, or a combination of factors that includes their revenues.

While we can learn from those debates, there's something that is distinctive about finance platforms. They have to comply with investor protections through specific duties - things like fiduciary duty, duty of care, duty of loyalty, best execution, and best interest. These legal duties may conflict with such platforms' ability to optimize for their own revenue.

Today, digital platforms, including finance platforms, have new capabilities to tailor products to individual investors, using digital engagement practices (DEPs). These modern features go beyond game-like elements, or what is sometimes called "gamification." They encompass the underlying predictive data analytics, as well as a variety of differential marketing practices, pricing, and behavioral prompts.

While these developments can increase access and choice, they also raise important public policy considerations, including: conflicts of interest, bias, and systemic risks.

Conflicts of Interest

First, I'd like to discuss potential conflicts of interest.

The algorithms that modern technologies rely on have tradeoffs. A platform and the people behind that platform have to decide what they're optimizing for, statistically speaking.

In the case of that online retailer, perhaps the platform's employees are optimizing for revenues, basket size, and margin.

In the case of brokerage apps, robo-advisers, or online investment advisers, when they use certain digital engagement practices, what are they optimizing for?

Are they solely optimizing for our returns as investors?

Or are they also optimizing for other factors, including the revenues of the platforms?

To the extent that revenues are in the mix in their optimization functions, that means from time to time, they're going to issue a prompt that will, statistically speaking, optimize their own returns. Further, based on predictive data analytics, I may get different prompts, suggestions, or visual cues than another investor will.

Therein lies the tension and the potential conflict. What do we do about that tradeoff?

For example, a robo-adviser might steer us to higher-fee or more complex products, even if that isn't in our best interest. As one scholar put it, "rapid advances in artificial intelligence and machine learning may soon necessitate a rethink of liability regimes applicable to robo-advisors."[2]

Moreover, a brokerage app might use DEPs to encourage more trading, because they would receive more payment from those trades. More trading, though, doesn't always lead to higher returns. In fact, the opposite is often true. Or perhaps an app might steer us to high-risk products, options trading, or trading on margin, which may generate more revenue for the platform.

When do these design elements and psychological nudges cross the line and become recommendations?  The answer to that question is important, because that might change the nature of the platform's obligations under the securities laws.

Further, even if certain practices might not meet the current definition of recommendation, I believe they raise a question as to whether there are some appropriate investor protection guardrails to consider, beyond simply the application of anti-fraud rules.

In August, the Commission published a request for public comment on the use of new and emerging technologies by financial industry firms.[3] The comment period just closed.

For example, we received a comment from the University of Miami School of Law's Investor Rights Clinic, which provides pro bono services to investors of modest means in Florida.[4]

The clinic reports "a sharp increase in clients and prospective clients who suffered losses in their accounts with digital platforms that use DEPs."

Their clients, they note, "trust the financial institutions they use and express confusion as to the reason their trusted institution would promote high-risk strategies or approve them for levels of options or margin trading that are not appropriate for them."

In the clinic's view, these business models do "present a conflict of interest between the retail investor's needs and the digital platform's incentive to make money."

I understand that these tools have opened up the capital markets to a whole new group of people. Digital platforms - from the internet, to mobile phones, to apps - have streamlined user interfaces, enhanced the user experience, and brought greater retail participation into our markets. That, in and of itself, brings a lot of good. But the application of digital analytics raises new questions about conflicts of interest that I think we ought to consider as well.

Some of these issues can (and will) be addressed under our existing rule sets, or through updates to those rules. I've asked staff to take a close look at the feedback we received as they make recommendations for the Commission's consideration, both related to brokers and to investment advisers. We're separately looking at the incentives, like payment for order flow, which may drive some of these practices.

Bias

The second policy consideration I'd like to discuss is bias, and how people - regardless of race, color, religion, national origin, sex, age, disability, and other factors - receive fair access and prices in the financial markets.

How can we ensure that new developments in analytics don't instead reinforce societal inequities?

This isn't a new issue. We've seen this a lot in the consumer credit space. During the 1960s, the Civil Rights and women's rights movements demanded action to address the historical biases embedded in credit reporting. The U.S. passed laws to protect equal access in housing, credit reporting, and credit applications.[5]

Today, platforms have an insatiable appetite for a seemingly endless array of data. This raises new questions about what they can do with that data.

For example, one study has shown that people who used iOS software had better credit than people who used Android software.[6]

We have protections in our laws for certain groups of people. What if it turns out that people who used Android software also happened to be women, say, or members of a racial or ethnic minority?

The underlying data used in the analytic models could be based upon data that reflects historical biases, along with underlying features that may be proxies for protected characteristics, like race and gender.[7]

As finance platforms rely on increasingly sophisticated data analytics, I believe that it will be appropriate to safeguard against algorithmically fortifying such biases.

Systemic Risk

The third policy area I'd like to discuss is systemic risk.

When new financial technologies come along, we need to protect for financial stability and resiliency.

I believe that we need to consider how the broad adoption of new forms of digital analytics, and in particular a subset of artificial intelligence called deep learning, might contribute to a future crisis.[8]

For example, these models could encourage herding into certain datasets, providers, or investments, greater concentration of data sources, and interconnectedness.

Such herding, interconnectedness, and concentration can lead to system-wide issues. We saw herding in subprime mortgages before the 2008 financial crisis, in certain stocks during the dot-com bubble, and in the Savings and Loan crisis of the 1980s.

The interconnectedness of many credit rating models deepened the 2008 financial crisis. About a decade ago, Greece's debt crisis triggered similar cases in Portugal, Spain, and elsewhere.

Today's digital analytics, including deep learning, represent a significant change when compared to previous advances in data analytics. They are increasingly complex, non-linear, and hyper-dimensional; they are less explainable. I believe existing regulations are likely to fall short when it comes to the broad adoption of new forms of predictive digital analytics in finance.  

Thus, 2020s data analytics may bring more uniformity and network interconnectedness, or expose gaps in regulations developed in an earlier era. Financial fragility could come from different pathways - perhaps some critical data aggregator, or in particular model designs.

* * *

In conclusion, I believe we live in a transformative time, where artificial intelligence and predictive data analytics are changing many aspects of our economy. We may be at the early stages of these developments in finance, but we're already seeing changes in multiple areas: from trading, to asset management, to risk management and beyond.

I believe that these technologies present the opportunity to expand access and lead to better risk management. The predictive data analytics also raise a number of important challenges: conflicts of interest, bias, and systemic risk.

Thank goodness - that still leaves us humans with a role! All kidding aside, policymakers, technologists, computer scientists, and market participants can come together, engage in robust debate, and tackle a number of important issues that the adoption of predictive data analytics presents. I believe this will allow these technological developments to live up to their great promise. 

Thank you.  

= = = = =

[1] See Gary Gensler and Lily Bailey, "Deep Learning and Financial Stability," available at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3723132#.

[2] See Lee Reiners in Fintech: Law and Regulation, available at https://www.elgaronline.com/view/edcoll/9781788979016/29_chapter16.xhtml.

[3] See https://www.sec.gov/rules/other/2021/34-92766.pdf.

[4] See https://www.sec.gov/comments/s7-10-21/s71021-9316165-260078.pdf.

[5] Gensler and Bailey.

[6] See Tobias Berg, Valentin Burg, Ana Gombović, Manju Puri, On the Rise of FinTechs: Credit Scoring Using Digital Footprints, The Review of Financial Studies, Volume 33, Issue 7, July 2020, Pages 2845-2897, https://doi.org/10.1093/rfs/hhz099.

[7] Gensler and Bailey.

[8] Ibid.

Trading requires constant vigilance and the ability to adapt and profit from disruptions. But what happens when the act of trading itself is disrupted? To get a glimpse of the life of a trader in 2021, Bloomberg Markets asked five reporters-Justina Lee in London, Divya Balji in Toronto, Liz Capo McCormick and Sonali Basak in New York, and Rebecca Choong Wilkins in Hong Kong -- to interview traders. They quizzed them about how they got into the business, what their typical day is like, how their market and investing strategy is changing, and what advice they'd give to budding traders. All are grappling with the Covid‑19 pandemic, the rise of new asset classes and technologies, the unprecedented flood of money from the world's central banks, and the age-old challenge of keeping their emotions in check. The interviews, conducted in late August and early September, have been edited and condensed for clarity.

[G]ray and Holley, who was a pastor at Abundant Life Ministries in Flint, operated Treasure Enterprise, LLC, which fraudulently purported to provide financial planning and asset management services to investors.  Holley and Gray solicited many of the victim investors at financial seminars held at churches throughout Michigan and other states. 

As alleged in the indictment, in order to lure the potential investors, many of whom took their money out of legitimate investments-such as individual retirement accounts (IRAs) and 401(k)s-Holley and Gray promised high, guaranteed returns, and the safe return of an investor's entire principal at the end of the investment period.  The money, however, was not invested and did not earn the profits to pay the guaranteed interest payments.  Instead, Holley and Gray, and others directed by them, simply deposited the victim investor funds into Treasure's bank accounts and then used the money for their personal benefit, for the benefit of Abundant Life Ministries, to make interest and principal payments to earlier investors, and to pay other Treasure employees.

[C]laimant alerted the Commission to an on-going fraud prompting the opening of the investigation, participated in multiple voluntary interviews with Commission staff, and provided numerous documents that assisted the staff in its investigation, saving Commission staff time and resources. There also have been no collections to date in the matter.

Mankad, CTAX Series, and CTAX Partners

The defendants were charged in connection with the CTAX Series 1, LLC commodity pool (CTAX Pool). Mankad and CTAX Series are also charged with making false statements relating to the fraud to the NFA. The CFTC seeks restitution, disgorgement, civil monetary penalties, permanent trading and registration bans, and a permanent injunction against further violations of the Commodity Exchange Act (CEA) and CFTC regulations.

As alleged in the complaint, during the relevant period from approximately July 25, 2014 to approximately March 22, 2019, Mankad and CTAX Series (1) represented to pool participants that only experienced CTAs would trade funds in the CTAX Pool, when in reality Mankad, who was not a CTA and had limited, unsuccessful experience trading futures, engaged in much and eventually all trading in the CTAX Pool; (2) misrepresented and omitted material facts regarding brokerage commissions that would be charged to the CTAX Pool, when in fact Mankad and CTAX Partners misappropriated pool funds by extracting excessive commissions triggered by Mankad's own unauthorized trading; (3) beginning in July 2018, recklessly traded the CTAX Pool's assets in a manner that resulted in a loss of approximately 89 percent of the CTAX Pool's assets, resulting in significant losses to pool participants; (4) concealed those losses from pool participants by intentionally delaying the provision of monthly account statements to pool participants; and (5) falsified emails submitted to the NFA in connection with an NFA audit of CTAX Series and CTAX Partners to make it appear that defendants provided timely account statements to all pool participants. As a result of this conduct, pool participants lost more than $1.9 million, according to the complaint.

Ohanian and Scottsdale Wealth

The order requires Ohanian and Scottsdale Wealth to pay $338,000 in restitution and a $169,000 civil monetary penalty, requires both to cease and desist from any further violations of the CEA or CFTC regulations, as charged, and prohibits both from trading in commodity interests, registering with the CFTC, or engaging in activity requiring such registration for four years. 

Separately, the order finds that, during the relevant period, Ohanian and Scottsdale Wealth intentionally or recklessly omitted material facts from communications with pool participants, including (1) the full extent of Ohanian's relationship with and compensation from Mankad, CTAX Partners, CTAX Series, and another entity Mankad owned; (2) Ohanian's concerns regarding the fees associated with the CTAX Pool; (3) Ohanian's concerns regarding Mankad's reckless trading; and (4) details relating to the CTAX Pool's near-total loss in value beginning in July 2018. Ohanian and Scottsdale Wealth also failed to register as CTAs, which was required given their business of advising pool participants regarding the advisability of trading in futures.

The complaint charges that from approximately March 2018 through the present, Storm Bryant and Elijah Bryant III, individually and through CapitalStorm LLC, Generationblack LLC, and Ncome LLC, have fraudulently solicited, and continue to fraudulently solicit, existing and prospective clients who are not eligible contract participants (ECPs) to engage in retail transactions in off-exchange foreign currency (forex) on a leveraged, margined, or financed basis. The defendants received approximately $1.05 million from approximately 94 clients during the relevant period, all of which the defendants misappropriated. Approximately $50,870 was sent back to clients as purported forex trading "profits" in the nature of a Ponzi scheme.

Capital Storm, Generation Black, and Ncome, without registering with the CFTC as commodity trading advisors (CTA), and Storm and Elijah Bryant, without registering as associated persons of a CTA, respectively, solicited and continue to solicit clients or prospective clients through in-person solicitations as well as social media platforms such as Facebook and Instagram, including a website operated by Storm and Elijah Bryant, to induce non-ECP, retail clients to send the defendants funds.  Storm and Elijah Bryant, both individually and as agents of Capital Storm, Generation Black, and/or Ncome, describes themselves as highly successful forex traders who generate tremendous returns for their clients. When the Bryants successfully induced non-ECP, retail clients to send them funds, the Bryants misappropriated the funds by receiving them or moving them into accounts held by Storm and/or Elijah Bryant in their own names and using the funds to purchase jewelry, rent homes, European travel, and fund the Bryants' personal trading accounts.

Plaintiff Johnny Burris ("Plaintiff") worked as a financial advisor for J.P. Morgan Chase & Co. and J.P. Morgan Securities, LLC (together, "Defendants") until November 2012, when he was terminated. In this action, which was filed in September 2018 (following an array of related proceedings between the parties in other forums), Plaintiff contends that he was fired for complaining about Defendants' efforts to push investors into risky, "bank managed" financial products and then improperly blacklisted from the financial industry, in violation of the whistleblower retaliation provisions of the SarbanesOxley Act of 2002 and the Dodd-Frank Act of 2010. 

The current issues before the Court, however, have nothing to do with whistleblower retaliation. Instead, they arise from Plaintiffs' systematic efforts to destroy electronically stored information ("ESI") from an array of phones, laptops, email accounts, and external storage devices. Plaintiff's evidence-destruction efforts took a variety of forms, including the repeated use of software programs called "BleachBit" and "iShredder," and spanned a period of years, beginning before (but in anticipation of) this litigation and accelerating as the litigation unfolded. Eventually, a court-appointed forensic expert was tasked with investigating the scope of Plaintiff's efforts to destroy ESI, but the day before Plaintiff produced certain devices to the expert, he used wiping software on them, too. Based on this and other conduct, the expert concluded, "to a reasonable degree of scientific certainty, that [Plaintiff] caused Potentially Relevant ESI to be irrevocably lost from his Electronic Media." (Doc. 73-1 at 3.) 

Following the issuance of the expert's report, Defendants filed a motion for terminating sanctions. (Docs. 78 [sealed], 84 [unsealed].) That motion, as well as Plaintiff's motion for leave to belatedly submit certain exhibits in opposition to the sanctions motion (Doc. 92), are now fully briefed and ripe for resolution. For the reasons that follow, Defendants' motion is granted, Plaintiff's motion is denied, and this action is terminated.

Plaintiff does not propose any sanctions in lieu of dismissal, instead arguing that "there is no basis to impose any sanction whatsoever" (Doc. 89 at 1), but the Court would decline to impose lesser sanctions even if Plaintiff had proposed them. An adverse jury instruction or presumption that covers all of the destroyed evidence would have to be so broad that it would, itself, essentially terminate the case. Additionally, the sheer scope of Plaintiff's dishonesty and spoliation efforts-which the Court explicitly finds amounted to bad faith-makes this the rare case where it is impossible to have confidence that Defendants will ever have access to the true facts. Thus, the Court finds that although it did not impose alternative sanctions before dismissal, such sanctions are "not necessary" in this case. Valley Engineers, 158 F.3d at 1057. 

Of course, dismissal will be highly prejudicial to Plaintiff. But Plaintiff already had the opportunity to litigate several of his termination-related claims on the merits, via a two-week FINRA arbitration. This somewhat reduces the prejudice of dismissal. At any rate, because Plaintiff has engaged in such extensive misconduct and deception, without any obvious contrition or awareness of the wrongfulness of his conduct, there is a serious risk that further proceedings will continue to be plagued by a "pattern of deception and discovery abuse [which makes] it impossible for the district court to conduct a trial with any reasonable assurance that the truth would be available." Id. at 1058. 

• Securities Industry Commentator
• Bill Singer