Today, the Commission is considering a proposal to address conflicts of interest that may emerge when investment advisers and broker-dealers use predictive data analytics or similar techniques to craft their interactions with investors. I believe that, if adopted, these rules would help protect investors from conflicts of interest—and require that, regardless of the technology used, firms meet their obligations not to place their own interests ahead of investors’ interests.

We live in an historic, transformational age with regard to predictive data analytics and the use of artificial intelligence. Such advances open up significant opportunities for humanity, from healthcare to science to finance. As we further automate pattern recognition and parts of human intelligence itself, this can create great efficiencies across the economy.

Today’s predictive data analytics models also provide an increasing ability to make predictions about each of us as individuals. This growing capability facilitates being able to differentially communicate to each of us—and do so efficiently at scale. How might we respond to individualized communications or nudges? How might we respond to individualized product offerings? How might we respond to individualized pricing? This includes means to optimize for, predict, guide, forecast, or direct investors’ investment decisions.

Such analytics and narrowcasting has the potential benefits of greater financial inclusion and enhanced user experience.

This also raises the possibilities that conflicts may arise to the extent that advisers or brokers are optimizing to place their interests ahead of their investors’ interests. If a firm’s optimization function takes the interest of the firm into consideration as well as the interest of the investor, this can lead to conflicts of interest. What’s more, such conflicts could manifest efficiently at scale across brokers’ and advisers’ interactions with their entire investor bases.

Members of the public know some forms of these predictive data analytics well: the flashing button on your screen, the push notification, the colors, the sounds, the well-engineered subtleties of modern digital life.

For instance, the streaming apps’ recommender-models long ago figured out I’m a rom-com guy. But what if finance platforms figured out something else as subtle as some of my color preferences? For instance, my mom used to dress my identical twin brother, Rob, in red, and me in green. Today, I might not react as favorably to green prompts. You see, it was a bit Rob-red, Gary-green, but it was a little overused in my youth.

Ultimately, the math behind these interactions can affect investors. If the robo-adviser or the brokerage app is using a function… yes, that’s math… to optimize for its own interests, and not solely for yours, therein lies a conflict. Regarding the Rob-red, Gary-green example, are firms communicating with me in a color other than green because it’ll be good for my investment decisions, or because it might benefit the firm’s revenues, profits, or other interests?

Right now, advisers and brokers have obligations to act in their investors’ best interests. When offering advice or recommendations, firms are obligated to eliminate or otherwise address any conflicts of interest and not put their own interests ahead of their investors’ interests.

Similarly, I believe that investors deserve to be protected from predictive data analytics-driven interactions—whether it’s Rob-red, Gary-green, or beyond—that result from conflicts of interests, even in instances when those interactions may not amount to providing advice or recommendations. Left unaddressed, I believe that investors exposed to conflicted investor interactions in such instances may lack the time-tested investor protections our laws and regulations provide.

Thus, today’s proposal would require firms to do a number of things.

First, the rules would require firms to analyze conflicts of interest that may emerge when using predictive data analytics to interact with investors. Firms would need to identify any such conflicts that result in an investor interaction that places the firm’s interests ahead of investors’ interests. Firms then would need to eliminate or neutralize the effects of those conflicts. Building on existing legal standards, this rule would help ensure that firms using predictive data analytics to interact with investors meet their obligations not to place their own interests ahead of their investors’ interests.

In addition, the rules would require firms that use this technology for investor interactions to maintain books and records regarding their compliance with these matters.

Today’s proposal addresses one of the four areas the staff recommended the Commission address in the staff’s GameStop report from 2021.[1] Further, we benefitted from public feedback to the Commission’s 2021 request for comment regarding the use of digital engagement practices and similar techniques, including predictive data analytics.[2]

These rules would help protect investors from the conflicts of interest associated with the uses of predictive data analytics.

I’d like to thank the members of the SEC staff who worked on this proposal, including:

• William Birdthistle, Sarah ten Siethoff, Melissa Roverts Harke, Sirimal Mukerjee, Blair Burnett, Michael Schrader, Trevor Tatum, Hae-Sung Lee, and Guang Yang in the Division of Investment Management;
• Haoxiang Zhu, David Saltiel, Andrea Orr, Roni Berghoffen, Emily Westerberg Russell, John Fahey, Devin Ryan, Kelly Shoop, Anand Das, Kyra Grundeman, and Jim Wintering in the Division of Trading and Markets;
• Jessica Wachter, Charles Woodworth, Rebecca Orban, Juan Echeverri, Charles Lin, Lucretia Zinnen, Oliver Richard, Lauren Moore, Michael Davis, Wei Liu, and Daniel Bresler in the Division of Economic and Risk Analysis;
• Meridith Mitchell, Malou Huth, Natalie Shioji, Robert Teply, Robert Bagnall, Joseph Guerra, Maureen Johansen, Ronesha Butler, Dominick Freda, Jeff Berger, and David Lisitza in the Office of the General Counsel;
• Rolaine Bancroft and Benjamin Meeks in the Division of Corporation Finance;
• Mathew Meyerhofer and Heather Marlow in the Division of Enforcement; and
• Natasha Greiner, John Polise, Stephanie Bennett, Micahel Hershaft, Carolyn O’Brien, and Jenn McCarthy in the Division of Examinations.