On AI, Digital Assets, and the SEC
Last week, U.S. Securities and Exchange Commission Chair Gary Gensler comments on AI-driven predictive data analytics and digital/crypto assets included:
"The Commission recently proposed a new safeguarding rule for investment advisors … [to] help ensure that advisers don’t inappropriately use, abuse, or lose investors’ assets.
“Based upon how crypto trading and lending platforms generally operate, investment advisers cannot rely on them today as qualified custodians.
“To be clear: just because a crypto trading platform claims to be a qualified custodian doesn’t mean that it is.
"When these platforms fail—something we’ve seen time and again—investors’ assets often have become property of the failed company, leaving investors in line at the bankruptcy court."
“Many separately managed accounts are advised in part through the use of predictive data analytics. No, I’m not talking about ChatGPT. I am talking about whether there are conflicts of interest inherent to an advisers’ use of predictive data analytics.
“When an adviser provides advice, in part through the use of predictive data analytics, do those algorithms optimize for the investor’s interests, and place the investor’s interests in front of the adviser’s own interests? Alternatively, are they optimizing in part for the adviser’s interests? I believe this may lead to conflicts relating to how they use predictive data analytics and individually tailored investment engagement."
Note: Predictive analytic models use historical and real-time data to anticipate future price moves in support of millisecond trading.
OUR TAKE
Increased oversight of digital/crypto assets will leverage existing laws, introduce new regulations and continue debates on when a digital asset is a security, a commodity, or a currency.
Predictive data analytics can benefit buyers and sellers - and addressing conflicts will require mediating the influences of many market participants.
Innovative digital asset and artificial intelligence based solutions (e.g. predictive data analytics) will change the financial services landscape - and the pace of these changes will challenge some policy makers.