When the US Treasury Secretary gets concerned enough about market volatility to call a sit-down with other key officials to further discuss, wealthtech providers should pay close attention. According to coverage from MarketWatch, that’s what happened earlier this month, when Janet Yellen met with officials from the Securities and Exchange Commission as well as the Federal Reserve.
The agenda reportedly focused on market volatility driven by GameStop, AMC and other “meme stocks” that surged in value after retail investors mobilized collectively on the popular online community Reddit to bid up these shares.
With the ongoing surge of self-directed online trading expected to further fuel market volatility, wealth management firms and technology entrepreneurs alike are seeking asset management solutions that can supersede or sidestep human emotions and bias to create better outcomes.
And artificial intelligence-driven, machine learning-based solutions are increasingly viewed as one potential solution.
Aligning AI with Asset Management
Adam Malamed, CEO of Ajax Investment Partners, a Miami-based fintech incubator launched in May last year, is no stranger to the process of identifying technologies that can accelerate growth.
Previously a significant individual shareholder in, and Chief Operating Officer of, Ladenburg Thalmann, the NYSE-traded wealth management firm, Malamed was one of the lead architects of the sale of Ladenburg to Advisor Group in February last year, at an enterprise value of $1.3 billion.
Before this transaction, Malamed was a driving force with the Ladenburg Innovation Lab, which invested in early-stage tech start-ups with solutions that could be adapted for traditional wealth management firms. It’s a strategic vision he has been recreating at Ajax Investment Partners, having already seeded two fintech start-ups with solutions expected to be rolled out in the next 12 months.
“Since the end of January, we’ve been approached by technology entrepreneurs with fairly advanced data sciences platforms that, in theory, could be repurposed for asset management that supports traditional wealth management firms,” said Malamed. “In our recent experience, the GameStop frenzy is significantly fueling interest in using AI to drive better and more consistent investment returns.”
Barriers to Entry?
But persuading large wealth management firms and their financial advisors to adopt AI asset management solutions could be challenging, albeit necessary – Especially because direct-to-consumer approaches could be exponentially more complex and expensive.
Malamed notes, “While AI experts know data science and algorithms inside and out, they frequently need considerable help in customizing their offerings and adapting them to appeal to wealth management firms.”
Third-party asset managers gain trust and market share with wealth management firms when there is a clear track record established over a multi-year period.
In the case of AI-driven asset managers, in addition to investment performance, product platform gatekeepers at wealth management firms will likely also want to see less volatility, together with cost savings that can be passed along to their firms, their financial advisors and their clients.
“There’s considerable promise to AI-driven investing, but it’s going to take time and effort for such asset managers to prove themselves to product platform gatekeepers,” said Malamed.
Moving Beyond Human Bias
The opportunities for aligning with traditional wealth management firms aside, fintech experts generally agree that successfully building an AI asset manager will require access to a deep bench of seasoned data scientists, algorithms that capture the fundamentally dynamic nature of the markets and do so on a scalable basis.
One start-up with a considerable leg up in this regard is San Diego-based AlphaTrAI, an AI-driven asset manager that is one of the portfolio companies of Analytics Ventures, a venture capital firm which boasts an ecosystem of 50 artificial intelligence experts.
AlphaTrAI’s CEO is Andreas Roell, who is also the Managing Partner of Analytics Ventures, and a veteran in spearheading the use of AI to transform traditional ways of doing business across multiple industries.
Teaming up with Roell is former LPL Financial President Bill Dwyer, who is a significant shareholder in AlphaTrAI, and serves as Chairman of the company’s Advisory Council, and as a member of its Board of Directors.
Dwyer, who has been advising AlphaTrAI on its marketing and distribution strategies, is widely credited as one of the leaders of LPL Financial who were instrumental in building the company into one of the largest independent wealth management firms today.
Speaking to the recent meme stocks-related market disruption, Roell emphasizes that “All asset managers, including quantitative, technical, algorithmic, and even human traders, who solely rely on historical events to drive their present investment decisions, were at an absolute loss during this unprecedented event.”
Meanwhile, Roell notes, “We didn’t suffer the steep and dramatic losses that many asset managers experienced related to the GameStop-related trading frenzy.”
The Dynamics of Shifting Market Data
According to Roell, the three elements that position AlphaTrAI to deliver better investor outcomes are the company’s trading models that are geared around prediction and detection based on very small data sets; its ability to operate with models that can identify and comprehend market conditions on a high level; and its algorithms that can “solve the entire problem versus only a portion of it,” with capabilities that determine what to trade, and that can successfully execute the trades.
Roell notes, “The stock market is dynamic, and it is riskier than what the majority of investors think. Investors need asset management solutions that can manage risk as much as possible while making decisions for each brand-new scenario as quickly as possible.”
“Recent events highlight that most funds are based on portfolios designed to deal with frequently observed, small downturns in the market. This approach is necessarily fragile to the large, rare risks, or so-called tail events, that can occur over short to long time horizons,” explained Roell.
“These are the events that matter most when maintaining sustainable performance in the financial markets. We use Machine Learning to leverage information as effectively as possible, and we use this information to construct portfolios that we believe are designed to achieve gains while managing tail events that can be catastrophic for other portfolios.”
Algorithms Unlikely to Fully Replace Humans
But for all the potential of AI-driven asset management, it is extremely unlikely for either asset managers or the wealth management firms they support to have AI completely replace human professionals.
Roell said, “We strongly believe humans need to be part of the algorithmic trading equation, especially when it comes to ‘global shocks’ and with identifying new, lasting opportunities that further enhance the algorithms.”
As an example of the latter, Roell calls out the emergence of new asset types, such as cryptocurrencies, and exploring how they could be added into portfolio models.
Adam Malamed agrees that human professionals will continue to be crucial to the future of wealth management and asset management, saying that speculation today about artificial intelligence completely replacing human investment managers is similar to “hype about robo-advisors replacing human financial advisors from the first half of the last decade.”
“Instead, over the past ten years, experienced financial advisors have proven their value again and again to the end consumer – Including most recently with the pandemic-driven market disruption and economic uncertainty. “
Malamed emphasizes, “There’s a similar parallel to be drawn here with AI-driven and machine learning-enabled asset management, and where it will need to evolve in the future to be relevant for independent broker-dealers, RIA firms and their financial advisors.”