Across industries, artificial intelligence (AI) has become more than just a buzzword. Its premise—that machines can be programmed to think and act almost like humans, to continuously learn and to use that knowledge to solve increasingly complex problems - has already been proven and the technology is well on its way to mainstream adoption.

While many companies have been slow to adopt the technology, due in part to steep implementation costs, AI and deep learning are rapidly appearing in the financial service industry. Financial advisors and RIAs, who have already been buffeted by industry changes, are at great risk of being left behind if the forgo this new innovation.

Key Takeaways

  • Technology has always been adopted by the financial sector, from the original ticker tape to screen-based trading and electronic marketplaces.
  • Now, artificial intelligence (AI) is on the cutting edge of financial services, with machines that can 'learn' and adapt on their own.
  • Most of the AI used now is among Wall Street professionals, but industry analysts predict it will soon make its way to the retail financial advisory space.
  • Help with customer support, back-office, and other client services is where AI seems most likely to help, while automated trading platforms like robo-advisors tend to draw on standard investment models rather than AI.

The Rise of the Trading Robot

With more than $250 billion currently under management in the U.S., various industry studies predict that the amount managed by robo-advisors will continue to grow at a torrid pace. At one point, many even predicted that robo services would drastically reduce or eliminate the need for traditional advisors.

Clearly, the demise of the human financial advisor has been greatly overstated. While robo-advice has disrupted the advice industry, it has by no means replaced humans. In fact, the technology has generally served to enhance the delivery of advice.

Take, for example, Vanguard’s offering, Vanguard Personal Advisor Services. Vanguard's platform is a combination of robo technology and human advice and has been widely successful in terms of drawing assets. And robo-investing pioneer Betterment now offers options where clients can interact with a human advisor as well as a platform that allows human advisors to use Betterment's platform for their own clients.

Robo-advisors do not use a whole lot of AI in their implementation so far. In fact, the majority of them simply automate portfolio strategies that fit with some version of modern portfolio theory (MPT) and build optimized passive indexed portfolios. They then continuously scan and rebalance client portfolios but the investment strategy is not informed by any sort of machine learning. Still, these companies are looking for ways to use AI to enhance MPT through strategies like smart beta investing.

Where AI is more prevalent is on Wall Street where professional trading desks have put it to use to model the economy and the market and to predict what will happen in the near-term. High-frequency trading (HFT) desks also use AI to come up with new and novel trading strategies that operate on the scale of milliseconds. When traders use AI in their HFT algorithms, the trading systems adapt on their own to changing market conditions that occur below the level of human perception, and often time neither the traders using them nor the software engineers that built these bots actually know what is going on under the hood or why the HFT algo does what it does!

AI for Ordinary Investors

If you aren't a Wall Street trader, you can still find ways to take advantage of the purported benefits of artificial intelligence in picking stocks or timing the market - but it won't be found through most roboadvisors. Instead, several exchange traded funds (ETFs) have sprung up that use professional AI techniques and then allow ordinary investors to buy into that strategy through shares in its ETF.

Several ETFs invest in the AI sector (companies involved in developing or using AI) but do not use AI in their portfolio selection process. Be careful to note which strategy an ETF is using before buying.

"Artificial ETFs" are intelligent ETFs that are chosen and managed by computer programs that follow set rules and analyze funds to find the best performers within the constraints of the given rules. Since 2017 several different artificial intelligent ETFs have started and they are doing well against the rest of the funds market. The sheer number of stocks they are able to analyze gives them the advantage over traditionally-managed intelligent ETFs.

One example is the "AI Powered ETF" (NASDAQ: AIEQ). From the fund's prospectus, it states: "AIEQ uses artificial intelligence to analyze and identify US stocks believed to have the highest probability of capital appreciation over the next 12 months, while exhibiting volatility similar to the overall US market. The model suggests weights based on capital appreciation potential and correlation to other included companies, subject to a 10% cap per holding. It is worth noting that while AIEQ relies heavily on its quantitative model, the fund is actively managed, and follows no index."

It is too early to tell whether AI-powered funds like AIEQ will beat the broader market over the long-run.

Looking to the Future

There is much speculation about what the next frontier of AI will move out of Wall Street and into the financial advisory industry. Many believe that the next step is for AI to better facilitate advisors' relationship management as opposed to making purely trading decisions. As an example, an advisor could use AI during a client meeting to call up specific client information and model the performance of potential recommendations, a task that previously would have taken a team of analysts several hours or more.

While many of today’s financial planning programs do offer these capabilities, AI's growth will only serve to expand software's analytical and predictive power. This is augmented by AI's deep learning capabilities, which will relieve advisors from having to perform much of the rote or mundane monitoring and administrative tasks that currently occupy a significant portion of their time. For example, an AI-based system could be set-up to monitor client portfolios and send a signal to the advisor when allocations fall outside of certain parameters.

While AI could conceivably eliminate some roles for human advisors or support personnel, AI's analytical capabilities will likely result in the growth of more specialized, interpretive roles as well. The adoption of Artificial Intelligence will free up advisor time for increased client-facing activities: it's unlikely that advisors will ever want to just let their systems spit out data and analysis directly to a client without some review of this output.

Automating Client Service

It's likely that many of your clients' inquiries are questions that could be handled by an AI-driven assistant, guided by parameters that you set. This virtual assistant could perform an analysis of the client’s question and have some suggested alternatives ready for you to review and discuss.

This system could be set so that there is continual analysis of your client’s financial picture, suggesting options as the client’s situation evolves. Perhaps they have a loan that could be refinanced or there has been a recent change in the tax law that would trigger the system to automatically review the impact on all of your clients.

Similarly, if there were a significant change in the management of a mutual fund used in one or more client portfolios, your AI-based assistant could trigger an alert for the advisor to determine whether that fund should be retained or replaced.

Costs of Falling Behind

While these scenarios may seem futuristic, many of them are already being implemented by industry giants. Lagging behind in technology can pose a huge risk to advisors, especially those that are working with the next generation of tech-savvy millennial and Generation X clients. These generations are on track to be the beneficiaries of the largest intergenerational transfer of wealth in history and expect their advisors to work with them on their terms.

While AI and related technologies have not replaced human financial advisors and are unlikely to do so, AI will enhance advisor’s analytical capabilities and automate a number of mundane back-office tasks, reducing costs across the board. AI and other technologies are a tool and advisors who wish to continue to prosper will need to continuously stay on top of these technologies and strategically incorporate them into their practices.