Robo-Advisor Updates: Over the years, artificial intelligence (AI) has become more than just a buzzword across different industries. Its assumptions—that machines and/or robots can be scientifically programmed to think and act almost like humans. So that they can continuously learn new things and use that knowledge to solve increasingly complex problems around the world. The prepositions of AI has already been proven and the technology is being adopted in almost all the sectors of development.
Even though many companies have been slow in adopting the AI technology, because of its expensive implementation costs, it didn’t stop it from being accepted. Artificial Intelligence and deep learning are rapidly and already being used in the financial service industry. Financial advisors and RIAs, who have already been buffeted by industry changes, are at great risk of being left out if they ignore this new AI innovation.
KEY POINTS
What is Artificial Intelligence? See details.
- Automation has always been adopted by the financial sector. This technology moves from the original ticker tape to screen-based trading and electronic marketplaces.
- Presently, artificial intelligence (AI) is on the cutting edge of financial services, with machines that can ‘learn new information’ and adapt on their own.
- Almost every AI currently being used now is adopted by big names including Wall Street professionals. But industry analysts predict it will soon make its way to the smaller retail financial advisory space.
- Chatbots, online help with customer support, back-office, and other client services is where AI seems most likely to help. While on the other hand, automated trading platforms like robo-advisors tend to draw on standard investment models rather than AI.
Explanation for the Rise of the Trading Robot
Reports has it that the U.S. has more than $250 billion currently under management by robot. Also, several industry studies forecast that the amount of money managed by robo-advisors will continue to grow at a very quick pace. It has even gotten to a point, where there’re predictions that robo services would drastically reduce or completely eliminate the need for traditional advisors.
Looking at the situation clearly, you’ll notice that the removal of human financial advisor has been greatly over emphasized. But bear in mind that even though robo-advice has disrupted the advice industry, it has by no means replaced human efforts. In short, the AI technology has generally served to enhance the delivery of advising services.
A good example is the Vanguard that is offering; Vanguard Personal Advisor Services. The popular Vanguard’s platform is a combination of robo technology and human advice. They have been widely successful in terms of drawing assets. Furthermore, robo-investing pioneer known as Betterment now offers options where clients can interact with a human advisor. They also made available a platform that allows human advisors to use Betterment’s portal for their own customers.
Robo-advisor and Modern Portfolio Theory (MPT).
From what we know, the Robo-advisor do not use a whole lot of AI in their implementation. The fact is; the majority of them simply automate portfolio strategies. These arrangements fits with some version of modern portfolio theory (MPT). They also build optimized passive indexed portfolios. In addition, MPT can continuously scan and rebalance client portfolios. However, the investment strategy is not informed by any sort of machine learning. Upon that, these big names are looking for better ways to use AI to enhance MPT through strategies like smart beta investing.
The fact remains that where AI is more prevalent is on Wall Street. This is where professional trading desks have put it to use to model the economy and the market. They also use it to predict what will happen in the near future. Another sector is the High-frequency trading (HFT) desks also use AI to come up with new and novel trading strategies that operate on the scale of milliseconds. Therefore, whenever traders make use of AI in their HFT algorithms, the trading systems adapt on their own. It also goes forward to changing market conditions that occur below the level of human perception. Additionally & in most cases, neither the traders using them nor the software engineers that built these bots actually know what is going on under the backdoor. They don’t even know why the HFT ALGO does what it does!
Artificial Intelligence (AI) for Ordinary Investors – ETFs
If you aren’t a Wall Street trader, you can still find ways to take advantage of AI. You can also access the purported benefits of artificial intelligence in picking stocks or timing the market. It will however not be found through most roboadvisors. On the contrary, several ETFs which means exchange traded funds have sprung up that uses professional AI techniques. From there, they then allow ordinary investors to buy into that strategy through shares in its exchange traded funds.
IMPORTANT UPDATES ABOUT ETFs:
Several ETFs invest in the AI sector (companies involved in developing or using AI). But do not use AI in their portfolio selection process. I will advise that you be careful to note which strategy an ETF is using before buying their services.
“Artificial ETFs” are intelligent ETFs that are chosen and managed by computer programs that follow set rules. They completely analyze funds to find the best performers within the constraints of the given rules. As far back as 2017, many different artificial intelligent ETFs have begun. Presently, they are doing well against the rest of the funds market. To be sincere, the total number of stocks they are able to analyze gives them a better advantage over traditionally-managed intelligent ETFs. That’s the truth.
NASDAQ: AIEQ
There’s one example that explains it. 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. They do this, while exhibiting volatility similar to the overall US market. Going deeper, the model suggests weights based on capital appreciation potential. It also looks at correlation to other included companies, subject to a 10% cap per holding. More importantly, note that while AIEQ relies heavily on its quantitative model, the financial aspect is actively managed, and follows no index.”
For now, it is said to be too early to foretell whether AI-powered funds like AIEQ will beat the broader market over the long-term.
Looking to the Future of AI and Robo-Advisor
Different researches shows that there is much speculation about what the next frontier of AI. We expect to see if it will move out of Wall Street and into the financial advisory industry. The tech gurus believe that the next step is for AI to better facilitate advisors’ relationship management. Consequently, it will deter the opposition to making purely trading decisions. Take an example, where an advisor could use AI during a client meeting to call up specific client information. After that, he can model the performance of potential recommendations. Previously, this type of task would have taken a team of analysts several hours or days.
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 – Robo-Advisor
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 AI and Robo-Advisor
Even though these scenarios may seem futuristic, many of them are already being implemented by industry giants. Not upgrading in technology can pose a huge risk to advisors. Yes, there’s not truth other than that. 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.
In conclusion, 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. Let us summarize by saying AI and other technologies are a tool. That being the case, advisors who wish to continue to prosper will need to continuously stay on top of these technologies. Finally, these advisors have to strategically incorporate them into their practices. What are your views?
