Across economic sectors, AI is the elephant in the room – it is growing by the minute, so ignore it at your own peril. Early adopters have achieved promising results, creating a “bandwagon effect” for others to follow suit.
The impact of AI-based platforms like ChatGPT on business strategies has been revolutionary – helping improve decision-making through data analysis at scale and pattern recognition.
Decision makers find themselves in an ethical quagmire, knowing full well the implications of AI adoption for the employees and the business bottom lines. The situation is no different in the financial sector.
AI adoption in the financial services sector is expected to contribute about $37 billion to the UAE’s economy by 2035. Such statistics largely draw upon the growing traction of AI-based investment platforms, especially since the pandemic outbreak.
For example, Robinhood, a commission-free trading platform, made waves in 2021 after an influx of users. However, in August 2023, despite its first-ever profitable quarter after going public, Robinhood witnessed a shares slump due to a decline in users. Such mixed results necessitate a reanalysis of the strengths and shortcomings of AI-led investing.
The profound promises of AI in the financial sector
Popularly known as “robo-advisors”, AI-based trading platforms and their versions have certainly opened doors for first-time novice investors to enter the financial market. The purportedly “free” services have incentivized myriads of particularly young, inexperienced yet curious investors to sidestep their long-standing hesitancies and take the plunge.
In this regard, AI has democratised the market. The platforms have continued to expand and improve their offerings, building full-stack models.
Such developments hold promise for seasoned investors, too, who are largely relying on conventional tools and technologies to strategize investments. Typically, financial advisors and seasoned investors base their decisions on historic patterns and market performances. Some investors use their knowledge and experience accrued over decades of successive investment cycles to time their strategies and identify when to buy, hold, and sell.
With AI, the data-intense financial markets can be demystified through a mere click. Complex patterns of financial information can be simplified and enumerated on intuitive dashboards to make timely investment decisions.
Also, investors can seamlessly track the performance of a stock against custom KPIs in real time. At a time when securities are volatile and increasingly defying conventional patterns, AI can be a valuable addition to the decision-making process. However, it essentially requires a human-in-the-loop approach to consistently yield desirable outcomes. If anything, that underscores the importance of traditional financial advisors.
AI with, not versus, financial advisors
The financial practice continues to thrive because of the ability of advisors to provide consistent guidance while maintaining a focus on the client’s goals and coaching them to stay the course through turbulent times. Deep understanding and in-depth knowledge have no substitute.
And investment in knowledge continues to provide the best returns across asset classes. That is perhaps why one of the common characteristics of successful investors is their association with financial advisors. Such relationships have only strengthened in the last few years. If the pandemic and the subsequent cycles of “stagflation” taught us anything, it is that people need hand-holding, especially during economic downturns.
In recent years, financial markets have witnessed a host of policy revamps and regulatory changes in response to protracted inflation. Such changes are expected to continue for the foreseeable future, with strong implications for corporate and personal tax, estate and legacy planning, and retirement savings.
That status quo calls for periodic portfolio rebalancing and diversification as per the investor’s personal financial circumstances, such as employment, age, health, and family obligations – something that a long-term financial advisor, well aware of the client’s personal and professional circumstances, can readily perform. That level of personalisation and contextualised guidance eludes AI-based trading platforms, which depend on self-direction from clients.
Most seasoned investors aren’t entirely keen on leaving the fate of their finances to machines. However, they are acutely aware of the AI-based opportunities they could potentially miss out on. That ambivalence has worked in favour of financial advisors who are leveraging AI to further optimise their services.
Some advisory firms have launched proprietary, app-based portals to give clients an intuitive and convenient way to manage portfolios. The deep-learning algorithms in such portals provide financial advisors with timely insights for portfolio allocation and rebalancing. Clients can monitor asset performances and interact with the advisors on the platform while being in the comfort of their homes.
The human-in-the-loop approach to AI adoption in financial services lends itself well to GCC’s exemplary technology absorption. Furthermore, the changing global order has placed regional economies in an advantageous position to strike deals that provide investors with easy access to international financial markets and asset classes. At this juncture, the synergy between AI algorithms and financial advisors could be consequential for wealth creation and preservation.
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