Robo-advisers are here – the pros and cons of using AI in investing

Artificial intelligence (AI) is shaking up^[1] the way we invest our money. Gone are the days when complex tools were reserved for the wealthy or financial institutions.

AI-powered robo-advisers^[2], such as Betterment^[3] and Vanguard^[4] in the US, and finance app Revolut^[5] in Europe, are now democratising investment. These tools are making professional financial insight and portfolio management available to everyone. But although there are plenty of advantages to using robo-advisers, there are downsides too.

Since the 1990s, AI’s role^[6] in this sector was typically confined to algorithmic trading and quantitative strategies. These rely on advanced mathematical models to predict stock market movements and trade at lightning speed, far exceeding the capabilities of human traders.

But that laid the groundwork for more advanced applications. And AI has now evolved^[7] to handle data analysis, predict trends and personalise investment strategies. Unlike traditional investment tools, robo-advisers are more accessible^[8], making them ideal for a new generation of investors.

A survey published in 2023 showed that there has been a particular surge^[9] in young people using robo-advisers. Some 31% of gen Zs (born after 2000) and 20% of millennials (born between 1980 and 2000) are using robo-advisers.

Another survey^[10] from 2022 found that 63% of US consumers were open to using a robo-adviser to manage their investments. In fact, projections indicate that assets managed by robo-advisers will reach US$1.8 trillion^[11] (£1.4 trillion) globally in 2024.

This trend reflects not only changing investor preferences but also how the financial industry is adapting to technology.

Tailored advice

AI can tailor^[12] investment advice to a person’s preferences. For example, for investors who want to prioritise ethical investing in environmental, social and governance stocks, AI can tailor a strategy without the need to pay for a financial adviser.

AI can analyse^[13] news and social media to understand market trends and predict potential movements, offering insights into potential market movements. Portfolios built by robo-advisers may also be more resilient during market downturns^[14], effectively managing risk and protecting investments.

Robo-advisers can offer certain features^[15] like reduced investment account minimums and lower fees, which make services more accessible than in the past. Other features such as tax-loss harvesting^[16], a strategy of selling assets at a loss to reduce taxes, and periodic rebalancing^[17], which involves adjusting the proportions of different types of investments, make professional investment advice accessible to a wider audience.

These types of innovations are particularly beneficial for people in underserved communities or with limited financial resources. This has the potential^[18] to improve financial literacy through empowering people to make better financial decisions.

AI’s multifaced role

AI’s impact on investment fund management goes way beyond robo-advisers, however. Fund managers are using AI algorithms in a variety of ways.

In terms of data analysis, AI can sift through vast amounts of market data and historical trends to identify ideal assets^[19] and adjust portfolios in real time as markets fluctuate. AI is also used to improve risk management^[20] by analysing complex data and making sophisticated decisions.

By using AI in this way, traders^[21] can react and make faster decisions, which maximises efficiency. Other mundane tasks like compliance monitoring^[22] are increasingly automated by AI. This frees fund managers up to focus on more strategic decisions.

What are the disadvantages?

One of the biggest concerns regarding AI in this sector is based on how having easy access to advanced investment tools may lead some people to overestimate their abilities and take too many financial risks. The sophisticated algorithms used by robo-investors can be opaque, which makes it difficult^[24] for some investors to fully understand the potential risks involved.

Another concern is how the evolution of robo-advisers has outpaced the implementation of laws and regulations^[25]. That could expose investors to financial risks and a lack of legal protection. This is an issue yet to be adequately addressed by financial authorities.

Looking ahead, the future of investment probably lies in a hybrid model. Combining the precision and efficiency of AI with the experience and oversight of human investors is vital.

Ensuring that information is accessible and transparent will be crucial for fostering^[26] a more informed and responsible investment landscape. By harnessing the power of AI responsibly, we can create a financial future that benefits everyone.

References

1. ^{^} shaking up (www.ft.com)
2. ^{^} robo-advisers (www.investopedia.com)
3. ^{^} Betterment (www.betterment.com)
4. ^{^} Vanguard (investor.vanguard.com)
5. ^{^} Revolut (www.revolut.com)
6. ^{^} AI’s role (arxiv.org)
7. ^{^} evolved (www.weforum.org)
8. ^{^} accessible (www2.deloitte.com)
9. ^{^} surge (www.investopedia.com)
10. ^{^} survey (www.magnifymoney.com)
11. ^{^} US$1.8 trillion (www.statista.com)
12. ^{^} tailor (www.ftadviser.com)
13. ^{^} analyse (www.sciencedirect.com)
14. ^{^} more resilient during market downturns (onlinelibrary.wiley.com)
15. ^{^} features (www.ft.com)
16. ^{^} tax-loss harvesting (corporatefinanceinstitute.com)
17. ^{^} periodic rebalancing (corporatefinanceinstitute.com)
18. ^{^} potential (www.brookings.edu)
19. ^{^} ideal assets (doi.org)
20. ^{^} improve risk management (www.sciencedirect.com)
21. ^{^} traders (doi.org)
22. ^{^} compliance monitoring (ieeexplore.ieee.org)
23. ^{^} Loch Earn/Shutterstock (www.shutterstock.com)
24. ^{^} difficult (www.lseg.com)
25. ^{^} laws and regulations (fastercapital.com)
26. ^{^} fostering (www.turing.ac.uk)