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Tech-Driven Analysis for Enhanced Investment Decisionsby@devinpartida
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Tech-Driven Analysis for Enhanced Investment Decisions

by Devin PartidaMay 14th, 2024
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Investing is a complicated field. Anything impacting people’s money needs a high level of accuracy, but predicting the future of a market with so many influencing factors is anything but easy. That perfect storm of complexities makes it ripe for tech disruption. Informed investment decisions need information — today, that means digital data. Consequently, technologies like AI and automation that unlock data’s full potential could be game-changers in the investing space. Here’s a closer look at some of the tech making waves in this area.
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Investing is a complicated field. Anything impacting people’s money needs a high level of accuracy, but predicting the future of a market with so many influencing factors is anything but easy. That perfect storm of complexities makes it ripe for tech disruption.


Informed investment decisions need information — today, that means digital data. Consequently, technologies like AI and automation that unlock data’s full potential could be game-changers in the investing space. Here’s a closer look at some of the tech making waves in this area.

AI Risk Assessment

AI-driven risk assessments are some of the most valuable tech use cases. Investing — whether in the stock market, property or anything else — is inherently risky. More than 70% of individual investors lose money instead of making more because it’s hard to weigh risks accurately, but AI is much better at this kind of analysis than humans.


Machine learning algorithms can pick up on subtle trends people may miss and factor in years of historical data to accurately predict how an investment may perform. They can then compare this to an investor’s profile to determine how risky it is for that particular person.


Even more importantly, AI can perform this analysis in seconds, whereas it may take a human hours — if not days — of research. That way, people can make decisions based on the most up-to-date data and act before the market changes again.

Personalized Recommendations

Similarly, data analytics can tailor recommendations to individual investors. This goes beyond determining if a potential investment is too risky. AI can also compare options to find which stocks or properties benefit each person’s needs and goals most.


What makes an investment ideal for one person may be different for another. Differing budgets aside, some investors may need something in their portfolio to make it stronger. One may be more interested in selling stocks to make money, while someone else looks at investments as a retirement vehicle. AI can account for these differences and bring the hyper-personalization people expect in social media to investing.


This personalization is becoming increasingly important, too — 66% of high-net-worth investors want more tailored advice from their wealth management partners. As investing becomes more accessible, this trend will also help people with lower net worths get into the field safely.

Robo-Advisors

As these analytics technologies become more reliable, they’re going beyond mere recommendations. Robo-advisors automate the investment process, automatically investing money or selling stocks based on investors’ unique goals.


From an investor’s standpoint, the process is essentially the same as using a managed investment account. Unlike human advisors, though, robo-advisors can use AI to make accurate, complex predictions in minimal time. Consequently, they can act faster to capitalize on changing market conditions at the perfect moment.


Robo-advisors may also make investing more accessible. Total fees for these bots average around 0.37% — significantly less than a human financial planner usually charges.

Remaining Challenges

Given these benefits, it’s little surprise that 61% of investors today think faster AI adoption is important. Still, some obstacles could hinder this technology’s growth.

AI Hallucinations

One of the biggest challenges facing this tech transformation is AI’s reliability. As accurate as machine learning can be, it can still get things wrong and hallucinate. In investment, that can affect financial outcomes and limit investor confidence, which isn’t good for investors or the companies offering these services.


Of course, humans can get things wrong, too. But it’s easier to recognize that and see who’s to blame if things do go poorly. Responsibility isn’t as clear with AI, and stories about its accuracy mean people may trust it too much. This technology will get more reliable over time, but for now, this grey area holds it back.

The use of AI and similar technologies in the financial industry could also lead to legal complications. As you’d expect from anything where other people’s money is at stake, investing faces some stringent regulatory guidelines. While the SEC has proposed a few AI regulations for clarification, it hasn’t finalized anything yet, which could cause some enterprises to remain cautious about new tech.


There are also privacy regulations to consider. Personalization is great, but it requires a lot of personal information. Consequently, this technology could put people’s privacy at risk or introduce complications under data laws, which are becoming increasingly common. The industry may have to wait for legislation to catch up to technology before going much further with it.

New Technology Will Revolutionize Investing

Like the stock market, technology moves quickly. It’s still the Wild West in some ways, but it has the potential to disrupt the financial industry thoroughly. Tools like AI and data analytics could make investing safer, faster, more personalized, and more accessible than ever.


The companies making and applying this technology still face some challenges, so this disruption won’t happen overnight. However, businesses will overcome these obstacles with time and research — when they do, investing will be a better practice for everyone involved.