While artificial intelligence (AI) has been a focus of the tech industry for years, the term "generative AI" pulled this technology into the spotlight this year. Suddenly, virtually every company is trying to mention AI in any commentary investors are likely to read or hear, and investors are sending the stocks of such companies skyrocketing.
Of course, many fintech companies have been using AI for years, but this year it has become important for companies to talk up those efforts to draw attention to themselves. However, for investors, it's important to weed out the companies that are truly using AI to make themselves and their offerings better from those that are merely using AI as a buzzword to draw Wall Street's attention.
The biggest winners in terms of investing in AI will be those who hold out for only the most cutting-edge applications of the technology — rather than those who invest wholesale in every company that even mentions the words "AI" or "artificial intelligence" in their communications.
Additionally, one of the best places to see artificial intelligence in action is in the fintech industry, where many companies have already been utilizing the technology for many years. In fact,
However, it is this experience in using and developing AI that could put fintech firms ahead of those in other sectors when it comes to developing the most cutting-edge applications of this technology.
The Earliest Use Cases of AI in Fintech
That same study revealed that 77% of respondents in the financial services industry expected AI to become of "high or very high overall importance" for their businesses within two years. Now four years later, we're seeing a variety of different applications of AI in fintech, and new applications of this technology continue to explode.
For example, AI has enabled personalized financial advisors for many investors who otherwise couldn't afford a human advisor.
Talk of robo-advisors was all the rage just a few years ago, but now, this AI-based technology has become virtually commonplace.
Other areas in which AI has already become a key piece of the puzzle are fraud detection, algorithmic trading, data analysis, and improved accuracy and productivity.
The Future of AI in Fintech
While many of those areas of fintech have already mastered the use of AI, new applications are constantly being developed and discovered. Here are some of the most promising use cases of AI in fintech, many of which remain open to those with truly innovative solutions to problems in these spaces.
For example, financial reporting is one area that's ripe for improvement. Every publicly traded company must put out regular reports on their financial results, which essentially requires sifting through loads of data and then turning it into informative reports for investors.
Of course, AI speeds up data analysis and enables companies to produce these reports faster and more efficiently. AI algorithms can enable companies to spot trends and patterns that otherwise might be overlooked. Natural language processing can automate data extraction from financial documents, preventing the need for manually sifting through numerous documents and avoiding human error while saving time.
Some fintech starts are also using AI to analyze the creditworthiness of potential borrowers. Traditionally, this was done by reviewing someone's credit report, but today, there is far more information available that can help with making decisions.
In fact, fintech startups that have utilized AI in this way are uncovering potential borrowers who don't have established much credit but do have other signs of being able to repay loans, like a steady job with a steady paycheck. AI can also help speed up the decision-making process for lenders by analyzing multiple data sources in record time.
Of course, the vast amounts of data generated by financial services companies create endless opportunities for innovation in AI.
Is This the Next Big Area of Innovation in Fintech?
With the explosion in AI research and capabilities, the race is on for the next big thing. In the financial sector, including fintech companies, one area that could become a goldmine for those with the foresight and know-how to apply AI to common problems is in regulations. The financial sector is among the most highly regulated industries in the U.S., and compliance has been a real problem for many decades.
For example, machine learning models could be developed to improve company transparency and accountability. Such models could also be designed to predict the impacts of new or changing regulations, both on an individual company and on the financial sector as a whole.
Ultimately, AI could prove to offer significant potential or peril for companies, the industry, and even regulators. Of course, the greatest opportunities will be available to whoever envisions the future and designs it first.
Investing in the Future of Fintech
At the end of the day, readers of HackerNoon know that it's virtually impossible to predict the specifics of what the most cutting-edge fintech startups will do with AI technology next. While anyone can make broad predictions about where the technology will go next, specific use cases that are truly cutting-edge will seem to come from nowhere.
Of course, the easiest and most obvious way to invest in cutting-edge AI and fintech companies is by buying their stocks. However, given that I'm focusing on the most cutting-edge AI technologies, the ideal situation would be to get in before the IPO. Thus, venture capital is one of the earliest places to invest in AI-focused fintech technologies, but unfortunately for some, you have to be an accredited investor to buy into the venture-capital stage.
Ultimately, investors who can identify the truly extraordinary technology that's ahead of its time and get in on the ground floor are likely to do well. After all, those who invested in Google at the time of its initial public offering in 2004 and continued to hold those shares have seen their investment climb well over 4,000%, and that doesn't even take into account pre-IPO gains.