Artificial intelligence has been a hot topic for the last several years, but it became a major area of hype in 2023 with the release of ChatGPT, arguably the first groundbreaking generative AI. As soon as OpenAI made it available to the general public, people
were asking it virtually any question they could think of.
AI is already disrupting many industries, with some people even starting to lose their jobs. In fact, advancements in AI technology are sending ripple effects through large chunks of the job market, including the fintech industry.
After disrupting finance, fintech set for disruption
A recent estimate pegged the AI-in-fintech market at $42.8 billion this year — with a compound annual growth rate of 2.9% through 2028, bringing market revenues
to $49.4 billion. Its full impact on the fintech industry has yet to be realized, although according to one study, 90% of fintech firms
were already using AI technology as of mid-2019.
Of course, it hasn't been that many years since fintech began to greatly the traditional financial industry. Robo-advisors were among the earliest applications of fintech, although new use cases have rapidly spread throughout the traditional financial industry.
Today, new tools constantly being released and offering consumers new and better ways to manage their money, and many of the newest tools are based on artificial intelligence. In fact, many retail investors have already been using AI-based robo-advisors
for several years.
However, the disruptions from AI are sure to accelerate rapidly within the fintech industry, which is young compared to most of the other industries experiencing disruption from AI this year.
The first-fruits of AI in fintech
As fintech startups began to open up their virtual doors over the last several years, much of the technology was already based on AI. At first, the technology helped these startups improve experiences for customers, automate their processes, and analyze
cyberthreats and reduce fraud. However, that was only the beginning.
The earliest use cases of AI in fintech have largely been data-driven because the benefits of automated analysis of massive sets of data were immediately clear. Not only can AI analyze all that data faster and more efficiently, but it does so with few mistakes,
if any. (Of course, there are some important considerations to keep in mind regarding accuracy, which will be discussed below.)
Aside from data analysis, AI is also being used to offer customer service via chatbots around the clock, enabling consumers to get answers to questions when no human representatives are available. As this technology continues to improve, these chatbots should
be able to improve the customer service experience.
Finally, AI technology has now advanced to the point where it can be used to make better decisions about a consumer's creditworthiness based on more than just their credit score. Of course, much more disruption is in store for the fintech industry as AI
technology continues to improve.
Where AI is likely to disrupt fintech next
For example, one of the newer use cases of AI in fintech is in the form of fraud detection, an area that has captured massive amounts of attention in recent months. Banks have long depended on traditional anti-money laundering rules based on monitoring of
transactions and the use of name screening systems.
However, those technologies tend to generate a large number of false positives, creating problems for customers and banks alike. Additionally, fraud is constantly on the rise, with scammers always developing new ways to beat the system and separate victims
from their hard-earned cash.
As a result, AI is starting to play a larger and larger role in fraud detection. Fintech companies are starting to add AI to the existing systems that have long been used by banks to identify new patterns that previously went undetected.
AIs are also helping uncover anomalies in data and even suspicious relationships among people and entities. The result is a more proactive approach to fraud prevention rather than the traditional reactionary approach. While fraud detection is a somewhat
newer application of AI technology, AI is sure to disrupt this part of the fintech industry more and more as the months go on.
The payments business is also ripe for continued disruption. We've already seen significant innovation in this space with the introduction of QR codes that can be scanned to pay. However, AI is likely to continue to drive further disruption in this space.
For example, shoppers at the Amazon Go stores in the U.S. simply scan a QR code when they arrive, grab whatever they want to buy, and then leave, having the payment automatically charged to their account.
Final AI considerations for fintech firms
With the release of ChatGPT, generative AI was suddenly shoved sharply forward, but there are still risks to consider, especially for fintech firms. For example, the financial industry has been highly regulated for a long time, and we have yet to really
see any significant regulations placed on AI technology. We would expect new regulations to be rolled out in the near future.
Accuracy, or rather, the lack of it at times, is also a problem. Currently, generative AI is causing some serious issues by making up stories and inventing false sources for stories. For example, a generative AI caused a huge stir in the fintech community
in early June when "anonymous sources" supposedly told journalists that SEC Chairman Gary Gensler had stepped down amid a pending "internal investigation." However, the AI had simply made that up. Regulating this technology is going to be tricky.
Finally, fintech companies would do well to remember that sometimes there can be no substitute for real human communication and touch. AI chatbots may be able to rattle off lots of information, but they have no human emotions or diplomacy to handle emotionally