How artificial intelligence is transforming fintech

Traditionally the market for wealth management has catered to those with high net worth. AI solutions are helping to increase this market significantly, being able to scale in such a way that it can be offered to a much broader section of the population. A great example of this is Wealthfront, an artificial intelligence-powered wealth management platform that is significantly cheaper than traditional providers. In addition to offering traditional investment advice, it is able to look at things like spending patterns to make sure that customers have sufficient emergency funds, while also providing constantly updated net worth projections allowing for better retirement planning.

Fraud is an enormous and costly problem in the financial services industry. Identity theft alone cost a staggering $USD56 billion in 2020, with an average loss of $USD1100 per incident. Many fintech companies and traditional financial institutions are now utilizing AI-based solutions for real-time fraud monitoring and prevention, however, there is still much opportunity for improvement as criminals become more sophisticated in their attacks. One startup aiming to eliminate fraud for cryptocurrency exchanges and fintech companies is Sardine.ai, who have created an AI-based fraud protection as a service (FaaS) platform. Sardine has received $USD4.6 million in seed-funding already, and has already demonstrated some impressive results for customers. The platform utilizes a wide variety of data points, along with analyzing minute details of user behaviour in real-time, all while still maintaining a customers privacy.

As with many industries, contracts are a central part of the finance sector. Whether between institutions and customers, or other companies it takes an enormous amount of time to keep track of all of the contracts created. AI is able to help streamline this process using combinations of optical character recognition (OCR), machine learning (ML), and natural language processing (NLP). One significant example of this is the COIN project launched by JP Morgan in 2017. COIN, which stands for Contract Intelligence, was able to perform the equivalent of 360,000 work hours in only seconds.

While it can seem counterintuitive, AI has the potential to make the customer experience much more personalized than ever before. Historically, customers would form a relationship over time with the staff at their local bank branch, who over time would come to know them personally and understand their needs. This particular method of customer service can work well at the local level, but in a world where the younger generations are moving more frequently than ever, it isn't really possible to maintain.

This is an area where AI has been able to fill the void through online chatbots. These chatbots are powered by the enormous amount of data the financial institutions have about individual customers, giving them the ability to provide hyper-personalized assistance 24/7/365. The financial institutions making use of chatbots have good reason to continue doing so and improving them, with global savings from chatbot use expected to top $USD 7 billion by 2023.

AI also has the potential to disrupt the payments industry. Amazon's Go Stores provide a good example: The stores allow customers to scan a QR code in the app as they walk in, take what they want, and leave. The customer never has to stop and scan any items or use any kind of payment kiosk, with the process designed to be as seamless as possible. For this to work, Amazon uses computer vision-based ML algorithms, combined with reinforcement learning (RL) – all driven by the enormous computing power available through Amazon Web Services (AWS). A detailed breakdown of the fascinating process can be found here.

While the uses outlined above show some of the ways in which technology is transforming the financial sector, the use of AI is not without risks. Two of these risks that are worth mentioning are:

Examples such as the JP Morgan COIN program mentioned earlier show the enormous efficiency potential offered through AI-powered automation. But what happens to the jobs of those doing the work previously? Dana Deasy, JP Morgan's CIO in 2017, was quoted at the time saying that it freed employees to work on "higher-values things", however, it will remain to be seen how this type of automation will affect the security of many jobs.

While AI has the ability to calculate risk to lenders, quickly and at huge scale, there is still the risk of bias when it comes to providing finance to consumers. A 2019 study of millions of mortgage and mortgage refinancing applications demonstrated that there was a racial bias still present in both in-person and algorithmic-driven outcomes.

These risks aside, there is little doubt that AI is only going to play a bigger role in fintech in the coming years. Customers can now access the financial information they want and need, at their convenience, while providers are able to benefit from the significant cost reductions that AI-powered automation provides. Even better, the improved layers of security that AI offers benefit everyone, and will only improve as the technology matures.