Artificial intelligence has had a major impact on many industries, and banking is no different. Technologies like biometrics, advanced chat and algorithm-driven trading can help solve issues that have plagued bankers for years.
“AI will change banking” has become an industry trope in recent years, with experts predicting how future developments might be used. But there are practical AI-based solutions available right now that not only can, but will almost definitely be utilized to solve major issues that bankers have wrestled with for years.
Security is one of those issues. Despite the billions spent to protect institutions — and the billions paid to buy off attackers — things are only getting worse, with synthetic identity fraud costing banks nearly $50 billion last year. As many as 95% of phony identities go undetected. Biometrics, combined with machine learning, ensures a high level of accuracy with a minimum of false positives or other errors.
According to researchers, the combination is ideal for mobile banking, a top trend for banks right now. One initiative currently making waves, and that will likely give the concept a major boost is Open AI CEO Sam Altman’s Worldcoin project, which seeks, among other things, to increase accessibility of financial transactions to the unbanked. Worldcoin uses eye scans for initial authentication, and the group is offering developers access to its currently proprietary device — presumably to expand its use for other financial organizations.
Another important issue is ensuring that customers get correct financial advice — and AI, done properly, can accomplish that, outshining even top financial advisors. It’s not that advisors aren’t capable; they just don’t have the resources AI can utilize. By scanning customer needs, goals, risk acceptance levels, demographics and dozens of other criteria — along with characteristics, history, market conditions and hundreds of other factors affecting investments — algorithms can provide customers with guidance on the most effective ways to invest their money, providing insight into available investments that will help them achieve their goals. That’s far beyond the capabilities of even the best human advisors.
To accomplish this, AI will utilize causal networks — systems that “think” like humans, making decisions in the same manner a trader would based on intuition, taking into account many specific factors and then stepping back to assess the overall situation. Causal networks have the ability to analyze, answering what-if questions and understanding the answers to those questions in larger contexts — just like a human investor would, except that these networks can do that sort of “thinking” on a large scale.
Causal networks examine large numbers of elements, giving each the appropriate weight or value relative to each other — thus understanding the relationship and interaction between elements, and using that data to understand overall trends and make specific decisions. Such a system could predict the likelihood of events — such as wars, shortages, pandemics, advances in medical research, etc. — and provide customers with advice on how markets will fare under these circumstances.
Another major pain point for banks is customer service. Whether due to the lingering effects of Covid or a general labor shortage, banks are hard up for personnel, both for top-level and customer service positions, resulting in long wait times for responses and assistance — and increasing levels of customer ire. The situation is not expected to improve anytime soon, and it seems that the only solution is for banks to significantly increase pay for service workers — likely an expensive proposition. Another alternative would be further outsourcing of service calls — also hardly an ideal solution, for both banks and customers.
With the rise of ChatGPT and more advanced iterations of chat technology, banks could develop chat algorithms that help better guide customers on many of the most commonly asked questions or deal with common issues, such as problems accessing account information, queries on payments and the like. And for even more advanced applications, banks could utilize services like D-iD, which puts a human “face” on an AI-generated chat. Banks will also increasingly build systems that integrate humans and AI efficiently, transferring queries immediately to humans, and along with them the chat or AI history so the customer does not need to waste time repeating things or reciting their account details, etc.
These pain points — security, investment accuracy and customer service — have been endemic to banking for decades, and have only gotten worse in the digital age. But for digital-caused problems there are digital solutions — and AI-based technology could help banks, finally, save money and develop effective ways to resolve these issues.