Most financial firms believe artificial intelligence will have a huge impact on their own business and the overall industry in the next few years. If that’s so, investment and integration need to begin fairly soon. And the reality is, most banks are far from doing so.
Below are five charts that show the current state of AI in U.S. financial institutions; what banks’ AI plans are; and why they’ve been slow to move on them, despite the hype.
In a Celent survey of banks, the only technologies being used are fraud analysis and risk detection and natural language processing, by 14 percent and 5 percent of respondents, respectively. For all the hype around chatbots, none of the banks have fully deployed one, although 9 percent are running pilots. Celent doesn’t identify which banks participated in the survey but it’s safe to assume those piloting chatbots are among the largest, like Bank of America’s erica as well as Capital One and Chase, who have also reported bot pilots.
Some banks are running pilots with RPA and Natural Language Generation, but most are still just considering different technologies or haven’t made any plans.
Few are investing in AI
Just 9 percent of banks, presumably the same ones that are running pilots and seeing positive results, plan to invest more than 50 percent in AI in the next year than they did in the last one. Another 23 percent of banks indicated they planned to invest more than 25 percent more. Thirty-two percent indicated their investment levels would remain the same, but another 32 percent indicated they’re not investing at all.
“A lot felt it was expensive, a lot of people have a general lack of understanding,” said Stephen Greer, an analyst at Celent and co-author of the AI report. “There’s such a perception and understanding that it will have an impact, but there’s a limited number of institutions doing a lot with it.”
Five percent of banks said they planned to invest less than 25 percent in AI in the coming year than they did in the last.
Expense and security
Fifty-eight percent of banks indicated that AI might be too expensive to implement and deploy. The same percentage listed security as a concern — although 13 percent indicated they weren’t concerned about security at all.
Most striking for Greer was the high percentage (31 percent) of respondents who said ethical considerations weren’t at all a concern. Eliminating bias, abusing AI and displacing people’s jobs all fall under the ethics category — and they’re some of the largest sources of uncertainty for most consumers who don’t work with the technology hands on.
Where does it go?
According to PwC, most firms in banking, capital markets and wealth management say they’ll rely more on human judgment than machine algorithms to inform their biggest decisions.
Further, according to Celent, banks aren’t very optimistic about AI’s applications for their customers. They seem most excited about using it for fraud detection — particularly as fraudulent activity gets more sophisticated.
“I don’t get the sense most of the industry was acutely aware of how [AI] will happen or why it will evolve,” Greer said.
For some AI technologies, it takes time to digest the customer data they need and to have humans teach them how to react appropriately. Over time, the hope is that AI can reduce banks’ cost of serving customers and improve customer interactions. It’s hard to see that in these early stages, when AI is still in the learning stage. However, banks showed they don’t expect AI to handle more than 30 percent of their front or back end operations.