Much in the same way older generations don’t like using new technology (i.e. grandparents and Facebook), some industries have responded the same way to the use of artificial intelligence. The banking industry is a prime example. While many CEO and financial leaders agree that using AI is great for automation and creating more innovative ways to cater to their customers, these bankers still harbor some fear about it.
You’d be hard pressed to find a business owner who didn’t feel that using the amount of data they already collect from their customers or clients to make their business relationship easier to maintain, and even grow as more services and product become available for both parties to use, would be a good idea. This is the same thought many banking leaders have, yet they are still too scared to take the leap into relying more on AI. So what gives?
Using Tools Banks Already Have
Of all the industries, the financial one probably knows the most about us individually. Perhaps even more than the medical field (sad, I know). Since the beginning of time, banks have collected large amounts of data from clients to use to their advantage in creating a better experience.
This has allowed banks to automate loan applications, account setup, and more, leaving the client to worry about other things rather than filling out a form from scratch every single time.
How AI Can Help Banks
There are many ways AI can improve services banks already offer and also create more ways for the industry to help clients.
With chatbots, which are exactly what they sound like, banks are able to interact with customers without getting a human involved right off the bat. They system works to find the root of the issue for the person’s call and then directs them to the appropriate representative.
While banks and other businesses have had automated machines perform this task for many years now, chatbots allow them to get rid of the touch-tone process and replace it with an actual voice assistant that can listen and offer options based on what the client says. As this technology advances, natural language processing and generation will make it increasingly difficult for customers to tell whether they are talking to a human or an AI interface.
Using machine learning to spot patterns can also help banks perfect and automate their services and protect clients and investors. AI could spot the anomalies or patterns in transactions which might indicate fraud and money-laundering.
“There is so much [unrealistic] AI hype in the banking industry and the banking execs are understandably confused,” says Zor Gorelov, chief executive and co-founder of Kasisto, a company that sells an AI platform KAI to banks.
“We’re trying to be very realistic and set banks’ expectations around the capabilities of the system. One of the things we do right away is we say, ‘our work system must have contextual connectivity to a person’… because nobody can hand over, and probably for the foreseeable future they will not be able to hand over, 100 per cent of their process to AI.”
The Fear of AI
AI and machine learning have a lot to offer the banking industry, so why are these leaders so afraid of implementing them?
A lot of this fear comes from the fact that many people think implementing more technology into everyday procedures will take jobs away from humans and cause layoffs across the board. Yes, some of this tech could do some jobs that are already being done by people, but they could also require more jobs in IT, engineering, and other segments that support technology.
Many refer back to the automation of factories after Y2K as an example of what could happen in finance if AI is implemented. That’s simply not true, though. “If you want to know what happened to manufacturing after 2000, the answer is very clearly not automation, it’s China,” says Dean Baker, an economist at the Center for Economic and Policy Research. “We’ve been running massive trade deficits, driven mainly by manufacturing, and we’ve seen a precipitous plunge in the number of manufacturing jobs. To say those two things aren’t correlated is nuts.”
As more banks choose to use AI for certain tasks and see the benefits of the moves they’re making – J.P. Morgan is using AI algorithms to execute trades, Citi is tapping machine learning to handle pricing requests sent to traders, and others are jumping on board everyday – we will hopefully see some great progress in the implementation of this technology in the industry.