More than 90 percent of FIs will use AI technology by 2024, but banks risk breaking their user experience as they race to embrace AI, says Chris Ward, EVP at PNC Treasury Management. In the latest Digital Banking Tracker, Ward tells PYMNTS why boosting processing power is the key to avoiding AI deployments that don’t deliver. Plus, headlines from BBVA, Chime and Citigroup, and rankings of top providers, inside the Tracker.
The global market for AI and machine learning (ML)-enabled solutions is currently valued at $12 billion, per some recent projections, and set to be worth more than $57 billion by 2021. That growth in value is due, in large part, to financial institutions (FIs), many of which have adopted or developed new AI solutions, products and features to offer their customers more stringent security, intelligent insights and other value-added capabilities.
Some of the largest FIs in the space have even begun to experiment, and experts predict that more than 90 percent of global FIs will have adopted the technology in some capacity by 2024. That’s for good reason, too, according to Chris Ward, executive vice president and head of product management for PNC Treasury Management. He believes the technology could be a game changer for the financial services space and everyone in it.
“At the end of the day, I think this technology is going to be great for the business in the long term,” Ward explained. “I think it’s going to allow us to make faster decisions for customers, it’s going to help increase compliance, and I think it’s also going to create new revenue opportunities and client experiences that we just don’t have today.”
While the technology’s advantages may be appealing, adopting AI isn’t as simple as the snap of a bank executive’s fingers. In a recent interview with PYMNTS, Ward shared his thoughts on the roadblocks standing in the way of widespread AI adoption, as well as his predictions for the technology’s future in the financial services space.
One of the major challenges an FI typically encounters in encouraging adoption of any new technology is convincing its customers to embrace an unfamiliar feature. That doesn’t seem to be a problem in the case of financial services-focused AI, though.
Since so much has already been written and discussed regarding the rise of automation and intelligent technologies, Ward said most of his commercial banking clients are eager to see the impact it can have. In fact, in his experience, AI-powered features — like in-depth, intelligent insights and analysis regarding financial health and activity — are particularly popular among clients.
“Customers probably have more excitement than concerns about it,” Ward noted.
The largest friction points with which FIs must contend are the internal shifts needed to add AI to their offerings.
“I think the biggest challenge is adapting an organization’s talent and infrastructure,” Ward explained. “You need a different skill set to be able to work with AI.”
As such, companies need to collaborate closely with data scientists and other industry experts to anticipate the changes banks will need to make to their own infrastructures to work with the technology. Computer processing power must be increased to ensure their machines are capable of running AI programs and features, for example.
Another challenge is the possible impact that AI development errors can have on a bank’s operations, Ward added. The technology is designed to boost the speed of transactions and decisions, meaning it can also speed up and expand the impact of a mistake.
“You can create a lot of errors in a short period of time,” he warned. “So, you really need the right quality-control processes in place to make sure everything functions in the way it should normally function.”
Despite the adoption hurdles, Ward has faith that AI usage will have an increased impact on the financial services space. There is still a wide variety of use cases that have yet to be fully explored, he noted, and they can all be given an AI and ML boost — like onboarding clients, underwriting and risk management processes for lending, and providing product recommendations for existing clients.
According to Ward, PNC is currently working to more fully understand the technology and the benefits it could offer.
“Short-term, we’re trying to … prove that it works and that we’re comfortable with it,” he noted. “Long-term, it’s about scaling it and being able to apply it at the right places at the right times — and apply it to more and more use cases.”
The development of AI- and ML-enabled solutions is seemingly well under way for financial services providers like PNC, but only time will tell how widespread their adoption will be.
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