Why AI Won’t Replace Banking Software Yet - Chris Walters (CEO, Finastra)

Are banks actually making money out of AI? I want to go straight to AI because AI is everywhere now.

Well, when you say making money, that would suggest that there's kind of more revenue associated with AI.

I'm not sure that the majority of banks are making incremental revenue from AI.

That said, there are plenty of banks that are using AI.

in their operations or to support their customers to get even better experiences today.

But we're still very early days in terms of AI and its deployment in the banking sector and more broadly across industry.

What about you guys at Finastra? So where are you guys using AI and what you are doing with

AI? Yeah, so we're doing a lot with AI, I'll go as deep as you'd like, but I'd say it falls into two major categories, right? So one is within the business, and then in delivering value to customers is the second category.

And so within the business, there's certain things that we look at more top down, right, where there's so many people that are impacted, and the value associated with streamlining processes and applying AI is quite material.

And I'd say there's a handful of those areas in the company that we're leaning in quite hard and applying AI in quite consistent manners, right? And that would be in customer support and engineering and testing and QA, as well as in our sales processes.

And the other thing that we're doing within our organization, and this is more bottom up where you're looking for individuals to innovate, is putting a lot of tools and training in people's hands.

And we want individuals to experiment with ways to do the work that they do every day, even more effectively.

And so that's kind of within our business, what we're doing.

In terms of within our products or associated with our products, there's a few levels of what we're doing.

One is similar to what many are doing, including our customers, which is around customer support.

And so we'll be launching... across our key growth products, basic chat bots that allow for users to have more timely and very accurate responses to any questions they have about usability within the product.

But that's kind of, I would describe that as level one.

Level two, and this is over the course of the next 12, to 18 months, we have some very, very feature-rich products that have extraordinary amounts of data in them.

And many customers have said it would be very helpful if we could use many of those features, even if I don't fully understand all those features or how to navigate to them.

And so the intent is to provide natural language commands where you could instruct the product what to do versus knowing feature 1500 and how to navigate to it, right? So somebody wants to accomplish something They could just describe it and a similar dynamic with the data, right? So there's a lot of data that flows through our applications and being able to ask or query that data.

And so I described it as the second level of what we're going to do for customers.

And then the third is really powerful, which is, So our business now is primarily focused on the lending and payments operations of banks.

And there are certain activities that are highly repetitive in those lending and banking operations.

And if we can deliver modules that take some of those most time intense activities and make them incredibly simple or much less timely.

It actually helps our customers and drive efficiency in their operations.