PrecisionLender CEO, Carl Ryden, recently sat down with Jim Young, Director of Communications, on the Purposeful Banker podcast to talk about artificial intelligence and machine learning, topics that are front and center at PrecisionLender.

You can listen to part one of their conversation here, but we’re also pulling out excerpts from the transcript and modifying them into blog posts. Last month we asked, “Is Bank Data Ready for AI?”

Today’s topic:

The Digital Divide: Which Side Is Your Bank On?

(Note: While there are definitional differences between artificial intelligence and machine learning, for the purposes of simplicity, we’ll only use the term “AI” in this excerpt.)

Jim: One of the recent AI articles that was shared around the office is titled, “Artificial Intelligence Is the New Digital Divide,” by Enrique Don, professor at the IE Business School in Madrid. Don writes that, going forward, there will be the haves and the have nots; you either are on the side of the divide that gets and understands artificial intelligence and machine learning and know how to unlock it, or you get left behind.

So let’s turn this to banks. Are they in danger of being on the wrong side of that divide? Are some already there?

Carl:  That’s the rub. How do you know, and how do you put yourself on the right side?

Selling the World’s Most Fungible Asset

I think there are two camps on this. One is, and we see this a lot in what we do, there’s kind of the “back of the bank” camp. They really see what they do, maybe not consciously, but at least through their actions, as a commodity business. That their job is to reduce cost and improve efficiency. There is an aspect of that in everything you do, but you can also take that to the extreme – where you destroy any chance of creating value. It’s truly a cost-plus commodity business.

I’m of the belief that in banking, that’s not a place you can be; where you are selling the world’s most fungible asset. Your money is just as green as every other bank’s. If you sell the world’s most fungible asset in a cost-plus commodity business, it takes you down a path that’s really a hard place to be.

The other camp says, “We’re not going to be a commodity business. We’re going to be in the value-creation business. We’re going to be in a value-minus, not a cost-plus.”

So you take a different approach, with the idea being, “How do we create a system that creates more value for our customers?” That way there is more value to share in.

And what does this have to do with AI? Everything.

Amplify Humanity, Don’t Replace It

The first camp, when they see AI, they say, “We’re going to replace humans. We’re going to take them out of the loop. We’re going to decrease cost, increase efficiency, take it down a commodity path.” Don’t get me wrong, there’s a lot of cost and waste that can be taken out, but that can’t be your sole focus.

The second camp says, “Okay, we’re going to use AI to enhance the customer experience, to create value for our customers, to create more valuable interactions with our customers.”

Our philosophy has always been to do everything that a computer can do well, well, so that – and the important part is that “so that” – humans can do everything humans do uniquely well. Remember, the machines are still stupid, they just have more data to train on, right? We’re a long way away from, you know, sentience and those things. Even the experts in the field will tell you that.

When you take that second approach, AI becomes a means of amplifying humanity, not replacing it. Meaning, amplifying humanity by removing all the stuff that computers can do better than humans, like mere calculation or prediction. What matters are the things humans do well, like judgment, empathy and connecting to another human and understanding his or her needs.

The way we think about it is, “Build systems that amplify humanity, not replace it.” These systems amplify humanity by taking the rudimentary task off the human’s plate. Don’t ask a lender to calculate an ROE in their head, when we can calculate that for them.