Will a Bank's AI Produce an ROI? 6 Questions to Ask

August 6, 2018 Jim Young

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Lots of banks are talking about their innovation and artificial intelligence initiatives, but will those programs actually affect the bottom line?

In this week's podcast, PrecisionLender CEO Carl Ryden walks through the important questions that bank analysts and investors should be asking, as well as the answers bank leaders should be prepared to give. 

 

   

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Podcast Transcription

Jim Young: Hi, and welcome to The Purposeful Banker. It's a podcast brought to you by PrecisionLender. We discuss the big topics on the minds of today's best bankers. I'm your host, Jim Young, Direct or Communications with PrecisionLender and I'm joined today by PrecisionLender CEO, Carl Ryden.
 
Today we're going to look at the digital innovation movement in commercial banking through the lens of the investor or the analyst. Essentially, we're going to ask Carl to actually sort of play both sides here in a hypothetical earnings call here.
 
First, if you're investing in publicly traded banks, what are some of the questions you're going to ask so that you can really find out what sort of ROI banks are getting on innovation and AI and AI? But also asking you to think about it from the banker's perspective: You're going on this call and you know those analysts want those answers. How are you going to provide those answers?

 

1) What's the bank's innovation lab actually doing?

Jim Young: So, let's start off with innovation labs. Some of our clients have these. A lot of banks have them now. If you are an analyst and you get on a call with a bank and they proudly talk about how they started this new innovation lab and that sort of thing. What is you really want to know about that?
 
Carl Ryden: Well I'll start with the analysts. I know a lot of them. Worked with some of them over the years that went on to be analysts and talked to quite a few of them back in my days at Bain and other places. I can tell you there's a lot of cynicism among that crew.
 
When they get on a call and someone starts talking, if they lead the call with the innovation lab and the things they're doing there, a lot of times I think there's a suspicion - sometimes soundly placed - that that is a little bit of, "Look over here not over here."
 
A lot of times I think they'll almost ignore, even when it's genuinely placed, ignore those words and think you get hung on misdirect. So I think what it has to be is it has to be tied to an overall strategy of the bank. The strategy of the bank can't just be digital. What does that mean? It has to be we're going to transform the customer experience. We're going to win this particular segment. Here's how we're going to go about doing it and here's where we're going to do it most efficiently and most effectively. And here's how it's going to manifest itself into the things that will ultimately drive value to the business.
 
Some of those might be short term. Some of those might be long term. There are a lot of banks who, I said the cynicism can be well placed, There are a lot of places where not just banks but other companies are undergoing ... lots of industries are undergoing a digital transformation. Where they actually use the innovation labs as a little bit of innovation theater. Right? A little bit of a misdirect. Let's say we're doing this as a means of appearing to be doing the right thing or superficially doing what the world seems to be asking them for.
 
What I would actually dig deeper on is:  What is the purpose? How does it tie to the strategy? Make sure they understand the potential downsides of that. The downsides being how's it going to affect the moral of the talent and the other parts of the organization?
 
Is it always going to say that innovation only happens in this area? And innovation is going to die in other parts of the bank? Or the other person to think aren't capable of that sorts of innovation.
 
So it really is a tricky needle to thread. I talk to quite a few bankers within banks, some who have innovation labs, and they're working outside of that area and they're truly innovating on making the customer experience better. Becoming more valuable to the customers so the customer becomes more valuable to the bank.
 
And they're doing the hard work and pushing the hard fight. And they see the innovation lab guys without any real metrics. Without any real time frames and with foosball tables and Xbox's and other things while they're in cubicles doing the hard slog. And it can be quite demoralizing. So I think the long answer to a short question is as always it depends.
 
But I think you also want to be looking at ... I would want to understand what's the purpose? What are you trying to achieve with this? How's it going to manifest itself with the results? Have you really truly thought about the downsides of this? Is this the best way to achieve that purpose? 
 
And then, how does this not become an innovation lab forever? This needs to be absorbed back into the organization over time and to make sure there's a plan for that. If you don't have good answers to those questions, it probably is a little bit of a misdirect, some innovation theater in some ways a way of buying a few quarters' time until they have to answer the hard questions again. So you want to make sure of that.
 
Jim Young: Yeah. That cynical way, it's almost PR play as much as it is anything else, right? "Hey, look at us, we're innovative," as opposed to, "Hey, look at us we're creating value in this way."
 
Carl Ryden: It is and I think one way to look at that is to what degree the people in charge of it are more PR people than doers. There's talkers there's doers. You want to make sure you have the ... you of course have to publicize what you do. You have to communicate what you do to get everybody on board and to mitigate some of the problems I just talked about in the earlier case. So you have to be able to communicate that to be able to thread that needle. 
 
But if you start seeing it where it truly is a bit of a PR thing, where the measurable outputs are press releases and news mentions and those things. A lot of that may be necessary early on to build momentum and align the company and to gather folks around that purpose. But ultimately that by itself is not all sizzle and no steak.
 

2) Where is the bank focusing its innovation (retail or commercial) and why?  

Jim Young: What about retail versus commercial? Putting yourself in an analysts shoes. If you get on a call and they're talking a lot about how they're innovating and different things they're doing on the retail side. Or, they do the opposite and say versus commercial, does that matter to you as the investor? Is one more important than the other in terms of this innovation?
 
Carl Ryden: Again, it has to fit to the overall bank strategy. The overall bank strategy. So some banks might have a huge need and desire to attract deposits and to attract the retail customers. Some of them may be weak in that area. Some of them may be immensely strong in that area and they need to deploy those funds. And so commercial might be better. I think making sure that the innovation strategy is tied to the bank's overall strategy and their position and where they are and it's achieving the purposes that they need to achieve, is really key.
 
But again what you'll see is the retail, the folks who are probably doing innovation theater, it's probably heavier tied to PR and heavier tied to retail side because that's the things that are easy to rock. Those are the things that a lot of the hard work ...
 
I talk to commercial bankers all the time who are doing incredibly innovative things using AI and machine learning deep within the bank to analyze the documents of the bank and make sure that the data's the right data and maximizing cross-sell and having real meaningful impact on the bank's business. But there's no PR budget behind it and there's no need for that. Communicating it internally and putting the numbers on the board and pointing to the scoreboard is how they do things.
 
Not to say that you can't do that on the retail side. You can. But that sort of stuff is never picked up by the news media. Even if you had a PR department around that stuff, it's just not exciting or sexy enough for the general mass market to pick up. I think the folks who are truly doing the innovation theater tend to be drawn more towards the retail side just because that's where it's newsworthy. That's where news outlets will pick it up.
 

3) How is the bank using all its customer data? 

 
Jim Young: Customer data. Enormous amounts of it at banks. Enormous potential there. When analysts and the banks starts talking about their customer data and how they're using it, how much does it matter or how key is it to get to sort of how they're using it? The terms I've heard kind of put on different poles here are helping versus harvesting. Can you speak to that?
 
Carl Ryden: Well, so the helping/harvesting, first heard that from Gordon Ritter at Emergence Capital partners talking about his idea of coaching networks. That you gather what people do. You compare it to what other folks do, and then you coach others to be better. Now, enterprise software and enterprise applications and company enterprises like banks are actually in much better position to help instead of harvest.
 
The Facebook's of the world. The Google's of the world. The ones who are built upon kind of selling ad dollars, are in the harvest mode. We take your data. We use your data to then sell to others who want to get your attention, right? And the joke in Silicon Valley has always been is if you're not paying for the product, you are the product. I think that is the harvest mentality. 
 
The help mentality which is one where I think banks are actually well positioned for is that you're not gathering the data on your customer so you can sell it to advertisers. You'd never do that and if you did, your regulars would probably crush you. It's not a good idea because your business is built around trust. Right?
 
I think banks have an opportunity to be really fiduciaries of trust for their customers and using that data to help their customers achieve more. To help them better manage their money. To help them better achieve their goals.
 
And this actually spans from retail all the way up to commercial is how do we use the data we have? The data, people talk a lot about data. Data itself it has to be the right kind of data. Behavioral data grounded to outcomes so that you can actually see they did this and this positive result occurred. Therefore, we can kind of make inference from that that well if somebody else who looks like them did that, they would have that positive result occur as well.
 
So how do you take that data, translate it into insights, and then drive it back to actions? I think understanding the value chain of the bank and the value proposition of the bank and the strategy of the bank. But then understand the value chain of applied intelligence, right? It starts where you take the data. The right kind of data. You translate that data into insights and that's where a lot of things die. On the AI and the machine learning type stuff is you produce this wonderful insight but then it never drove any new action. Then you have to take that and translate it into action. And that's what I call the last mile of AI where most of these things are dying.
 
And so as I would go through, I said, walk me through. If you tell me you got the best data and you're going to build an advantage based on that, what sort of data? How's it grounded to outcomes? What behaviors are you seeing? How are you translating that into insights? Insights that you can deliver back into the right set of eyeballs where they can really have an impact. Describe to me that chain. Otherwise it really is a little bit about again sizzle but no steak. In Texas they call it all hat no cattle. It superficially looks like you're doing all the right things. But the rubber's not connecting to the road. You have no way of making progress. 
 
Jim Young: Yeah. I think that's where this sort of thought experiment can be very helpful to a bank. Because again it's like if you had to get in front of an analyst and explain this to them, you pretty quickly realize, "Wait a second. This doesn't lead to anything that matters to them." And you're missing that last step.
 
Carl Ryden: The analysts are not without or in some ways not without guilt in this equation either in that are sometimes superficial themselves. They will tell me about innovation and they're just checking the box. The lazy analysts are checking the box that says, "Do you have a lab? Yes. Do you do this? Yes. Do you have kids in hoodies? Do you have a foosball table? Yes. Yes." But what I'm saying is even satisfying those guys in the short term, they're going to turn and hate you in the long term because many a CEO has come back and says, "But, just a few months ago you were telling me this was important." Right? 
 
At the end of the day, performance is what matters. At the end of the day, delivering true value to your customers so then they deliver more value back to the bank. And doing that in a way that hopefully only you can do. Or that you can do better than anybody else in the world and that you have the machine built that it gets better and better each time you do it.
 
4) Is the bank's innovation goal to be more efficient? Or more effective?
 
Jim Young: And just for the record, Carl and I are recording this podcast both with jeans and sneakers on so we are obviously innovative here. All right. CEO gets on the call and talks about how the innovation they're doing is really allowing them to streamline processes, cut back on head count. Is that what you want to hear as an analyst? And if not, and I can definitely see a scenario in which it is what you want to hear. Why would you maybe want to hear anything different maybe?
 
Carl Ryden: Well that's a difficult one in that again, it's a difficult one for even a CEO to come on and say that's what we're doing because it also begs the question, did you have extra head count before? Were you inefficient? Blah, blah, blah. But maybe you've already ... they may have already told you that or that ship has sailed. And there are a lot of gains to be had in terms of efficiency. But I think you always ... there's a couple of books that I always recommend to folks that not a lot of bankers have read. One is The Everything Store about Jeff Bezos and it's really a story about long-term thinking and how he built Amazon and how he thinks about Amazon.
 
But there's another book which is required reading for all executives at Amazon called The Goal: A Process of Ongoing Improvement by Eliyahu Goldratt, which is about what is truly the goal that you're trying to achieve here and how do you register things back to that which helps all the earlier stuff. And the last one which is very important here is another book I think it's Peter Drucker from 1969 called The Effective Executive I think it's what is called. It's required reading for Amazon execs too.
 
In that book he breaks down the difference between effectiveness and efficiency. Efficiency is doing things right. Effectiveness is doing the right things. It's really easy to trade off efficiency for effectiveness.
 
What I would look for as an investor in a bank is a CEO and a management team who truly understands their strategy. How they deliver a differentiated experience to their customer base and how they built a machine that allows them to continually make that better with every interaction they have with the customers using data and behavioral data grounded to outcomes with continuous improvement machine.
 
But then ultimately that they understand the balance between effectiveness and efficiency?
 
There's a lot of things you can do in a bank that make you more efficient for this quarter or for next quarter. But you've given up on effectiveness of serving your customers and fulfilling your strategy. So I would really push on the balance between those and that they understand that. And that's something that I think is missing in a lot of places right now.
 
5) Is the bank using AI and machine learning positively, or punitively? 
 
Jim Young: You talked about using AI or machine learning positively rather than punitively at a bank. What do you mean by that and why should an analyst or an investor care?
 
Carl Ryden: So AI and machine learning is just a tool. It's amoral. It's not good it's not bad. People in the news media love to blow it up around kind of how fear and everything and terminators are coming and all that stuff. Other folks make it a panacea about how everything's going to be wonderful. We never have to work we just cash a check. All those wonderful things. The answer is AI itself is not either. It's a tool. It's a hammer, right? You can use it to build someone a house. You can use it to beat someone in the head and steal their wallet. It's a tool that you use and it's how you wield it which is really important but it is an amplifier.
 
It takes what you're doing and multiplies it by 10 or 100 or ... it's a force multiplier which is why I think having the right purpose, having the right culture, having the right values of the bank and making sure you communicate the heck out of those. Because building an AI system or a machine learning system to look at the behaviors that you see across your customer base, gather those up, compare them to behaviors that produce the best results for your clients and your customers, and then coaching your customers to do better, that's a positive helpful loop. And I can build a machine learning system to do that. 
 
I could also probably easier and more trivially build a machine learning system to detect which customers that I could easily slip a fee by and they not notice. Now no one would ever do that explicitly. No one would ever say on their business plan or their memo to management this is my plan. But a lot of those it's not as obvious like that. You want to make sure that everything is grounded. Are we helping to make the bank more valuable to the customers so that the customers will be more valuable to the bank?
 
If you do that, that's sustainable and you can do that with gusto. If you start going down the route of how can we optimize this and extract more value from our clients, if AI becomes an extraction tool, a strip mining tool, the strip mine value for your clients ultimately your clients will discover this and your brand will be destroyed. So it really is important to make sure ... recognize you're playing with fire here. Fire's a wonderful thing. It changes society but it's fire. And you need to make sure you don't let it get out of control.
 

6) What kind of scale advantage is the bank pursuing?

 
Jim Young: Yeah. Use that strip mining analogy, you come up with a lot of great stuff but eventually you come to the end of it and there's nothing else you can do with that land after you're done with it.
 
One more question here. I'm at a big bank. I've got a lot of built-in scale advantages. Why can't I just keep using my size to keep pushing my competitors around? Is it possible for me that the whole AI machine learning innovation stuff is a distraction from what I'm already doing really well?
 
Carl Ryden: Well the nature of scale is changing. So turn of the century type scale. Economy is a scale where fixed costs get leveraged across larger unit volume and there you have lower unit prices. And therefore you can out compete your competitors and can take more market share. That's what creates oligopolies, right? That's what created ... there's three auto manufacturers in the U.S. Ford, GM and Chrysler. Right? Because of economies of scale. I had the biggest factory. I had the most people. Eventually it bumps up against ... this is why the Sloan Management School was created because Alfred Sloan, the Chairman of GM, realized you start ... the organization gets just too unwieldy at some point and that's the negative feedback loop where you cap out. Where it doesn't become completely winner take all in industrial scenarios.
 
But I put forth a thesis 2010. I was on the advisory board for Microsoft Azure, their cloud, when it was just starting out. It was a small thing. I think that's why they put me on the advisory board because I was one of the few people using it at the time. It's now turned into the future of Microsoft. In there I did a presentation to the room full of senior IT executives and one guy from Microsoft nearly lost his coffee through his nose when I said you guys have to learn to embrace the cloud or one day you're going to wake up and you're just managing printers. Right? Because that's the last physical thing that exists within the bank.
 
The other thing I said I truly believe that statistical significance is the economy is a scale of the information age. So what I mean by that is Amazon's a data business. Right? If you have the best data and the best data means behavioral data grounded to labeled outcomes. When they did this, this led to this. When they did this, it led to this. That's the best data.
 
If I have the best data and the largest set of data and the most diverse set of data and I can make the best predictions around that, then if I can feed that back and create better customer experiences I crate a flywheel effect. I go around that flywheel. Better data gives me better insights. Those better insights I can use to drive different actions. Those actions then give me even better data and I go around that ... and  better customer experiences and that allows me to attract more customers which give me more data. 
 
And all of a sudden, Amazon, this is where talk about making things cumulative. Every person who shops on Amazon makes it better for the next person who shops on Amazon. Every person who buys something on Amazon makes it better for the next person buy something on Amazon. That creates a positive feedback loop that really doesn't have a negative loop like Sloan saw at GM. And it creates these natural monopolies. It's very hard to be the guy to catch Amazon. Look at how much money Walmart has poured into eCommerce and poured into jet.com and other things trying to catch them, right? It's not at all easy. 
 
So I would say the nature of scale is changing. Used to as a bank you would buy your own IT systems. You'd build up your own IT systems because if you were a trillion dollar bank you could spend more than anybody else could on that. But you would get to amortize it over $2 trillion of assets, right? So same scale economies. Fixed costs leverage over. 
 
But now what happens is the data center we have at PrecisionLender as a small company, we run in Microsoft Azure. We have 50 data centers around the world. World class data centers run by Microsoft. We can buy that by the drink. I don't need to have fixed costs scale. I can access that through other means. The scale advantages of fixed cost scale advantages have eroded away. And the advantages of data-driven scale advantages, intelligent-driven scale advantages are coming in their place. So I think very few folks actually I think hold that idea. I would say five years ago you'd have found folks. That one's been settled I think.
 
So recently at a conference, it was an Insight Ignite event over in London. There was a guy there talking about innovation, right? And I heard several people talk about this. I would say, as an analyst, if I heard someone say this I would probably lean in and push back. The thing is you have to learn to fail and you have to fail fast. You have to learn to embrace failure.
 
Ultimately, people say that a lot, but words mean things. And if you say that, people start to embrace failure. Failure sucks. No one wants to fail. That's not something you want to embrace. You have to love learning.
 
When I talk about machine learning and other tools are ways to accelerate the rate that your organization can learn, you need to love learning. Failure is necessary to give you learning. You will endure failure because you love learning. But you don't need to learn to love failure. Right? It's the idea of no pain no gain but the goal is the gain. It's not that you need to learn to love pain. You don't want to be a masochist. You want to be a weight lifter. You want to work out to get better. You endure the pain for the gain. You endure the failure to achieve the learning.
 
A lot of these things we need to learn to embrace failure and failure is ... that's not it. You need to love learning so much you're willing to endure failure. Right? But you still have to hate it every minute. Because the more you hate it, the more you're going to learn from it.  
 
Jim Young: And again as the bank CEO the investors and analysts, they're not loving your failure.
 
Carl Ryden: No. And you can get on there all you want and say, "We got to learn to love failure." It's like they're ... "I'll learn to love another stock."
 
Jim Young: Exactly. 
 
Carl Ryden: You can love failure. I'll love this other stock who's learned to endure failure to increase the rate of learning. And what they're learning is learning how to kick your butt while you're loving failure. 
 
Jim Young: Exactly. All right. Well now that will do it for this week's show. As a reminder, if you want to listen to more podcasts or check out more of our content, you can visit our resource page at PrecisionLender.com or head over to our home page to learn more about the company behind the content.
 
Finally, if you like what you've been hearing, make sure to subscribe to the feed in iTunes, SoundCloud, Google Player, Stitcher. Love to get ratings and feedback on any of those platforms. Until next time, this has been Jim Young and Carl Ryden and you've been listening to The Purposeful Banker.  
 

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About the Author

Jim Young

Jim Young, Director of Communications at PrecisionLender, is an award-winning writer with experience in a range of positions in media and marketing, from reporter to website editor to content marketer. Throughout his career has focused on the story – how to find it, how to understand it, and how best to share it with others. At PrecisionLender he manages the many ways in which the company shares its philosophy on banking and the power of relationships Jim graduated Phi Beta Kappa from Duke University and holds a masters degree in journalism from Columbia University.

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