In this Purposeful Banker episode, Dallas Wells and Jim Young look back at the BankOnPurpose 2019 talk given by former poker champ Annie Duke, author of the book, "Thinking in Bets." They discuss the ways in which Annie's insights on decision-making and risk can be applied to the challenges faced by commercial banks.
"Thinking In Bets" (BankOnPurpose 2019 keynote presentation)
"Thinking In Bets: Making Smarter Decisions When You Don't Have All the Facts"
New England vs. Seattle: Interception in Super Bowl 44
How Does Your Commercial Bank Coach?
Maria Abbe: Hi, and welcome to the Purposeful Banker, the podcast brought to you by PrecisionLender where we discuss the big topics on the minds of today's best bankers.
Today's podcast features Jim Young, Director of Content for PrecisionLender, and Dallas Wells, our EVP of Strategic Initiatives.
Jim Young: First of all, Dallas. I always thought, myself, that there's a good poker banking crossover there because what is alone, if not a calculated bet on a customer's likelihood of paying back? My father, when I tell him I'm going to a casino thinks that I'm putting money on a roulette wheel, and I like to think that banking is a little bit more scientific than that. Is that a fair analogy here or is that a little too simplistic?
Dallas Wells: No, I think it's fair. I tried unsuccessfully to make some of these same analogies just because I, in blog posts and things, I desperately wanted to include some Rounders quotes and screenshots and things, but I never pulled it off quite to the same effect that Annie did in her book, which is excellent by the way, the whole concept of thinking in bets. Of course we'll have a link to that in our show notes.
But to answer your question, is that fair? I think it absolutely is, and I think there's some benefit in actually borrowing Annie's terminology of describing things as bets. And it's not just will we win or not, right? Will this pay off or not? But also a lot of what she talks about is uncertainty. That's a big part of poker is that you can see your own hand. You can't see the hand of everyone else, so you're making decisions with imperfect information and gaps about what the other people know, what they understand, what's important to them. You have to come to grips with that uncertainty and make the best decision that you can in the moment.
She actually has a good anecdote on a separate podcast that she was in, which is actually what got us to her book and eventually inviting her to come to BankOnPurpose. In this story, she was talking about being at a restaurant and trying to order and between some language barriers and just not understanding the menu, the server walked away and Annie, talking to the person that she was at this meal with goes, "I'm about 60% that that order is going to come out right." She actually starts viewing the entire world through what are the odds, right? How likely are we to succeed in doing this?
And then the other part of poker, and I think the other part of banking that relates is, and then what's the potential payoff? So of course there's the credit decisions that banks make over and over and over again every day. But the one that we see a lot now also, is that banks are making some bets on strategies, on technology, on business models. Those are much more difficult or at least outside their comfort zone. The credit stuff, they're pretty darn good at.
Making a bet on technology feels a little weird. There is more uncertainty. There's a lot more upside and downside potential that they have to evaluate, and when they come at it with their banker hat on using that credit thumbs up or down decision mentality, they struggle with it a little bit, and a lot of times it just ends up being paralysis. I think this whole concept of of describing things as bets and thinking about the odds and thinking about the potential payoff and all those things I think, are a useful framework that can actually really be helpful.
Jim Young: Yeah, and I think again, if you're not someone who is familiar with the world of poker playing, and I made the joke about the roulette wheel because there is some people when they think bets, a lot of times they think of guys looking for action had the adrenaline and that sort of thing. And really, if you've ever watched a poker tournament, and believe me, I've tried to watch with people that aren't fans. If you're not really into it, you're going to be bored stiff because it really is a lot of cold dispassionate calculation which any banker should really appreciate.
Fortunately she did not sit there and go and tell loan by loan stories in her presentation. She went with much more entertaining things. Like for example, from the world of sports, if you are a football fan, you know the infamous Seahawks, Seattle Seahawks Superbowl play
And for those who don't, I'll give the very quick synopsis which was the Seattle Seahawks were at I think the one and a half yard line on second down. Anyways, I don't want to get too specific. The point was is they had an all world running back. Most people thought they should have run the ball to try to get it into the end zone. Instead, they threw a pass. That pass was intercepted, and pretty much everybody in the world outside of the Seattle Seahawks coach, and I would say Annie at this point, thought it was a terrible, stupid play.
She used that as an example of ... My family is sick of this word because I have started using it all the time of resulting, i.e., using the result as the determining factor as to whether the decision was the right one. Again, I could argue until I'm blue in the face about whether that was the right decision. But, I see your point here, which is that people make this thing all the time in the sports world of saying, "Well, since this team won or this team lost, that meant their decision making was terrible." And you can see, you can obviously roll your eyes at it there, but do you see this sort of thing happening in banking?
Dallas Wells: I mean, this is human nature. This happens all the time. It most certainly happens in banking, so we'll start again with the simple loan analogy. When a loan goes bad, the obvious thing is to say, "Well, somebody made a bad decision here" and a lot of times someone will get fired for that. When in reality, if you roll the tape back, maybe they made the exact right decision and just some crazy things happened. Some unexpected events happened and you can look at it ... The entire banking industry did this right before the financial crisis, right? Where, or right after the financial crisis where it was clearly some people made very bad decisions and some people made very good decisions and that's ... You're looking at the results, when in reality some people just got lucky, right?
There was some people that just didn't ... They bought some of the same mortgage backed securities and one tranche happened to go bad, and the other one survived, you know? Or, a lot of times the result doesn't reflect on how well the decision actually went. You see it in individual loan decisions. If it went bad, clearly we were wrong. If the loan paid back, then clearly we made the right decision, and that can just be categorically false.
The other place that I see it a lot, prior to coming to PrecisionLender, I help banks do hedging of interest rate risk. Yes, it's wildly exciting, but doing things like putting on caps, and LIBOR caps, and interest rate swaps, and things like that to hedge risks that they had on their balance sheet. So we would evaluate their risk and say, "If rates do this in the future, you're in big trouble. So let's hedge that." Basically, let's buy an insurance policy. Well then, when that doesn't happen, right? Everything is going well, but then they are underwater on that interest rate swap. They're like, "God, that was such a stupid decision. Why did we do that?"
It's like, no, no, no. That's not how this works. You can't look at the fact that you now have an unrealized loss on your hedge and say, "Because I didn't use the insurance policy, it was dumb to buy it." That's not how it works. It's like buying life insurance. Just because I didn't use it yesterday, doesn't mean it was a really stupid decision to have it. I think that looking at results, and there are lots of places in the bank where that's easy to see because either the borrower paid you back or they didn't.
You buy a security and it gets marked to market every single day and you can grade yourself. Did we buy the right thing or not? Well, you can show a loss on something and it was still the right thing for your portfolio and your strategy, so it's a dangerous thing that happens all the time.
Jim Young: Yeah, no doubt. No doubt about it. And I can distinctly hear the self talk in my head from being at a poker table and thinking, you fold out of a hand because you know that's the right decision you don't have ... There's just no ... Based on information you have, you don't, yet you've got a 2-7 offsuit and there's no ... Someone's raised in front of you and all that sort of thing, and the flop comes; 2-7-7 and you go, "Oh my gosh. Well, I'm an idiot. What was I doing?
Dallas Wells: Yeah, why didn't I play? Yeah.
Jim Young: Right. Exactly. Exactly. Then she gets in, she takes a little bit of a different curve away from that classic bet poker table thing and into an area which I thought was really interesting about how we form beliefs on things. She said basically that you would think you follow the order ... We all like to think we follow the order of. We hear some piece of information. We vet that, and then we form a belief about it, but that humans actually go on the order of, they hear something, they form a belief on it on it, and then they stack the deck essentially to make what they vet fit what they believe.
They seek out confirming evidence or they discredit disconfirming evidence. Bankers are humans too. But I like to think that a good credit underwriting process is that vetting part, and that bankers are doing that part before they form their belief about a customer or a deal whether to expend credit. I mean that's right, right? I mean, please tell me I'm right on this.
Dallas Wells: The good news is, is bankers figured this out a long time ago that they were their own worst enemy. This is why you have such a division of responsibilities within a bank, and it causes some friction that actually is healthy friction where you have a sales team that is pushing to make deals happen and you have a credit team that is incented in exactly the opposite way.
Their job is to not let us lose money, so there should be some friction there and some back and forth, and you have one group who can look at these things independently. So it's not that they can get past that very normal human bias and tendency, it's that they're checking each other. I think that's where Annie actually ends up going with this. And in her book she talks a lot about having some accountability teams and in the poker world that is, all anybody wants to talk about is their bad beat story, right? Like I had this hand won, and then the one card that could beat me came out, and it's whining and complaining and what you need is this group that will hold you accountable and say, "Look, did you make the right decision? Did you play it correctly?"
Then if so, forget about the outcomes and the results. And that's what we're doing in banking is we're saying to the credit group, "You hold the sales team, the relationship managers accountable." So, I think on brand new credit that the bank's extending, I think they're actually really good at this. Now, where that changes is when you're already in a deal, right? You're already in with a customer and they come to you with the next thing, and sometimes it's even a "Hey, things aren't fantastic. It's not all rosy and butterflies and rainbows, so this next thing is what's going to turn it around for us and I need to borrow more money to make this thing happen." That's where I think banks can ... They're trying to kind of justify the decision they've already made, right? And it's, "Hey, we're in it. We've got to help them out of it. We've got to, you can kind of ... If you squint at the numbers just right, they do make sense." I see banks do that where they end up throwing good money after bad because they're in this and they don't want to admit they're wrong.
Now, that's what the full disclaimer that I get sometimes once you're in is the bank. If you cut off credit, you kill it immediately, right? So I get that. But I think it actually goes beyond that. I think banks talk themselves into, because of exactly what Annie's talking about, the human tendency is actually just form your opinion. Well, you've already done that. This is a customer, and sometimes you're already telling yourself they're a good customer, so when the numbers come in and tell you something different, sometimes you'll say, "Well, let's turn the numbers just a little bit and make it look a different way because that feels better." You know? Again, it's those natural human tendencies we just have to be aware of.
Jim Young: Yeah, and you mentioned that one actually, and what comes to mind immediately actually is a post that Gita Thollesson just put out. It was out in her latest newsletter, and I'll post a link to it in the blog, but about the funding curves and what some banks are doing there, which is ... It's that we can't have it that funding curve flipped like that or go in the opposite direction. It needs to go up and to the right. So let's-
Dallas Wells: Right. Can't have inverted curves.
Jim Young: ... Right. Can't have an inverted curve here, so let's flip this. Let's put our thumb on the scale here and there. So, okay, good. Now that's the way we want it to look. Even though you basically-
Dallas Wells: Even though the entire marketplace says opposite.
Jim Young: Right, exactly. Because that's not the way we want it to be. That's not the way, yeah. So, which is an interesting thing and then some banks will give you their compelling reasons for it, but it's still fascinating to see that play out the way it does.
You were, I think, getting into a little bit of this, when you were talking about ... You were
talking about the human accountability and that outside decision maker, but the really intriguing part to me is when she went into what she called the inside outside view of decisions. And that inside, when you're inside the decision, you're that human there that it's personal, it's direct with you.
Outside is the information you're getting from somewhere else about that decision. And she went specifically to inside view of the human being involved in it. The outside view coming from computer algorithms, and this total transparency is something that we think about a lot when we think about our our software and Andy, our virtual pricing analyst, et cetera. And it's really something that our CEO, Carl Ryden, he talks about humans doing what they do best or computers doing what they do best, so that humans can do what they do best. That to me, I don't know if you had the same thought, but it really looked to me when she was talking about that where you can marry your judgment with the raw dispassionate data.
I think this is to go beyond PrecisionLender. It's a concept we've talked before about like Gordon Ritter's coaching cloud
. What technology now allows is the use of this massive datasets and all the fancy analytics. And what they can do is guide the human where the human needs guidance, right? And so there's some things that humans are really bad at, and I think that's what Annie is fantastic at understanding, and what every great poker player is good at is getting out of their own heads and understanding that they just have some ... Their logic, their thinking, their decision making just has some inherent flaws. Being aware of those enough and willing to seek guidance and help where you can get it, right? And to sometimes turn things into a cold calculation despite what you may think, right? One of the interesting things that happens when we actually implement a bank, one of the really important steps that we go through is we put the existing customer portfolios into the software.
What that does is it measures how profitable is each individual customer, each individual transaction, and it's this scary moment of truth for a lot of the individual bankers, right? Because they are all of the sudden going to instantly, as soon as we flip the switch, they're going to be able to open that up and they're going to be graded on every decision they've made over the last 5, 10 years. They love to go in there, pull up their own portfolio, and they're always surprised the customers that they think are their best customers are rarely at the top of the list of most profitable. And their initial reaction is, "This is wrong. You guys have something wrong in here. We've got to toggle some switches, turn some dials, because this ain't right." That happens with every single bank we've ever rolled out.
We've done this over 200 times now. That has happened over 200 times. It's a natural part of the process where you let the computer do what it's really good at, which is make this cold, numbers based calculation and it spits out a result. What humans are good at is adding the context. There are some times where the right strategy, the right business strategy, the right relationship building thing, is to look at that number and then make a decision that goes against that number. And humans can do that, but you need to be aware of that number and trust that number and make it a part of your decision. And if you're going to go against it, have a reason for doing so. You know? That's what I think. If you look at the future of banking, heck, the future of work anywhere, it is the humans learning how to work with the computer.
Computers are really good at calculating numbers. They're really good at finding patterns that we can't see. They're really good at remembering things that we forget, and they just don't have that natural bias that human beings have. What they can't do is build relationships. They don't have judgment, empathy. They interpolate really well. They don't extrapolate very well. There's those things that humans have to figure out what they're good at, be honest about what they're not good at, and let machines fill some of those gaps.
What we find is there are some bankers who are really good at that, and they're starting to embrace all these modern tools, and they see the performance from it because they're willing to admit that they have some gaps. They're not an all-knowing, all-calculating human computer who can do all this stuff on their own, so those that embrace it do really well. Those that fight it, good luck. You're fighting a tidal wave here.
Jim Young: Yeah. Again, to look at it from the poker perspective is that there are the guys who are the quant guys, the math guys out there who will crunch the numbers and know that they can, in their head they got a 7.3% chance of winning this hand based off of what they know, et cetera. And then there's those times when you say, "I think I'm probably ... The math tells me I'm beat on this, but I just have a read off of based off of what this person's doing, et cetera. And that sort of thing that I think I'm actually ahead on it." And so you make a call and the math might tell you to do something different in that situation. And yeah, with banks and how they make their decisions, sometimes there's just information that you can have that the numbers would tell you to do something different, but you know enough from all those human connections to know that there's more to it than that.
Well, finally Dallas, I want you to ... We've talked about this with a poker hat on and we've talked about it with PrecisionLender, but I want you to go back to your, put your old banker hat back on and think about that if you were in the audience absorbing that talk from a banker perspective, and if you were going to head back, we talked about various things in here and so we may have already covered all this ground, but if not, if you're heading back to your bank and someone said, "Hey, what was Annie Duke like?" And what's one of the ... Another takeaway or maybe your biggest takeaway that you had from that, that you would share with others?
Dallas Wells: I think the thing that really resonated with me, and it's a conversation that we've been having more and more internally and with some of the biggest banks in the world, which is, I think we'll have more stuff to come on this, but there's ... What banks are trying to wrestle with right now is the difference between risk and uncertainty and how you handle those two things and how you balance those two things. And importantly, what tools you use to manage those two things. So if you think about, again from perspective of just a relationship manager doing a deal and a credit team trying to decide whether or not to approve a deal, there's all sorts of things that you don't know, so there's all sorts of uncertainty. You know, the future direction of interest rates, no matter what your Treasury team tells you, they don't know where things are going, right?
We don't know what's going to happen with the future of this business. The owner of this business could keel over in their chair tomorrow, and how does that change things, right? There's all these uncertainties and bankers try to measure that with great precision, and they build these giant complicated models that don't always necessarily mean you're going to get a better management of the real risk, right?
And so to me, that's what Annie was really good at. That's why her talk was powerful. That's where her book was powerful, is saying uncertainty is okay. Let's just be honest about what we don't know. Let's measure the risks that we do have, right? And also set aside this thing and say, "By the way, there's 40% of this that I can't see at all. And I need to have some contingency plans for those. But I just need to get comfortable with the fact that I don't know."
That's an uncomfortable thing in banking, but it's just the reality. I think that was the big takeaway that you can take back is get used to the uncertainty, be explicit about it. Say these are the things that we don't know. And then, what you can get down to is like in poker you can say, "Look, there's a really big potential payout here. It's a big pot, but I only know 5% of what I need to know. So how much am I willing to spend to learn more? And am I willing to make that bet, and how expensive is it going to be?"
If you think about business decisions in that same way, I think it's a useful framework. It's a great book in that you get to decision trees, which is an insanely boring thing to think through, but Annie puts it in these poker terms and in these real life situations that makes it, I think, fascinating and also really useful. So, some good stuff that you can take back and use in your day-to-day job.
Jim Young: Yeah, absolutely. Yeah. And again, with a final poker thing, if you wait until you're absolutely to only play in the hands in which you're absolutely certain of an outcome, you're done.
Dallas Wells: Exactly, and banking is the same way, right? If you only bank the sure things, you're not gonna make any money. There's no reason for you to be around. Somebody can just take your money and buy Treasury securities and it's actually a much better return, right? You have to take risks, you have to take uncertainties, you just have to be smart and transparent about those and there's some banks figuring that out.
Jim Young: Yep, absolutely. All right, well that'll do it for this week's show and I think in the coming weeks and months, we're going to have a few more shows like this in which we go back through some of our BankOnPurpose speakers and really relate what we learn from them and how we connected it to to banking.
Now for a few friendly reminders. 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 you can just head over to our homepage to learn more about the company behind the content.
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