The Default Settings That Can Help Your Commercial Bank

April 16, 2018 Maria Abbe

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Jim Young and Dallas Wells discuss why default settings matter at your bank and how your default settings can either hinder or help you. 

"We know that the default settings determine the behavior of the group. Organ donation, 401k allocations, the typeface on our word processor--the way it's set to act if we don't override it is often the way we act. Because often, we decide it's not worth the effort to change the setting today." - Seth Godin 


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Podcast Transcription

Ashley: Hey everyone Ashley here, we're so excited to announce that it's that time of year. It's time to Bank on Purpose. Bank on Purpose is a conference based on the belief that the path to customer success is built on a customer centered foundation. It brings together the best and the brightest minds in banking. Austin, Texas on April 25th to the 27th. You can use the code podcast18 to get 10 percent off your registration and to show your pride for the Purposeful Banker podcast. It's time to stop reacting and get back to what makes banking great. It's time to Bank on Purpose.
Jim: 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. I'm your host Jim Young, director of communications at PrecisionLender and I'm joined again today by Dallas Wells our EVP for international operations. Today we're going to be talking about something that may not seem like it's all that important, creating default settings or if you're from my neck of the woods, creating default settings. The topic was inspired by a recent blog post from Seth Godin called Getting the Default Settings Right which is built on a 2016 article at Pro Publica called Set It and Forget It, How Default Settings Rule the World. So Dallas to start with can you kind of tell us why this particular topic struck a chord.
Dallas: Sure and for what it's worth I'm from Missouri and we say default also. So don't feel alone on that one from your neck of the woods.
Jim: Fantastic.
Dallas: Yeah.
Jim: So the reason that this topic kind of made sense to us to talk about, so Seth Godin has in his usual fashion a very short blog post where he takes a more in-depth blog post from someone else and he turns it into a Jack Handy style, deep thoughts, reflections on life. So he takes this Pro Publica article about default settings talking about essentially software default settings and Seth turned it into, since we all know that default settings are important let's use the right kind of default settings in our own lives and in our professional lives so that we approach things with the right default starting point. So Seth's post was interesting but actually what was more interesting to us was the Pro Publica article behind it which talks a lot about why it matters so much in software. So from our world at PrecisionLender we actually spend quite a bit of time thinking about this exact topic.
So anywhere where a user has to input something or interact with our software we have to have a starting point for them. So a field they enter has to have a starting range. If they drag and drop something we have to have a point that they start from. So defaults are really important. Sometimes we set them. Sometimes we have the administrators set them and there's actually a fair amount of strategy that goes into that so we thought it was worth talking about.
And I get that it's important to a software company. But you know in my area over in communications and marketing you know it's important to me that we not space twice after a period anymore.
Dallas: So I found, yeah.
Jim: Design it's important that we use a particular color and that sort of thing. So is it important in the grander scheme of things I guess?
Dallas: Yeah that's a fair question. Like isn't this something that only you guys care about. Because you have to. But I think the point is that default settings matter in a lot of places and I think that's kind of where Seth Godin was going with it and that's where we go with it with our banking clients which is this isn't just a software setting, you need to actually pay attention and have a reason for why you're putting that number where you put it. And Richard Thaler actually just won a Nobel Prize along with a few others on this exact topic which is how do we influence choice. Kind of by how things are framed. So one of the examples he talks about in some of his work is elections so that the order of names of candidates on a ballot actually influences the results.
And so he takes a much deeper kind of social look at it of are there ways that we are shaping society that we need to pay attention to. And there's some economic theory behind it too of if you're an advertiser the way that you list options or choices to your buyers, those things matter. And it actually comes back to us in pricing as well. You know how many choices do we present to a borrower, how many options do we give them. So it actually has a lot of implications. It can steer behavior in ways that you may not even expect and in a place like a bank where it's a volume business right. So we do very thin margins we do hundreds or thousands of transactions. The default starting point on all of those if it just nudges the behavior just a little we need to pay attention to it because just a little could be the difference between profitable or not profitable in the banking world.
Jim: So let's delve in that a little bit deeper into particularly just in the area of pricing within a bank. Would an example of this be and this is something we looked at a while back in our own your own clients data, the tendency for example to when you move a rate to move it by a quarter point.
Dallas: Yeah that's absolutely a valid example of it, of you know a lot of banks are still especially for smaller deals they'll use rate sheets. And so the inclination is to put those that even round numbers. And when you do that then the users of those rate sheets as they deviate from those they also deviate in round numbers. So in quarters or eights and there's lots of room in between where the optimal pricing point may be. There's actually a few others that we talk to our clients quite a bit about in influencing their own relationship managers behavior and in thinking about how something as simple as the starting point on the screen can really matter. So the two that we talked about a lot.
One is origination fees. So there's two ways of looking at that. When you ask a user to start talking to their customer about origination fees you can start at what is typically actually achieved. So let's say that on average for a particular type of deal a relationship manager gets a quarter point, well we could start that conversation at a quarter point. The other option is that they can set that maybe at a half a point or 75 basis points, start it higher and make your relationship managers actually actively have to go in and back that fee down from where it started in PrecisionLender to a lower level. And what we find when we do that consistently is that you do generate higher origination fees, just the human nature of that's what it started out on the screen and I have to go and make it go lower. They're much less likely to do that than you know if you put it lower and expect them to move it higher, to move the profitability up.
So little nudges and behavior like that. The other one that we talk about is some banks have, especially community banks, have struggled with booking way too many fixed rate loans. And so you have the choice of starting any particular product as either a fixed rate structure or a floating rate structure. So start at floating if you want to book more floating rate loans, use this kind of inertia of defaults really matter and it tends to stick in people's behavior. Use that to your advantage in kind of shaping where you would like deals to go. So it may feel a little bit manipulative but it actually really works. And again small nudges over a lot of transactions and banking can make a big difference.
Jim: You actually hit on what I was just about to ask which is exaggerating to make a point here. But is there a little concern that you're sort of treating your RMs a little bit like rats in a maze and you're kind of tinkering around with, I mean because you know we talk a lot about RM empowerment and RM freedom and now we're talking about hey if you do this thing here it kind of forces them to do this. And if you do that it kind of forces him to do that.
Dallas: Yeah I think really the key is not to view it as tricking your RMs into behavior. Instead it is make the path of least resistance the one that you most want them to follow you know. And so another way of viewing it which the rest of our product is built around is make it really clear what the institution wants from your banker. So if we really want floating rate loans instead of fixed, let's start there. Make that easy for them. Make that the path of least resistance, make it clear that that would be our preference. The RM is still empowered to switch it to fixed, just like on the origination fees. They are still empowered to drop that fee down if they need to make the deal work. But we've made clear to them what the expectations are and what our preference would be. And then they also know what the out-of-bounds lines are, how far can I go from that starting point and it's still okay. So if you communicate while you're doing those things I think it's perfectly okay.
Jim: Well actually that was the question I was about to have is that if you start off, if you don't set your default setting at the minimum but you set it a little bit higher but then you say it's okay to go below where you set it. Does that mean you lose your floor essentially on that? You started at 75 basis points and you say but we'd really like for you to make sure you keep it above you know 25 basis points. How do you get that last part?
Dallas: Yeah I think you know you can set all those minimums as well. You know you don't have to lose those thresholds. You can still very clearly set boundaries but you can use this whole concept of you know most things stay at the default. So as an example some of the things that we measure as we're thinking about our product, we've had a couple of clients ask along the way about making new features around closing dates. So let our relationship managers do something a little more sophisticated with closing date than just choose a date on a calendar out there. And so we went back and looked at it and said well do they really tinker with that stuff that much. And what we found was that over 90 percent at the time of the deals that got priced in PrecisionLender they stayed at the default time from pricing to closing. So if you put that at 60 days over 90 percent of them would stay at 60 days for that product. So that was kind of our response was like look they're leaving it right at the default anyway if you want some more sophistication around what those defaults should be that's what we should be talking about, not what the users do.
So find those you know areas where they really need more ability to move around and where they actually are using that versus the ones that hey set it where you just need it to be because they're not going to change it that much anyway. So there is some thought that goes into where you actually make those kinds of things. But again if you communicate it well; What are the boundaries? What's our preference? And then just start them higher. They tend to stay higher. It has a little of a anchor effect to it.
Jim: Okay. We've established this is important but we've also sort of established the [inaudible 00:12:05] anecdotes that a lot of banks aren't really that good at it. So what is sort of next with this? I mean is there sort of a better solution out there? You've talked about some of the things about how you can set them but is there sort of a macro grand better way I guess?
Dallas: Yeah so this gets into what our CEO Carl, Carl Ryden describes as a wet finger to the wind problem. So if you're a bank what he suggests you do if you really want to clean up your processes and find a penny sitting around that you should be scraping up along the way. Look for where people have wet fingers to the wind. So where are they making guesses or in the context of this conversation where are they just going with the default. And so the example that we use again in our pricing world is if you're pricing a revolving line of credit where the balance changes over time you have a commitment amount but then you have an amount that that facility's actually used. So what's the utilization of that credit facility and how much it is used has a giant impact on how profitable it is.
So in other words we don't really know how to price it unless we know how much it's going to be used. So that's an area where the default is incredibly important. And yet when we asked bankers to put that number in, so most pricing systems they have utilization as just an empty box in their pricing model and they say how much is it going to be used and they put in a number. Well you can guess what number usually goes in. It's the one that makes the deal work for the relationship manager right. They reverse engineer it to be able to hit their hurdle or their target, whenever they're aiming it.
The other option that we gave administrators is that well you set the default, most of them picked a very sophisticated number of 50 percent. So as we go in and again this is another thing we went into measure most of those lines of credit were priced right at that default starting point, a few were priced at where somebody had tinkered with it to get it to work. That's not the right answer. That's a wet finger to the wind that we can solve better and the way we solve that better is through machine learning. And so this is where big data and AI and machine learning. That's kind of what's next to help solve this problem of if you've got defaults sitting there, don't have a human being making a guess at what they think it will be when machines now can be really good at seeing the context around that box that has to be filled in.
And so in our case when a line of credit pops up it's not a guess at 50 percent anymore. Instead we can use the machine learning algorithm that we've built which looks at the customer, looks at the other accounts that they have, how many deposits do they have, what credit availability do they have, what credit rating are they, how big are all those facilities versus the line of credit that we're looking at, all of those variables can be combined and so we can say based on everything that we see about this customer we think the utilization is going to be 60 percent, so we can make a more informed decision about what that starting point should be. Now again the relationship manager's still empowered, they're still a human being having the conversation with the customer so they can absolutely override that suggestion and say you know what it's not 60. We know the usage of this line is going to be really high. It's actually 85. And they can put in why they think it's going to be 85.
But the starting point is not a wet finger to the wind, it's not a wild guess, it's not even based on an average, a bank wide average of what our line of credit's typically get used. It's very specific to that customer. So that's kind of the power of data and I think that's where we're headed next to start solving this problem.
Jim: Alrighty. For now we're going to head home on this podcast. We will solve those problems in a later podcast, maybe next week.
Dallas: Alright.
Jim: Yeah. That'll do it for this week's show. If you want to listen to more podcasts or check out more of our content you can visit the resource page at or you can just head over to the home page there 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 Play or Stitcher. We love to get ratings and feedback on any of those platforms. Until next time this has been Jim Young for Dallas Wells, you've been listening to the Purposeful Banker.

About the Author

Maria Abbe

As a Content Manager here at PrecisionLender, Maria develops the messaging, stories and content pieces for prospects and current clients – showing them the value in PrecisionLender. Her passion for serving others is evident as she leads the volunteer program here at PrecisionLender. Maria’s ability to be organized and constructive, along with her ability to be practical makes her an exceptional addition to our team.

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