Winning Tactics of Top RMs: Scaling Best Behaviors

How do you tap into the value of your top RM's behaviors? What should you measure? How do you do measure it? And how do you scale that knowledge? 

Gita Thollesson addresses all these questions on this episode of The Purposeful Banker. 

   

Helpful Links

Applied Banking Insights: Using Data to Drive Growth (Bank Director presentation)

RM Performance: Measuring and Scaling

Bank Director Bank Board Training Forum 

Gita Thollesson's Market Insights content

Applied Banking Insights Overview

Why Your Best Lenders Matter More Than You Know

Podcast Transcription

Jim Young: Hi and welcome to The Purposeful Banker, the podcast brought to you Precision Lender, where we discuss the big topics on the minds of today's best bankers. I'm your host, Jim Young, Director of Content for Precision Lender. I'm joined again today by Gita Thollesson, Precision Lender's SVP for client success and market insights. Regular podcast listeners will know that, when Gita's on the show, she's often here to talk about what separates the best RMs from the rest.
 
Today is no exception, but there's a bit of a twist. We're going to start off by talking a bit about a presentation Gita recently gave at the Bank Director of Bank Board Training Forum in Nashville. It's really about laying the ground work for how your bank can really found out what its best RMs are doing and, most importantly, turn that insight into action. Then, in the second half of the podcast, we're going to dig into some of those examples. You can see what it looks like in the real world. Gita, welcome back to the show.
 
Gita Thollesson: Thanks, Jim. Good to be here.
 
Jim Young: I don't want to completely rehash your presentation because that video is going to be up on our site, as well as a really good blog post, which does some summarizing and also adds some new material. Let's just start with the title, Using Data to Drive Growth. That sounds to be blunt, a little obvious, right? Who doesn't want to use data to drive growth?
 
Gita Thollesson: Sure.
 
Jim Young: Why did you feel the need to speak on this, and what was your different take on that?
 
Gita Thollesson: Well, Jim, easier said than done, using data to drive growth. It's something that I've personally struggled with throughout much of my career. It's not just a matter of producing great analysis, but it's also a matter of collecting the right data to develop the right insights, and then having a process in place to take action and on the insights to actually improve performance. What I've seen over the years working with banks is that there's no shortage of data. There's no shortage of reports, but usually where banks fall short is in actually doing something with the data and sort of developing the right insights and then having that process to improve performance.
 
Jim Young: Again, I will have a link up later in the week to the actual presentation in which Gita is actually pretty honest about where you struggled with this in your career and where you tried this and this didn't work and then tried this and this didn't work-
 
Gita Thollesson: Right.
 
Jim Young: But can you talk a little bit about where you've arrived at now, in terms of a process that you do think works?
 
Gita Thollesson: Yeah, well, sure. It's been an evolution. I'd say early in my career working with commercial banks, it was a matter of developing insights on the data. Sometimes commercial banking data wasn't so easy to collect, but go through a process of collecting that information and figuring out how the bank was performing and developing some recommendations. Quite often when we did that type of analysis, the banks would love it, but they would do nothing with it. A year would go by, and the results would be the same because the data really wasn't acted upon.
 
The way that my thinking on this has evolved over time is you've got to do that analysis, do it quickly, but then make it actionable. In my prior experience, prior to joining Precision Lender, I think I had figured out how to do that.
 
The only challenge was that it was a very slow process. Sometimes we'd have to wait for a deal to close. We'd then collect that information, take a couple of months to do the analysis, provide some recommendations, implement those recommendations, then go back and see if it worked. That whole process could just drag on for years, really.
 
I think we're on the right track in terms of needing to act on the data, but what I've come to realize since joining Precision Lender is that there actually is a way to fast track that feedback loop. It comes down to collecting data earlier in the process, not waiting for deals to close before you actually collect that data. It's also a matter of collecting the right kind of data, so behavioral data rather than just outcomes, and then turning that into coaching for bankers.
 
Jim Young: You talk about gathering data and banks are ... sometimes have big analytics-
 
Gita Thollesson: Sure.
 
Jim Young: Teams or that sort of thing to actually generate the insights. Can you talk about sort of that critical last step area?
 
Gita Thollesson: Yeah. Absolutely. There's really no lack of talent at banks in terms of analyzing the data, drawing insights from the data. Really that last mile is the piece that's missing quite often, and that is taking those insights and using those insights to coach bankers to a better result. If you identify certain best practices, some things that your star performers are doing, how do you take those behaviors and then use that information to coach other bankers to a better outcome?
 
I think a lot of times bank executives will say, "Well, it's just I've got some real super stars. They're very talented." I think, at the end of the day, there are some skill that are embedded into the behaviors of these RMs and those are skills that can be leveraged. Figure out what those bankers are doing and then you use that information to coach the rest of the team.
 
Jim Young: Again, for our listeners, if you want to really dive into the how to on this in this sort of fly wheel effect that gets created from doing this, once you measure those best practices, you analyze them, you generate that insight, you coach them to do it, they do it better the next time, you get better data. All of that is really laid out eloquently in Gita's presentation. Again, there is sort of a quicker version of that in her upcoming blog post. Again, today, what I wanted to get into was those actual behaviors.
 
Gita Thollesson: Mm-hmm (affirmative).
 
Jim Young: In your presentation, you go through a lot of different types of data that you can gather.
 
Gita Thollesson: Yep.
 
Jim Young: You said the most important one, or the one you really focused on, was behavioral data. Why that one versus all the other types?
 
Gita Thollesson: Well, when you look at the typical reports that most banks have, the reports are all results. Probably one of the most common reports that's out there is going to be some form of a loan production report. Every bank has some form of that report, whether it's new and renewed deals or the total book sliced and diced based on the bank's organizational structure. It'll show what the bank has put on the books. From that report, you could see who's doing well and maybe who has not done so well, but what you don't see is the behavior that led to that outcome.
 
You don't see what were the actions that the bankers took that led to such great production numbers. You don't see were some bankers really proactive in reaching out to customers. Were others simply responsive to an RFP, or just reaching out at a time that they a deal coming due or ready for renewal? It's the behaviors that explain the outcome.
 
It's only by understanding those behaviors that you can then say, "Well, what do we need to do differently? What sorts of actions do the other teams need to take, the teams that have not done so well, to get to a better result?" It's that behavioral data that we tend not to get. That data doesn't exist in the system of record. It's not in the loan accounting system. It's not stored in the back office. It's behavioral data, really, at the time that RMs are initially talking to customers. They're pricing and structuring deals. That's information that's really only recently begun to become available with the use of cloud-based technology.
 
Jim Young: All right. Let's get into a little of the nitty gritty here and some of those behaviors and how you would go about measuring them and learning from them and turning them into better results.
 
Gita Thollesson: Sure.
 
Jim Young: Let's start with RM behavior around last year's tax cut. Do you mention that in your presentation, I believe? What exactly could you learn from that?
 
Gita Thollesson: Well, there was a bank that I was working with at that time. It was early in 18, right after the tax cut went into effect. The bank was struggling with whether or not they should lower the tax rate in their pricing tool, the RAROC model. What they decided to do was to go ahead and lower it and keep the hurdle exactly where it was, and then go back after a few months, after the deals that their bankers were working on had closed, and see what the behavior was and see if their bankers were solving for the minimum and essentially giving back the full benefit of the tax cut to customers, or if they were doing the right thing and still maximizing pricing.
 
Hearing that, it just sounded like total madness because, if you think about it, from the time that an RM starts working on a deal til you get to closing, that could be months. Then, by the time you collect that data and analyze it, that's maybe another couple of months. To think about the potential revenue that the bank could lose, the profitability they could lose, by going through that very long, drawn out process. The better approach is, using cloud-based technology, you roll out the lower tax rate to a group of RMs. Keep it where it is for another group of RMs.
 
Instead of waiting for the deals to close, you basically look at the behavior. Look at what pricing the RMs are proposing in the two different groups, and well in advance of when these deals get to closing. You measure to what extent are people solving for that minimum. Then you can adjust very, very quickly. You can say, "Okay. We're going to either not make the change to the tax rate, or we're going to make it, but maybe bump up the hurdle, or the target." You can take action very quickly. All of that can done long before these deals ever close 'cause you're observing that RM behavior as it's occurring instead of only after the deal's been booked.
 
Jim Young: I'm going to ask what may be an obvious question here, but you'd have to have a system, though, that is capturing all of that, like you said, not just, "Here's what happened if the deal closed."
 
Gita Thollesson: Right.
 
Jim Young: But just capturing all of the actions that are taken, even if it doesn't eventually lead
to a closed deal.
 
Gita Thollesson: That's exactly right, Jim. What it comes down to is you've got to start with tools for your bankers that they actually want to use, tools that are helpful to them in doing their business.
 
Really, a great CRM tool, great pricing and profitability system, because when you can deliver those tools that are helpful to RMs, then they want to use it. They use those tools in the process of doing their job and then you're able to, very passively, collect that behavioral data. You're not asking people to type in a bunch of data into a form. You're essentially just letting them do their job. You're sort of riding shotgun with them, observing what they're doing, collecting that data passively. What happens is that the more and more these bankers use these tools, the better and better the data gets. When the data gets better, the insights get better. When the insights get better, the coaching gets better. Then, as the coaching gets better, the system becomes that much more valuable. People use it more and more and this feedback loop, or fly wheel, just keeps spinning faster and faster.
 
Jim Young: Great. Yeah. I guess for our listeners, again, that's sort of the context. I should've mentioned that before we got into the first one, but I got excited about getting into all the different behaviors, but that is sort of that context here if you're wondering, "Well, wait a second. How would you know this?" You've got to have that sort of in place. For the purposes of this discussion, with that sort of system in place, what could you do? We mentioned the tax cuts.
 
Another one here is: Are your bankers or your RMs doing a good job of presenting alternatives out there when they're having their pricing and deals discussions with their clients? How would that work?
 
Gita Thollesson: Well, one of the best practices that I've seen working with many different banks is that the best RMs will really do a good job identifying what's important to the customer. Sometimes the way to identify what's important is to present them with a couple of different options. Sometimes, if a banker ... let's say the borrower pushes back on a high spread. Some bankers will just be inclined to cut the spread. Others will say, "Well, you know what? Maybe they're rate sensitive. Maybe we could do something a little bit more creative where we cut their rate but add a fee. Or, maybe it's really more about structure. We can give them something really competitive in terms of the term or the amortization and then balance that off with a lower spread." Those are some of the behaviors that the best RMs engage in, but those are all behaviors that you can actually see in the data.
 
In your pricing and profitability system, you could measure to what extent RMs are actually coming up with these different options. How often are they presenting two or three or four different choices for the borrower? When they do that, what are the results? Are those RMs winning more deals? Are they getting better pricing? You can even measure, specifically, what the different options are. Are they pricing options? Are they structure? Is it cross-sell? All of those different things can be observed in the data.
 
Jim Young: Maybe you could actually find out sort of what the magic number is on it, sort of that point between either A, not giving them enough alternatives, or B, overwhelming them with choice. Maybe there's something in the middle.
 
Gita Thollesson: Yeah, absolutely. It's the exact same issue when it comes to calling efforts. I think we all know intuitively that you've got to call on your customers a little bit more often, but there can be such a thing as too much outreach. People don't want to be annoyed by a call from you every week, especially if you're just emailing them about the weather or sports and not really adding any value. Yeah. You could absolutely figure out from the data what that magic number is.
 
Jim Young: Yeah. As someone who is in marketing, I will admit that sometimes there can be such a thing as too much-
 
Gita Thollesson: Yep.
 
Jim Young: Outreach, as much as-
 
Gita Thollesson: Absolutely.
 
Jim Young: I hate to admit. This one, here, on the list was ... I'm curious about how you would measure this. It's proactivity.
 
Gita Thollesson: Yep.
 
Jim Young: I guess I'm curious about that because it seems like the other one is sort of an absence of it. How do you measure this? What are you talking about, again, and how would you measure it?
 
Gita Thollesson: Well, what I'm talking about when I say being proactive is when RMs are not simply responding to an RFP, they're not waiting for the customer to reach out with a request and instead, they're taking that first step in going to the customer, talking about their business, talking about their goals, and then figuring out if there are things that the bank can provide to help the customer achieve those goals, are their solutions that the bank can bring to the table to add value. That is something that you can track in your CRMs. Obviously, depending on what data you're collecting, you could look at the date that your deals are coming up for renewal.
 
How far in advance of that date did the RMs reach out? How often did they reach out? If you're collecting the right data, you could sort of figure out what the content is. Is it simply that the RM is responding to something that the customer asked for, or did the RM take the first step? That's absolutely something that you could measure and then you can correlate that with the RM success in winning business and as well as getting good pricing, good cross-sell.
 
Jim Young: Now we've got a few more of these to go through, but I'm also sort of thinking actually, and it's something ... a lesson I should probably take, too, but if you're setting this sort of thing up and saying it, do you have sort of an idea in mind of how many of these you should do, 'cause it seems like you ... this is a wonderful area, but it also could be a rabbit hole in terms of if you were suggesting to a bank, "Hey, I want you to start measuring these behaviors." Would you tell them measure three, or measure four, or measure this particular areas? How would you sort of go about giving them the initial steps so that they don't go overboard?
 
Gita Thollesson: Well, it's hard to say that a bank could go overboard in this because we're not talking about a manual process. In my prior life, doing analysis was a manual process because you had to take the data and run analysis off of it. These are things that you can automate, in effect. These can all become push button, using the technology that's available out there. What I would suggest is you start by looking at the outcome. Take those RMs that have won more deals, gotten better yields, gotten more ancillary business, and then you run a bunch of analysis to see what those bankers are doing and look at the behaviors that are embedded within the data. Certainly not everything can be captured, but quite a bit of it can.
 
Jim Young: Okay. All right. This is an area where we've spoken quite a bit about this on this podcast, and you've had a really great webinar on it, pricing renewals and pricing renewals well, I guess would be the ... what you're hoping for. Again, what are you looking to measure here? What are you looking to scale?
 
Gita Thollesson: Well, there are several best practices around renewal pricing. One that I found pretty interesting that actually is measurable, it's a story that we talked about in the last webinar, which was a story of a bank that was trying to figure out how much was too much. How much of an increase on a renewal would just encourage the customer to shop the credit and would jeopardize customer retention?
 
This was a bank that actually engaged with a consultant company and it was a pretty expensive engagement to run this pilot and to ask RMs to present higher pricing to the customer. All of that analysis, which sort of went on for several months, finally led to the conclusion that you don't want to ask for more than a quarter point.
 
If you think about it, going through that extensive pilot program, and I can only imagine how much that bank paid for that study, those are all things you can observe in your own data. If you see an RM propose a higher price, you could actually see exactly what they proposed. Then you can tie that back to your CRM to see whether the deal was won or lost. We certainly see that in our data after the fact. We can see that banks that charged a much higher premium on renewals, let's say bumped up pricing by half a point or a point, tended not to do as well as the people that just asked for a quarter point or less.
 
Those are observations that every bank can make on their own. The specific number may vary, depending on where you are in the market. Maybe larger borrowers, it's an eighth of a point and smaller borrowers, it's a quarter point or maybe a little bit more. Those are all things that can be observed in the data.
 
Jim Young: Again, the way that this would work is that, essentially, you would have this delivery mechanism so that, let's say that your pricing renewal and it's at a threshold of a certain size where you would be able to tell the relationship manager at that moment, "Hey. For the deals of this size, ask for this range," basically, or, "Ask for this number," or, "Don't exceed this number." Is that basically sort of how that would work?
 
Gita Thollesson: Well, that's exactly right, Jim, because now you're getting back to the feedback loop and that last mile that we talked about. It's not just about identifying the right behaviors, but then it's taking that data and then using that to coach other bankers. In this example, when we talk about renewal repricing, you observe what the right tipping point is. How high do you go without encouraging the customer to shop? Then the next time that an RM is pricing a renewal, and maybe they're setting the bar a little bit higher, that' when you coach them right at that moment and say, "Wait a second. Instead of asking for 50 basis points, I think you're better off asking for 25."
 
You use that data to coach those other bankers. Those bankers have more success, then, in winning that piece of business. Then it gets them using it and getting better and better coaching. You've got to close that loop.
 
Jim Young: Well, again, and just thinking through how the nonstop nature of that loop would
allow you to recognize market shifts as well-
 
Gita Thollesson: Sure.
 
Jim Young: If you suddenly realize that, "You know what? We told them don't charge more than 25, but we were actually ... our renewals have dropped down, so maybe we now need to shift it to 20-"
 
Gita Thollesson: Yeah.
 
Jim Young: Or maybe you say, "Gosh, we renewed 95%. Maybe we actually need to be asking for more now-"
 
Gita Thollesson: Exactly.
 
Jim Young: It's not a one time, this is what you do, and then later on we come back. It's constant. That's the beauty of it.
 
Gita Thollesson: That's right. You just don't do a one time study and then walk away. It's got to be evolving as market conditions change.
 
Jim Young: Yeah. This is an oldie but goodie, one that we talked about, gosh ... I want to say we talked about it in our Bank of Last Resorts White Paper a couple years ago, but the practice of pricing in nonstandard increments. This feels like something that Dan Ariely might've written about because it seems fascinating behavior to me, behavioral psychology almost. Talk a little bit about that.
 
Gita Thollesson: Yeah. That's, again, something that's really easy to observe in the data. Bankers have a tendency to price in very standard quarter, or even half point, increments. The RMs who are more successful at winning business and also maximizing profitability use those interim price points. If they've got a competitor that's out there pricing at LIBOR plus 200, instead of going down to 175 maybe they go to 190 or 185. The flip side of that is when they know that there's value that they bring to the table, something that the customer really puts a lot of value on, then maybe they try to bump up the pricing, but not so high as to encourage the customer to shop.
 
With that same example, maybe they go to 210 instead of 225. That's something you can see in the data. You can actually very easily measure the use of these nonstandard pricing steps and pricing in between the quarter point increments. Then, the next time you see an RM that's pricing a deal, maybe it's a longstanding relationship and maybe they're sending a price of 250 over LIBOR, you can actually observe how much business the bank has with that customer, how strong a relationship it is, how long it's been in the portfolio. You could coach them and say, "You know what? I suggest you try to get 255, or get 260, instead of 250." Again, you're taking that data and using it to coach bankers to a better outcome.
 
Jim Young: This one is pretty broad here, so I'm curious how you're going to sort of frame it, but, "Measuring tailored loan structures." What does that mean exactly?
 
Gita Thollesson: Well, I've seen, especially on the middle market side, one of the ways that RMs differentiate themselves from the competition is by customizing the loan structure to meet the customer's needs, and ... so doing something out of the box. One example might be, let's just say, a longer amortization. Maybe it's a customer who's got some challenges around cashflow. It's not just about the price. It's more about what their payments are going to be. The RM may say, "Okay. I can even bump up the price, but then extend the amortization and lower your payments." That can be something that resonates with the customer.
 
Or, I think on one of our earlier podcasts we talked about a hotel who really needed seasonal payments, so during their slow period it was going to be interest only, and then during the busier period they could pay off the principal. Those are things those tailored loan structures you can observe in the data. You can see which deals deviate from the norm. Are there some opportunities to coach other bankers to maybe present some different options, and specifically, what are those options? What does that look like to be a little bit more customized? That could come down to presenting a couple of different alternatives and one of them may be a suggestion, "Hey, I suggest you maybe bump up the rate but then extend the term." We're indifferent as a bank between those two different options. We're going to get to the same result, but maybe one will resonate with the customer more than the other.
 
Jim Young: Finally, this is the buzziest word. I swear every time I feel like I have a conversation with a banker we're talking about noncredit business these days.
 
Gita Thollesson: Yeah.
 
Jim Young: What you mentioned here was the timing of noncredit business, or I guess the timing of when you try to add noncredit business. What would that look like?
 
Gita Thollesson: Well, I know one commercial executive that I'd worked with for many years always said that if you don't get the ancillary business upfront, you're never going to get it. I don't know that everybody would agree with that. Maybe it's a little bit extreme, but I do think that there is an issue where bankers will quite often expect to win that business. They plan on it. They bake it into their estimates when they're looking at [inaudible] profitability on a proforma basis. Then, ultimately, that business doesn't materialize.
 
Timing is really important. You can observe in the data whether RMs are negotiating that business upfront. That can be very compelling. If you say to your borrower, "Look, I can give you this great rate on this loan that you're looking for, but I need to have those deposits moved over before closing." Once you've gotten to closing, it's almost too late. At that point, what incentive do they have? They've certainly made that promise, but there's really nothing to lose at that point.
 
You can observe at what point do the bankers actually get that business moved over? If they don't get it to closing, what are the behaviors that ultimately lead to success? Do you have some RMs that are actively tracking that business that's been promised and following up with their product partners, following up with the customer to make sure that that business moves over? Versus, do you have other RMs that maybe put in the system that they're expecting that business but they never really took any steps, never exhibited any behaviors, so to speak, that led to any improved performance?
 
Those are all things that can be observed. Then, what you can do is you can give those RMs that haven't been so successful little nudges. You can essentially coach them and you can ... whether it's a little popup or maybe it's an email that comes across their desk that says, "Hey, you've got some business out there that hasn't yet come into the bank. Suggest you follow up with this particular customer or follow up with your product partners." Again, it's not just a matter of figuring out what the best RMs are doing, but it's taking those behaviors and using that to develop coaching for your other RMs to help them get to a better outcome.
 
Jim Young: Well, again, as always when I record podcasts with Gita, I find myself wishing we could go for a lot longer 'cause there's just so many different areas that she has so many interesting observations and, a lot of times, anecdotes to go along with them, but we're going to wrap it up for now for this week's show. Gita, thanks so much for coming on.
 
Gita Thollesson: My pleasure, Jim.
 
Jim Young: Now for a few friendly reminders. If you want to listen to more podcasts or check out more of our content, visit our resource page at precisionlender.com, or you can head over to our homepage to learn more about the company behind this content. Want to remind our listeners, also, that Gita has a Market Insights newsletter which has content in this vane that I would encourage you to subscribe to. I'll include a link to that in our podcast notes and would encourage you to be on the lookout for that. It's going to be coming out I guess mid June, so probably in a few days after this podcast recorded. Finally, if you like what you've been hearing, make sure to subscribe to the feed in iTunes, Sound Cloud, 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 Gita Thollesson. You've been listening to The Purposeful Banker.

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