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As things are quickly changing in the world, we have Dale Larson Jr. and Dale Larson III as our guests in the Hot Topic to talk about data accessibility and how it is enhancing recruiting and industry transparency in 2022 and beyond!

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Want to know more about Dale Larson III, Founder & CEO at Modex, & Dale Larson Jr, Founder, Partner, and Investor?

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Growing And Understanding Your Team, Business, And Market With Dale Larson Jr. And Dale Larson III

It’s good to have you here. This show is created by mortgage professionals. It is four mortgage professionals and we’re so grateful to have you as our audience. When you hear the date, November 22nd, what comes to mind? For those of you that have been around for a while or study history in Dallas, JFK was shot in Dallas on this notable day in 1963. It’s not one of the better moments for Texas, but it’s also one of those dates that stand out. We all remember where we were at. Jack and Alice, do you guys remember when you were when you got the news that JFK was shot?

Yeah, I do. I think I was in third grade.

I was in sixth grade. Alice, how about you?

We’re all giving away our ages. I was three. I don’t remember.

It was a notable day, but another tragedy took place over the weekend. Our hearts go out to those in Wisconsin. It’s unimaginable. Someone is driving through a crowd running over older people, grandmas, and babies, just hearing some of the statistics on that. Our hearts, thoughts, and prayers go out to those so deeply impacted in Wisconsin. There is so much going on in the world and it rips your heart out when you hear these kinds of stories.

We’ve got a heartwarming story this day here in Austin, Texas. We’ve got Dale Larson and Dale Larson Jr. We’ve got Junior and the third joining us in the Hot Topic segment. They both cofounded and partnered with investors in Modex. We have one of our sponsors. I’m excited about it because we’re talking about data accessibility and how it is enhancing recruiting and industry transparency, especially as we look into 2022.

I am looking forward to having them on the show. There is a lot of great information that we were sharing with them. I love these two because it’s a father and son team and I love these kinds of stories. Father and son team stories touch my heart. It’s family, especially as we get close to the holidays. It’s timely that we’re going to have both of them on. It’s going to be a great interview in the Hot Topics segment plus, say we’re thrilled to be a part of the Industry Syndicate. Check out all the episodes on IndustrySyndicate.com.

Also, a shout out to our sponsors, the Mortgage Bankers Association of America. I am grateful to have their sponsorship as well as Finastra’s Fusion Mortgagebot Solution. It’s a great solution these days. Check out the episode we did with Karen Jenkins talking about UX, User Experience, and CX and their importance of that. Check that out. We did that interview on October 4th, 2021. There is a lot more coming out about that. That’s getting downloaded a lot. I call your attention to that episode and as others are reading to it and going, “What is the number one FinTech company in the world?”

Think about UX and CX, Customer Experience, and User Experience. You’ll want to plug into that. Also, Lenders One and the Mortgage Collaborative, both of these are co-ops that help you get up close and personal so you get to know other lenders or vendors. We’re part of both of these organizations. I am pleased to be affiliated with them as well as The Community Mortgage Lenders of America. As well as Insellerate. It helps lenders grow or close to the consumers that they engage with. They do a great job of engaging borrowers more effectively, developing prospects into customers, and also engaging previous customers.

Also, Ken Perry and the Nut Group at Knowledge Coop do a great job of what they’re doing at helping you Learn and Train your People. Check out KnowledgeCoop.com. Also, Mobility MMI as well as Modex. We’ve got Modex on here, but mobility, I think the two fit nicely together. They both complement each other. They both help you in recruiting. We’re going to be talking with Dale and Dale of Modex.

We are pleased that we have both of them as sponsors. Also, Snapdocs. Check out Michelle Giordano’s episode from September 13th. Our newest sponsor, SuccessKit. The most effective way to reach your audience is not necessarily through your own words but through that of others. There’s an old proverb that says, “Let another man’s mouth praise you. Not that of your own.” It’s a principle that I operate on.

Find people, talk about yourself and what you’ve done for them, and you’re going to have a much more effective way. We’re using SuccessKit both in the show as well as our consulting business. They’re doing an amazing job of collecting written-in-video testimonies from our customers and having them tell our stories. It’s the most powerful thing. Check out SuccessKit.io to learn more about it. We’re going to be talking a lot more about it in the months ahead.

Also, Lender Toolkit. We always call them LTK, but they’re known in the industry for being innovative. We are very excited about having them as our newest sponsor. Check out all the sponsors on our sponsorship page. I’m looking forward to telling you more about both of our new sponsors. A special thank you goes out to Rob, Les, Alice, Allen, Matt, and Jack, my co-hosts on the show. Also, we appreciate you being here.

It’s time for the hot topic segment of the show. It’s November 22nd, 2021. We’re excited to have to join us. Dale Larson Jr. and Dale Larson the III. Junior is the older one. Dale Jr. and I are pretty close to the same age. They live up in the Seattle area. I love father-and-son teams. I love these two and how they work together, so you’re bringing in a really important solution to the industry called Modex. We’re going to be talking and discussing data accessibility. I’m interested in the industry transparency part, especially as we move into 2020. Dale and Dale, it’s good to have you here. I appreciate you.

It’s great to be here, David. It’s fun to join the show. This is Dale Jr. I’ve been taking notes from all your other guests as Dale III looked at me. He is like, “Dad, pay attention. It’s about our turn,” but I’ve got a whole page of notes from all your other guests, so thank you.

I love the fact that you two work together and I want to share a little bit about your story. I love father-son teams, but I want to go back and circle back because it’s really good. Also, give an update on how you guys have navigated some of the dynamics that can come with a family business. Talk about that briefly.

David, thank you. There were three Dales. There was Dale, Sr., Dale, Jr., and Dale III. It was in 2012, shortly before my father passed away and said, “Dale, you and that kid of yours should do something.” It’s interesting David. This is close to our hearts. Modex is a dynamic product. We have hundreds of clients we’ve got grown, but at the core of it, it’s driven by this desire to work together in a family environment.

I had a background of 25 years in the mortgage banking space. Old school, very much face-to-face, belly-to-belly, and hand-to-hand. That kind of business model and it was Dale III, David that said to me one day, “Dad, has anybody brought a deep level of transparency to what you do?” Everything from production to types of loans to offerings that companies might have.

It was one of those watershed moments where he looked at me and said, “You can be out of business someday, dad, if somebody were really to digitize everything you do.” You and I have talked about this as well. I still believe at the core of it. There’s such a human factor to the mortgage banking space. We decided to focus not on the consumer side of the business but on the business-to-business gap.

That was essentially bringing clarity and transparency to data around loan officers and companies and building programs to help with that matchmaking. To this day, Dale and his team of developers and their market-developed team run way beyond me, but the core of it is finding good data and matching people up. It’s a family business. It’s terribly exciting.

David, in terms of dynamics between me and my dad, and this is Dale III, I’m the CEO of this business. My dad is chairman of the board and I run the business day-to-day in terms of product development, clients, and all that. He’s an incredible sounding board. When it comes to legal and board matters, he’s a great guide for me because he’s been hiring people for a long time for me to say, “Dad, what do you think about this characteristic in this salesperson?” Also, things related to the board. We have a very strong dynamic between the two of us.

I’m always looking for keys to success.

I was going to say, David, one of the things I so appreciate about you and your show is how you personalize and are not afraid to talk about the human component. Truly for us, Modex is a dynamic company. There are lots of people now working for it. There are hundreds of clients. The products that are being developed are unique. What’s in the queue is very exciting, but at the core of it, David, I hope your readers respond well to this.

Data Accessibility: MODEX is a dynamic company. Many people are working here, it has garnered hundreds of clients, and the products they are developing are unique.

At the core of it, the idea that I get to collaborate with my son, you and I joked about this. I just turned 60 and I’m telling you, nothing matters more to me than these moments with my family and my kids. Modex has got investors and venture capital looking at all these exciting things, but at the core of it, we got to work together. I know that sounds sappy, but it matters to me.

I think that’s so important. We could go a whole program into that because there are a lot of fathers and sons. Quite frankly, they do a lot better if they had their dads involved because there’s something about the experience. One of the things that caught my attention when we were talking in preparation for this is you talked about how data and recruiting can benefit the consumer. Talk about that.

At the end of the day, we’re creating less friction in the industry by providing employers and loan officers that fit into their company’s culture and operations better. Also, the other way around. For loan officers, we’re helping fit them into companies that are going to be closely aligned with them as people and how they run their businesses. Since we’re helping that and creating less friction, we’re finding that consumers have better experiences with loan officers. They are having faster closes because loan officers and operational staff are in a position where they’re less rough with each other.

That’s not exactly a great way to describe it, but when the company can hire loan officers and they have good retention of those loan officers, you have a better structure and a better operation. If you’re hiring loan officers using no data and you don’t know exactly what type of loan officer you’re hiring and you’re losing loan officers a couple of times a year, it can impact operational staff. That can impact those clients.

They may not return to you or to that loan officer that you had or maybe lost. By creating better loan officer employer fits, we’re making the process easier on the consumer and, in some cases, cheaper because there is such a heavy monetary burden to hire a loan officer and potentially lose a loan officer. We’re trying to reduce that and then it trickles down to the consumer.

One of the things Modex does that’s interesting is we measure and track everything. One of the things we’re building some models around is to track the efficiency and cost savings when there’s a better match from an employment standpoint. The cultural fit matter and we’re seeing that if you can lower the cost of recruiting if you can lower the cost of retention, the reality is that trickles down to the consumer.

It’s a measure twice, cut once hiring. That’s such a good deal. Alice, my dear friend, what are your thoughts and questions?

I’m curious about the data that you’re using. Beyond the units and the volume, is there more with MLS, consumer, and other databases?

Yes, there is. We aggregate data from dozens of sources, private and public. We also focus on what we call derivative analytics internally here. In terms of MLS data, we work on looking at what is the relationship between loan officers and real estate agents. Some companies want to hire loan officers that have strong referral partnerships with real estate agents. Other companies want to hire loan officers at a more consumer-direct base.

Where referral partnerships or real estate agent relationships aren’t as important, we also can then understand what types of properties are loan officers capable of financing. Beyond that too, it’s also important to understand who the consumers are behind these loan officers in these transactions. We’re using multiple data sets to not only understand, “Let’s look for loan officers in Seattle, Washington, that did $12 million in the last twelve months.” We might also say, “Let’s look for loan officers that have an inclination for referral partnerships or have experience servicing certain communities in our area.”

Alice, it’s a great question. Dale said we have dozens of sources. We have some wonderful partnerships with industry leaders for accessing data and are grateful for the mass amount of data available there. We’re also able to aggregate large amounts of consumer data and real estate data. It’s early stages, but for Modex, we’re working with computational mathematicians to be able to maybe predict or see patterns. The data is a little unnerving, how much is out there, but we find it fascinating when we start thinking about various products that would meet a need within the industry.

The amount of data, sorting through it, and slicing and dicing it is probably where the secret sauce is. How is data accessibility enhancing recruiting industry transparency? I love the word transparency. Allen and I talk about it all the time. Talk about that, please.

I’m going to talk about something that we’re very excited about. Traditionally, when people talk about these sorts of data, they talk about it from the perspective of a recruiter looking at a loan officer. A recruiter says, “I’m looking for loan officers within a certain geography,” or, “I have a job application now and I now have a loan officer that I’m interested in talking to. I want to look at their production.”

That’s important and that continues to be important. That’s what we’ve generally served here at Modex. Now, what about if we flip it the other way around from a loan officer’s perspective? A loan officer is out there looking for jobs. They get offers from maybe 3 or 4 branches, but they maybe get similar offerings. They want to know more about that branch.

What about if I could tell that loan officer now, “This branch has hired or lost this many loan officers in the last quarter or year or last month.” Besides that, I could also say, “The average loan officer that gets hired by this branch, within six months sees a 10% increase in their production for new hires.” We’re not now saying, “Let’s make the industry transparent for recruiters. Let’s now make the industry transparent for loan officers.”

We’re trying to continue along the path of building excellent employer loan officer fits. It’s not a one-way street. It’s not a “The recruiter is excited about the loan officer.” We want it to be the other way around too, where the loan officer says, “I’m excited about working for this company because of X, Y, Z reason.”

It’s an alignment issue. It’s helping them connect. I like that. Jack, over to you, my friend.

First of all, Dale Jr., I’m glad you were taking notes earlier in the show. I wrote down one thing, Dale and that is Alice writes down a lot of things. I went up to your website and took a look at it. One thing that struck me as extremely beneficial is injecting a certain amount of reliability into the data. I’m quoting your website, “The internal quality assurance and quality control process takes the data a step further.” Can you talk a bit about the benefit to an audience with accurate and reliable data to assess the right fit loan officer for their organization?

The data has always been available. It’s out there, and over a 30-year career, I’ve purchased data. I’ve acquired data. There are a couple of things about it and it’s back to that. It was hard for me prior to being able to use a tool like Modex to validate that the information was accurate and to compare it against other data sources. We also will have, for instance, actual users and perhaps loan officers. We will also validate their data and compare it to the public data we have.

There’s an assurance, and from a hiring standpoint, the idea of being able to make sure that what is being represented is very significant to me. The other thing that we find fascinating is that when you talk about millions and millions and millions of bits of data, and if you’re thinking about getting that on an Excel spreadsheet, it’s difficult to wade through it and capture. I’ll give you an example. I hope this helps.

We’ve also had a dialogue with a computational biologist, which is fascinating. Why are you talking to a computational biologist? What’s interesting here is that when you’re looking at things related to the DNA and sales structure, the data’s there, but unless you have programs to extract it and put it into a meaningful fashion, you may miss something. Modex is doing that with millions of bits of data around all sorts of data. I think part of it isn’t only the validation of the data. It’s how the data is presented. I hope that answers your question.

Dale, it also answers the next question. I’ve heard you talk a couple of times about the immense scary amount of data that’s out there and that’s a great thing, but I’ve watched people. I’ve watched the processes. I’ve watched organizations suffer from data paralysis. It looks like Modex has a very fast user-friendly ability to enable clients to drill quickly to the set they need to make the right decision.

I think that’s an accurate representation. That was perfect. I want to say something that ties into this, though. The industry is large, and somebody said to me who was an investor or a venture capitalist, “This is very disruptive to the industry.” Everybody talks about disruption. Here’s the thing. We say this internally. We don’t want to be disruptive for disruptive sake. What we want to do is want the information to enhance this matchmaking process because here’s what we’re finding.

The hundreds of clients we have now are some of the best in the industry. The accessibility and clarity of data cause the best to rise to the surface or also create an incentive for others to improve their offering. When we also come full circle, we see the industry, those that are leading the way, stepping up and willing to say, “Absolutely, let’s have data available, and let’s make it visibly apparent.”

I want to get to one of the things we’re seeing more and more. We’re hearing a lot about artificial intelligence. We’re hearing about machine learning and predictive analytics. From your perspective and from what your business does, I’d like to have you explain what this means for mortgage banking, specifically recruiting.

Predictive analytics and machine learning are when machines and computer software are trying to make guesses on a certain data set at a certain level of confidence. Essentially, one of the things that we’ve been working on and that we’ve been hiring for is understanding when. This is going to sound absolutely crazy to you and all of your audience, but this is something that we have been working on trying to predict when a loan officer is going to change jobs before they even say it.

By looking at all of the variables that we have available to us, like real estate data, licensing data, loan officer, production data, and consumer data. Tying that all together to then say, “We have a confidence score of 80% or whatever that this loan officer may switch jobs within the next 3 months, 6 months, etc.” These sorts of models already exist. They already exist in the space of consumers. There are scoring algorithms out there to guess when a consumer is going to buy a new house or move to a new rental property.

We’re applying similar models to our data sets to say, “How do we anticipate this company is going to perform in the future since they’ve been hiring loan officers or losing loan officers? Where have they been getting a license, etc.” Also, all the way down to the loan officer, “There’s functionality in Modex where loan officers can come claim their profiles and indicate they want to talk about job opportunities.”

That’s a very definitive action where a loan officer says, “I’m putting my stake in the ground saying I want to talk about new job opportunities.” There are lots of loan officers that also have not claimed their profile yet. We want to look at all of the data that we have available on them and say, “Who’s going to switch jobs?” That’s a two-pronged thing too. It’s where, “Let’s look at which loan officers are going to probably go to be switching jobs soon,” but secondly, from a company retention standpoint. Imagine if we could tell a company, “You need to look at this loan officer, these branches, or this territory because Modex has an indication that you might be losing loan officers in this area soon.”

Data Accessibility: MODEX can indicate that you might be losing loan officers in a particular area soon.

If you think about it, Jack, if you could have that kind of prediction and look at who might be moving, especially if you’re looking at recruiting and look at the competition across the road, that is so significant.

I joke about it. I say the future is scary. I mean that in an exciting way across many facets of the world, but it is a little even me running this business. It is a little odd saying, “I’m going to be able to predict when someone’s going to switch a job. It’s exciting, though.”

Predictability is in the data and that’s what you guys specialize in. I am getting some questions from our audience that I want to share with you. Talk about the biologist. Go back and talk about that a little bit. What was behind that a little bit more?

That’s a great question, David. I appreciate the clarity. For clarity, we have not engaged or hired a computational biologist to work for us. I’m talking about a PhD in computational biology. Can you imagine a human genome? Think about the amount of data there and they build models to predict outcomes for medications or for treatments or new drug trials, but there are massive amounts of data points related to a loan officer, to a company, or to a consumer.

How about the buying patterns of a potential homeowner? How about the buying patterns of a loan officer? Also, could you apply some of the same modelings that are used in biology to predict? It’s back to the idea Dale spoke of machine learning and the idea of predict outcomes by looking at large amounts of data. We thought, “Why would we stay in a lane of only looking at things that are mortgage-related? Why wouldn’t we look outside of the mortgage-related industry and say, “Are there other mathematical models that could be deployed and benefit the data transparency in the mortgage industry?” It’s us being very creative, David.

I want to put a quick note on top of that. Maybe I’m almost summarizing it and I’m sure if you have any audience right now who have backgrounds in machine learning, I’m probably going to get an email from them but machine learning is machine learning. Now, that’s a general statement, but the pharmaceutical industry has been using machine learning to predict pharmaceutical trials for decades at this point. They are using massive amounts of data and they’re using it for health purposes and so they have to be very careful about it.

Now, in the mortgage industry, Modex recruiting, etc., we’re now starting to dip our toes into the machine learning pool. We’re now going to the folks that have been doing it for ages, the pharmaceutical industry with tons of data for health reasons and we’re now saying, “You guys have done this well here and you’re good at it. Now, let’s apply the same machine learning. Not the exact same models, but similar tunes now the mortgage industry.

Data Accessibility: MODEX is now starting to dip its toes into the machine learning pool.

This could open up a whole new world of how we look at our businesses and who we’re doing. It’s getting the right people on the bus and getting the right people off the bus, going back to that book Good to Great by Collins. I think it’s such an important tool. You have a great product. You’re doing a great job in the industry and I love the innovative approach. Data is data, but it’s what you do with it and the tools you use to sort through it all. I think that’s a bit of your secret sauce. In addition to the father and son team, we have run out of time, so how can people get ahold of you?

You can visit us. It’s very exciting. Since our last update on this show, we now own Modex.com. It’s easy for people to remember. You can visit us at our old domain, ModexConnect.com, or now you can visit us at Modex.com. If you’re interested in learning more about our product, I would suggest reaching out to [email protected] and we’ll get back to you real quick with a demo or a trial or tell you a little bit more about what we’re doing and who we are.

I encourage you to do so, readers. Be sure to check them out. They do a great job. We have so many of the clients we’ve turned on to Modex. Thank you so much. I’m so grateful to have you as our readers. We’re grateful to you. I hope you have a great Thanksgiving holiday. I am so grateful for our sponsors, Finastra, CMLA, lenders One, Insellerate, Mobility MMI, and Modex, whom we’ve heard from on this episode. The MBA Knowledge Coop, Mortgage Collaborative, and Snapdocs, as well as SuccessKit and Lender’s Toolkit.

We’re going to be having next week on Brent Embler with Lender’s Toolkit, talking about some of the latest and greatest things. This is one of those companies that snuck by me. Once Brent moved over to the company from Velma, he was all excited about it and now I know why. We’re going to hear all about it next week. A special thank you also goes out to Jack, my co-host, as well as Alice, Allen, Matt, and all of you who make this show. I look forward to having you back here next week and sharing this show with others. I appreciate it. Bless you.

Important Links

• Modex
• IndustrySyndicate.com
• Karen Jenkins
• Lenders One
• Mortgage Bankers Association of America
• Finastra’s Fusion Mortgagebot Solution
• Mortgage Collaborative
• The Community Mortgage Lenders of America
• Insellerate
• KnowledgeCoop.com
• Mobility MMI
• Snapdocs
• SuccessKit.io
• Lender Toolkit
• Good to Great
• ModexConnect.com
• [email protected]