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Transcript

Welcome to the Insurance Leadership Podcast, the podcast designed to bring new perspectives and principles from leaders in the life and health insurance industry. We trust you will enjoy today's episode.

Ryan Eaton: Welcome back to the insurance leadership podcast where we're picking up where we left off with James Behnam from last month where we were talking about technology and artificial intelligence, we're going to be getting into predictive analytics and how companies are using this in the market.

So, a P AND C company may use this to say, Hey, you know, in this flood plain, or, you know, this, this age demographics, I know this is kind of what I'm expecting from a claim standpoint, health insurance companies.

It's easy to be able to say, Hey, historically, when someone's had diabetes, high cholesterol, by age 75, we're going to see this claim spike right here. You know, an agency may use it to kind of look at their, their data and be able to say, hey, we know once we've had these policyholders on the books 10 years, they typically will stay on for another five years and it can be handled a lot of different ways like that.

Am I understanding that correctly? Or is there, or is it much less to that? Way more than that? Help me out here. 

James Benham: You're pretty much on the money. Like, so work comp and comp your big goal is to get back to work. Right? Right. I mean, the entire goal of insurance is identification, right? Like, so let's go like bigger than that.

And that is, you want to restore the insured to the original state before the incident, right? Like that's the whole goal of insurance is indemnification. And so, the goal is to do that as quickly as possible, right? So, in a good insurance company, that's the goal is you want to pay the claim as fast as possible because you want to restore them as fast as possible because the longer, they go non restored, the worse the damage gets, right?

The more likely they are to contact and get representation. The more likely they are to have a further subsequent injury. So, if you look at health, right, you want them restored to good health quickly, because if they're not, you can have compounding injuries that make it worse. Right. And so, I think it helps us to remind ourselves of the goal in work comp.

We can use this type of data, predictive analytics, and machine learning to better identify what reserves we should set at the beginning, our treatment plan that we should set at the beginning, and our back to work strategy. The other really big one in comp that also applies to health is we need to identify inner interventionary treatments that need to be that need to occur faster.

So do we need to get them into PT faster? Do we need to get in, you know, because you know, physical medicine plays a big role. Do we need to have an independent medical exam come in and double-check that doctor, to make sure the diagnosis is correct?

You know, all of those, all of those factors need to be determined very quickly because if they're not, you end up with a much bigger claim on the health side, you end up, you end up with a two-year claim instead of a two-month claim. On the P AND C side, on a comp, they're out of work for six months instead of one.

You know, big consequences and on the property too, you know, if you don't, if you don't repair the right kind of damage first, then persistent water damage and mold, and then, you know, everything gets worse, fast. It's not long, it's not linear. It's logarithmic, you know? So that's the that's the challenge. That's where predictive analytics can help us come in and look at all the data.

All the contributing data. And then make better decisions on what reserve we set our treatment plans, our mediation plan for the catastrophe, all those things. We can make better decisions. We can make them much faster because people are, people are fallible, you know, all we're all flawed, you know, and we just missed too much stuff.

And we have to, we have a lot of biases we roll into the claim with. Right. We think that we step into a claim and they're a smoker. And so we go, oh, well, I'm going to treat this like every smoker that comes in. But what if that's not the real cause of the issue? You know, what, if there's a contributing data element on this particular claim, that's, that's a problem or, you know, in underwriting, you know, when you're underwriting risk, I mean, I, I, I really, I really constantly ask myself, are we really looking at the right data that matters that actually drives a result.

There's a lot of pressure to stop looking at credit scores now in any type of underwriting process. Right. And okay, well, how, how do we assess risk then on this particular person and brokers are going to play a huge role in this as, as all these companies try the direct model and fail.

Or they try and they have a, they have a huge loss because their, their marketing expenses exceed their, their underwriting profit. Like that's happening? You're seeing it happen. Right. That's right. There's going to be a reversion back to the broker channel, I believe, but, but only to tech-centric, broker partners that can integrate with all the new InsureTechs that are API only like you can only, you can only hit them up with an API.

You can't get a quote by submitting a PDF. And so that's right. Yeah, aspect of this, the brokers are going to have to be savvy at dealing with data and predictive analytics. 

Ryan Eaton: So I probably don't have time for this question, James, but I'd love to get a quick answer from you on the blockchain. And I have, this is something new for me in, my Mississippi mind.

I hear blockchain. I think cryptocurrency, right? And you know, we've, we've heard it coming into the insurance industry, et cetera. How have you seen this happen? What, what are you seeing with it? Is this more of a carrier-type deal? Is this, and where does this fit into our world? 

James Benham: Good point. Alright. First off. I'm not a fan of crypto. And I know that's weird for a technologist to say that. Here's why, because I'm a recovering politician. I was city Councilman and mayor pro tem of my town here in college station. Yeah, I was, yeah, I did too. I term-limited, I hit, I hit my two full terms and yeah, I had a lot of fun serving in office.

I'm currently serving as Governor Abbott here in Texas, appointed me to the board of Regents at Texas Southern University. So, I'm a, I'm a regent right now as a governor's appointee. I've spent enough years in government service to know this, that the government if it can't tax it or control it, it ain't gonna allow it to happen much longer.

And that's just the way the world is, that's just the way the world is. And so and you're seeing that, you know, crypto took a huge hit. So. You're absolutely spot on, disconnect crypto from the blockchain. Blockchain is the underlying technology that enables crypto to happen. Right. You know, Bitcoin and doge coin, just, okay.

Put that to the side. I'm not saying don't invest in it. You can invest in it if you want. That's a highly volatile, highly speculative market. And remember this, a currency is not valuable if people, if you can't buy a hot dog with it on the corner, it ain't that valuable. Just remember that the value of a currency is the purchase exchange is the ability to buy goods and services.

But blockchain is extremely valuable because blockchain is a way to have a public ledger that everyone can see, but nobody can change. It is a, it is using a, a type of encryption that allows you to encrypt things onto the blockchain and read the blockchain without changing the blockchain. It is a train where you can add a car, you know, you can add a thousand cabooses and you can't take any of them away.

You can't modify any of them. And it's public. What a wonderful place the world would be, the cha if, if we could actually handle policy data that way, wouldn't that be great. If we can all read the same policy data story. Now, the challenge is how do you restrict access to that so every trial lawyer in the country doesn't use that to immediately read everybody's limits?

So there's, there's gotta be limits and security access rights, but blockchain. The concept of having an immutable ledger, a perfect, clear digital ledger that can't be modified or deleted is very attractive to looking at policies and claims and policy history across multiple companies. If. Actually, get everybody to agree on it.

Ryan Eaton: So, James, my question for you would be if I'm a large insurance company and let's just say I'm on the P AND C side here, let's just jump to the P AND C side for a second. And I got all the data related to my clients on here, and I'm putting a lot of data in here and it's on the blockchain. You can see that, Hey, you know, I've had Sally for this long and her record has been really clean and good.

And Fred he's had a good record, but John, over here, he hadn't. And they may try to quote my good customers better than my bad customers or try to do something different. It seems like if I'm the one giving the more information, I got more to lose than the other guys, am I, am I missing something there?

Am I completely wrong? What, what does that look like? 

James Benham: You always got to worry about that. Cause you, you could end up in an adverse selection problem. You can be disrupted, right. You know there’s a, there's something I call the benchmarking paradox when people submit data for benchmarking inherently, the, and I experienced this personally when people submit data to be benchmarked and they don't like the results of the benchmarking because they're in the last place.

They're the, they're the West Virginia of the data. They end up stopping submitting the data. Most of them don't want the bad news. So, they'll stop submitting data. So then naturally you're, you're benchmarking your, your, you start receiving less and less data, right? Because I mean, like NCI has accurate data, but they make people submit it.

Right. I mean, last year, unless you're the. You can't make people submit things that you're seeing a lot of carriers demand that TPA submit an inordinate amount of data now. And are they using it? Yeah. I mean, is there a risk that when your data is submitted, that it could be, it could almost be weaponized against you or potentially, that's why there's gotta be trust and there's gotta be a mutual understanding unless you use the blockchain example.

If you're going to have an insurance blockchain, Where you have a common record among a group of companies that agree to all use the same blockchain, which is kind of how this would play out. It would be secure. It'd be password protected. It would be accessible by a group of companies. It would be hosted on a neutral blockchain site.

And then they would read and write to that ledger. So, it's just, it's an open ledger. There'd have to be an agreement on how it would be used, where it would be used, and what would happen if they break those rules. Right. Right. Because yeah, because if, if you agree to submit the data, but then all your customers that you submit data on, ended up getting non-renewed or no one will quote on them.

Yup. Then you blow it up and you're not going to submit data anyway. Right? So there's, so there's gotta be for blockchain to work. There's gotta be a rules of play. There's gotta be an agreement on how it's going to be used and what's going to happen. And how, how people, what happens when you break the rules.

You know, I'm like, Hey, you get kicked off. You can't read it anymore. Right. So you've got to follow the right rules and, and doing this, but that's really how I would see blockchain playing out is a group of insurance companies or a group of insurance brokers. That makes sense. Like, wouldn't it be great?

I mean, honestly, wouldn't it be great if there was a blockchain that, that all the brokers participated in, where you could just identify if someone was doing the same submission with five brokers? I mean, would it be, would it be great if you didn't share any information other than who the insured is, and you can just see that there's five records on that particular cause right now, the only way you find out is when the carriers tell you that you're being shopped.

Right. That's right. So, so there, so there's a, there's a blockchain benefit. There's some, there's, there's a case for the insurance brokers, the world, the unite, and to form a blockchain. So they can at least prevent from doing the repetitive work and people will shop in brokers so much. I mean, but then you gotta worry about is that anti-competitive behavior?

Are there, are there any trust issues there? I mean, there are a lot of things you have to consider, but my point is blockchain-enabled. As a technology to do that 

Ryan Eaton: look, James, with kind of the last question I got for you today, you know, I, I, when I had you on the show and got you here, usually you have someone coming to speak on technology and it's like, you know, you need to talk on it, but it's like, oh, I wonder if they're going to be any good.

I hope they got a hope that I got a good energetic personality. I get out of the park, man, I've really had a blast, but I'd love to hear from you with owning your own business for over 20 years. Now, we, you know, what has been the most valuable lesson you've learned? Maybe through personal ditches, maybe from someone else share that with us, if you don't mind.

James Benham: Yeah. My book, that's an editing right now. It's called the bootstrapped entrepreneur and what I have really learned over the years, You can do more with less than you really think. And bootstrapping has taught me that lesson, you know, starting this business with 5,000 bucks and turn it into a 270-person company has taught me that if you're really capital efficient and you focus on learning from your mistakes and making mistakes small, and you create a culture where you can learn from your mistakes, that you can, you can innovate and change and grow on a minimal budget.

You don't have to go raise tens of millions of dollars and do an, a, B and C round. You don't have to do that necessarily. There's a lot of lessons I've learned that I've kind of summed up in my book, but I've, I've really tried to focus in on the mentality and the method of how to grow a business.

And how to do it with your own resources. And the, it kinda all summed it up into one sentence. I say about halfway through. And that is a bootstrapping is about doing what you have to do so you can build what you want to build. And that's really stumping that that's really powerful because I built, I built hundreds of websites and I can tell you this right.

I did not enjoy building websites, but I had to do it. And I built a lot of software for industries that I wasn't crazy about building software, but I did it because it generated profit that allowed me to build with, and right now, I mean, I, I I'm having. I love building our claim software, Terra claim. I love building our certificate of insurance tracking software smart compliance.

I love working for our brokers, TPAs and carriers, building a custom proprietary in-house software system. It's in my whole day as enjoyable, but I had to go through years of doing things I didn't like doing so, so I could build what I wanted to build. And once we got into that, It really enabled us to have a lot more fun to build things of high value.

And, you know, we ended up selling one of our companies SmartBid three years ago. And we did the, the coolest thing is that we sold the company without selling the employees and we kept the people and then we turned them onto a new product, and we started building some more products with them and I kept my team together was awesome.

And so it really, it really is fun. Business can be incredibly enjoyable. The other thing I'll say is you gotta have a process. We use EOS entrepreneurial operating system. Believe it or not an Alabama guy can do it. Introduced. And Ken, in addition to this, this method for running a business, and you think about somebody, you and I both hate, we both hate Nick Saban hate him.

And the reason that he can keep winning when his whole staff turns over every three years in his whole player, the staff turns over three years is because he has a man he's maniacal about the process. And so you know, we got maniacal about the process about six years ago. And it's a it's Yoda, huge returns.

And you know, while I may hate Nick Saban, I definitely want to be the Nick Saban of this run software. 

Ryan Eaton: You can't help but respect the guy there. There's no doubt to that. Well, James, I can't tell you how much I appreciate you being on the show today. This has been so much fun, and for our audience listening in, thank you so much for joining.

And remember, a good plan today is better than a great plan months from now. Thank you very much.

Thanks for listening to today's episode of the insurance leadership podcast. Make sure you subscribe on your favorite podcast app, so you'll be notified of future episodes or stream online at insuranceleadershippodcast.com.