Ep 42: Bryan Falchuk on AI, Claims, & What Happens When a Knowledge Business Has to Reinvent Itself

speaker-1: AI is reshaping every corner of the insurance industry. Today I'm joined by Brian Falchuk, president and CEO of the to explore how carriers are adopting AI, the risks and opportunities ahead, and what it all means for agents and brokers. Enjoy the show. Hi, and welcome back to the Enlightened Agent, the podcast that brings you conversations with top insurance professionals and industry leaders.

My name is Jason Keck, and we are on the fourth series of The Enlightened Agent, a show that is entirely focused on the hottest topic in technology and business right now, artificial intelligence. Today I'm joined by Brian Falchek, the president and CEO of the PLRB. Brian, welcome to the show. Excited to have you, excited for the conversation, excited to pick up speaker-0: Thanks for having me on.

speaker-1: on where we left off a few years ago, I met Brian, I can't remember how long. Coup a couple of years back. ⁓ and and and I've always known him as as an author of some fantastic books about the industry we were talking about. ⁓ one of his books that that didn't quite come to fruition, but we got to know each other and got connected and but but you're doing something new these days, Brian.

So I figured we'd kick off the show with maybe give you a chance to introduce what you're up to now and tell our audience what you're doing. speaker-0: Yeah. So ⁓ first of all, I'm not an enlightened agent, so I feel like there's a little bit of imposter syndrome. And second of all, I think it was twenty twenty one.

You guys, Broker Buddha was gonna be in a distribution focused book in the future of insurance series. Well deserved, and I got pulled in another direction. and you gave me a bunch of your time to understand your story, which was amazing. So I would still like to do that, but I'm also being dishonest with myself if I think I have the time to write it right now.

Or focus. Yeah. So PLRB is a a trade organization in the insurance industry, which I think outside of insurance ⁓ audiences would be the end of the conversation. People like, all right, that's I've heard enough.

But we are worked here for P and C carriers. We've been around for about seventy-five years. ⁓ and we support them in the delivery of coverage, which is a really fancy way of saying claims. ⁓ it's not that fancy, but claims.

Like we're there at the coal face supporting claims adjusters in doing their work. Number of different products and resources that we provide for them. And if people know who we are, which I know is not many people, but in our space, they would generally, when they say PLRB, they're probably referring to our one biggest conference. We run a number of education events and that conference is massive.

It's like thirty five hundred people. You know, our c our expos get like cranes and rigging and all that during setup. And we run about a hundred classes over four days. We run each one twice, helping adjusters kind of bang through all the CE requirements that they need for the year.

Okay. That's a great event. speaker-1: So con I guess considering our audience is primarily ⁓ insurance agents, what you know, what if they don't know about PLRB, why why should they care about who you are and what you do? speaker-0: Yeah, I mean, so my background is is broader in the industry.

I've kind of always been carrier focused, but ⁓ you know, as a chief claims officer, I was a COO for another carrier. I spent like ten years in specialty lines, twenty-five plus in PNC as a whole. And some of that includes distribution, where I ran a trading team and then I I ran distribution or built distribution for a British specialist carrier, ⁓ you know, building in the US. And so that means I spent a lot of time, you know, out in the field meeting with brokers and I've done a bunch of consulting projects on distribution before, so lots of like local insurance agent visits and interviews.

So it's it's a space I care about. ⁓ I speaker-1: You know some you know some enlightened agents probably then. speaker-0: You probably I've definitely met a few and I've been a defender of it when the whole ⁓ I'm not gonna name them, but in InsureTech was coming out at an insure tech insurer, kind of bashing the whole distributed model or the intermediate model as being stupid and a waste of money. And they're like, ⁓ we can do this for free with great tech.

Like, that's awesome. Distribution ain't free, even if you don't have a person. Google AdWords are pretty expensive last I checked. And yeah, they quickly learned their lesson and and pivoted.

And and I think that's why you see like the kind of intermediated versus direct sold mix is basically two rectangles sitting on top of each other in perpetuity because there's a need for distribution. and I think there always will be, AI or or otherwise. speaker-1: Yeah, I mean we we've we've always been an enabler of the broker for the same reason. I you know, I I think there's some c i there there's a there's a place for direct distribution, but that's a it's a small place, right?

And and you know, for people who've got that right, great, but there's a huge you need for for people who to help you understand insurance because it's complicated. speaker-0: Yeah, and that's not just a generational thing. It's like, ⁓ because like my dad can't use tech and I can't no. 'Cause it is maybe for like, you know, it's small, simple, personal or or like micro commercial, okay.

But God, you start, you know, you you you can be a one person shop and you're doing some things that are actually kind of meaty. All you have to do is is think, wait a second, someone can sue me for that, or what if someone gets hurt doing this? I don't understand any of this. I better get some help.

And help is is necessary. Yeah. speaker-1: I c completely agree with that. How about on the PLRB side?

If a if if yeah agents out there, why yeah, why would they care about PLRB? speaker-0: I I certainly know many a broker and agent who have had clients with claims. It happens. And yeah.

And you know, quite often you're the one that they're turning to, whether it's for first notice a loss and then you get out of the way, or it's they need your help in navigating it. And so we've definitely over the years had different agents and brokers who've reached out to see, you know, could we get access to your education resources so our staff could understand like, you know What is matching all about? Cause on these homeowners' claims, like we're dealing with this more and more and more, or you know, w whatever the issue is.

And so that's, you know, it has certainly come up where we've got agents and brokers reaching out to ⁓ to try to understand things better because it comes up in their world. It's tricky though, because like that's not their day to day. Their day to day is on the premium generation side and the commission side. And so there's this push and pull.

It's like, I wanna be involved in the claims. I wanna be there for my clients and I don't have time for any of that. So it's a it's a tough it's tough job for sure. speaker-1: I think that's where, you know, I w one of the reasons we invented this concept of the enlightened agent is because when I first came into the sector, you know, brokers had a bad name, right?

Broker's somebody's trying to sell you something that you don't really need, right? And trying to get, you know, they they get commissioned. So it's in their interest to charge you as much as possible, right? So there's this sort of bad rep for brokers.

And then I got into the sector and I realized, man, if it weren't for these people, like there there's some there's some there's some great people out there doing, you know, God's work to help protect these businesses, which are super important. And, you know, I think the better ones are the ones, frankly, who are going to lean in on the claims and sort of support you through that process and make sure that, you know, when your renewal comes around, you're, you know, everybody understands, you know, better understands what's required and why it's required.

And and so I w while while it might be a might not be a direct part of their job, the I I would expect the enlightened ones out there, ⁓ for those of you listening to Obviously, think about your customers first, 'cause that's that's what matters. speaker-0: The enlightened agents or brokers understand it's not a one-time transaction. It's a client service business. And those who stand by their clients, they're the ones who have the enduring, growing, strong business.

I mean, a renewal book is like that's what you're trying to build. It's great to have a new business, but once you get that renewal book firing, like that's that's what your, you know, blood, sweat, and tears are for to get that. generation engine going. And that doesn't come because you close the door on people as soon as you get your commission from their new business and you walk away.

You you need to know what you're doing and you need to be able to stand by them. And I think the r the real agents get like get that. Like any business, you know, great realtors, great even car salespeople. Chances are they you come back around.

But yeah, I mean the ones who really understand what client service means are the ones who actually like win in the business. speaker-1: Most the the best brokers get their business from referrals and the reason they get referrals is because they take care of their clients. And so that's ⁓ that feels like a critical part of the the relationship. Awesome.

That that's good context for the conversation. I think where I'd I'd love to go from here is is the topic of the day, which is AI. We've obviously been leaning in heavy at Broker Buddha on AI with the new platform. So curious and and would love to get that at some point get to that at some point, but I'm curious to hear how this is affecting your world.

Like where where does it come into play? speaker-0: I mean there's there's two different ways that AI is front and center for me. One is like very personally and and directly professionally, what it means to PLRB. And then the other is what it means to kind of my constituency, which is is largely the agent space sorry, the the carrier space, but it you know, it extends to the the whole ecosystem, including distribution.

When I think about it from P L R B standpoint, we are a a knowledge business. We provide resources to carriers. If they could just ask CatGPT, the same things they're coming to us for, why would you pay to be members of PLRB? And I shouldn't say that out loud and give them the idea, but they've already had the idea.

Sure. And quite frankly, like a lot of the the legal so we've got a whole team of coverage attorneys who will analyze claims and case law and policy forms and regs, and like we're constantly updating this knowledge database with that analysis. Well, so is Lexus Nexus and Westlaw. And if your covered your internal coverage team has, you know, a Westlaw subscription or a Lexus subscription, you're getting access to the AI tools that they're putting out.

So like, okay, well, would you turn to PLRB for that? Maybe the answer is no. And then that's a whole chunk of value you get from your membership that isn't valuable anymore. And we do that with building codes and with weather data and analytics.

And like, well, if I can just ask ChatGBT whether there was hail and what size it was at this specific address at that time and date. I gotta stop giving these examples. This is terrible. This a hundred percent.

And that's why, you know, it's I I was in line at the post office years and years ago, and there was an an older gentleman at the front who was like years and years ago was still two thousand and four. And he's like, What do you think of this email? I think it's a flash in the pan. I don't think it'll matter.

And like, even by two thousand four we knew. speaker-1: This is this is existential for you. I mean this Interesting. Okay.

speaker-0: Now, whether that's like quite the existential threat for the post office that AI is for a knowledge focused organization. I don't know, but it certainly had a massive impact in the the ⁓ like insurance, high frequency, low severity mail, like postcards. And we have to be thinking about that. Or, you know, it maybe it won't do away with our conferences because you can't ask AI to attend a conference for you.

You know, there's something to be said for being in person and networking and all that. But then we're just a conference producer and we're so much more than that. And so yeah, that's it's an existential threat. So that's that's like the direct day to day.

And that's part of why I was hired is to think about like how do we make sure this is a long term viable business. And we've made some awesome strides on that. And I'm very excited for some of the things I've seen privately internally that we're gonna start to show soon. Yeah.

speaker-1: Any any any hints or anything you could share that's ⁓ not public yet? speaker-0: I mean, I I shared about this stuff. ⁓ I did a keynote at our big conference ⁓ to share kind of where where we're going. And you know, some of it is looking at alternative I would say like we have amazing products and services that we distributed in non amazing ways, which is a nice way of saying like our website wasn't great.

It was hard to use, et cetera. So we've already like redone the website, rebuilt our whole like our website is our core system. It you know, it sounds simplistic to just call it a website, it's a lot more than that. But piece of that is to be able to deliver all those tools you get through APIs and quite frankly, automatically.

Like, why would an adjuster have to think, ⁓ I've got this claim and I don't like, you know, law and ordinance matters, like I need to check the the building codes. Let me log into PLRB and get a building code report and put that in the claim file. Why on earth are they doing that? So why why isn't that just done for them?

I mean, you know, you facilitate that third party data capture and and integration right into the risk file. Why isn't that happening on a claim? So when you open a claim, it's a homeowner's claim. We'll get the residential building codes automatically for that jurisdiction and just put them in the claim file.

Or better yet, pull a JSON file with the data behind it and put that into your decision engine if that's the way you're going. So facilitating that, and that's live now. So we came out with that while ago. speaker-1: ⁓ nice.

Yeah, no nobody nobody likes logging into multiple systems. This is I mean we we know the speaker-0: I always say like you get like a lion's mane of yellow post-it notes with all the login like details around someone's monitor. Maybe less of that in a day of like cybersecurity. But when I was coming up, like that was pretty common, you know, just all the post it notes framing the monitors.

speaker-1: Yeah, it was ⁓ a few years ago I was at a conference and somebody I met somebody, an agent, and they said, We have three screens. One's for email, one's for my AMS, and one's for my document management. And and I was like, That's and that's it. That's that's like that's all they do on their three screens.

So like as soon as you add a fourth screen, it's like Yeah bl blow my mind. So I think some people come come along since then, but I get the point, right? Like why why go to another system if you can have it integrated. speaker-0: And so then, you know, on the AI side is like we have sixty five thousand pieces of legal analysis in our our document database that our members can search through and and whatnot.

But A, we need better tools to surface relevant documents when you search. Because people are searching probably have no clue what's in there and what the content is. So their search the quality of of their search results is questionable. So I always hear like, you know, I do a search, I read some of the re the responses and then I get smarter about what I should be searching for.

So I do another one and then I look at those and then I do a third and then I find exactly what I need. I'm like, that's awesome. I don't know anyone who would put up with that. Like it takes you three searches and lots of reading before you've done a vet like that's not good enough.

So using AI to surface more relevant results, that's one piece of it. But more importantly is like anyone who's used Google recently, like the past couple of years, little Gemini answer at the top. We need to be able to do that. So yes, let's surface better results, but could we not answer like what is the matching regulation, you know, case law in Kentucky on these kinds of like, well, let's surface the answer for you if we have it in our database.

Now, the trick with that is accuracy really matters. So we when we're develop and this is why we're taking our time with this, is we cannot simply we could put out a tool today. That doesn't mean it'd be good enough because if it's wrong. Best case scenario, that carrier paid for a claim they shouldn't have paid for and didn't price for.

And so, you know, that'll drive up the rates that might lead to non-renewal, et cetera. But like that's not a great situation. Worst case scenario, that carrier denies a claim that they should have covered based on information we provided to them. And now they're on the front page of the newspaper for what they did.

And you get the whole plaintiff's bargain, like, that's catastrophic. And our reputation is toast. So that one that that's the one that like privately we're looking at, we're not releasing it yet, but that's where we want to get speaker-1: You're hitting on something that has been ⁓ eating eating at me is the wrong way, but this idea I mean AI adoption in insurance and I mean everybody's leaning in on how to use it. The the confidence around the results.

I think most people know these days that every every AI agent will tell you how correct their information is when it responds to your prompt, right? Here is the answer, and it's this is exactly what you were looking for, right? And there's this It I don't know, I'm I have this instinct that there's huge risk around that because your ability to evaluate and determine whether or not the response is either correct or directionally correct or you know needs double checking is is crucial.

And to your point, like if somebody just takes it and uses it without thinking about it and double checking it and cross checking it, ⁓ like problem big problems. Like just there's big problems there that come from that. And that's not okay. speaker-0: Yeah.

And that's not a big issue though. I mean, like I so I ran a claims team. This was an issue when we'd get coverage counsel, you know, outside coverage council to look at something. And, you know, my team leads would say to their staff, like, they didn't handle the claim for you.

It's still your claim. So yes, you get a coverage opinion, but you need to make a decision based on what you're seeing. And and unfortunately I think we both know that's not gonna be reality. And and the more we do this stuff, the more people will just take what the thing said and then go off of that.

And actually it should be an input into decisioning, but the reality is that's not gonna happen enough for it to be the right path. speaker-1: ⁓ gosh, six ⁓ trying to think six six months ago I was having this conversation with some friends about just about just AI in general and and it's like, you know, if if you're just gonna if you're just gonna use models like like why why are the why do these models matter? Like they all kind of tell you the same thing. Like what like how do you differentiate in this world?

And somebody raised a really good point and I it's kind of stuck with me all the time, which is that the ability to leverage AI is it comes in three ways. One, you have to be using it in the particular context. So like what like you can't just go out to Claude or ChatGPT. I mean you can every now and then, but like when you're trying to solve a specific problem, like you have a particular context for doing the work.

Two is you need the right UI to help you with the decisioning. In other words, like it's it's a matter of combining information you already have in a system you're already using with a response from a third party model. like in a specific workflow that is helpful for you, which actually helps you make the decision. Right.

And that so like it's not just a matter of using AI arbitrarily to like ask a question and get a response. It's like how does AI integrate into the systems you're using now in a way that supports decision making but but doesn't maybe send you off on a a decision that that you just sort of ⁓ blindly accept. We think about that a lot with a lot with our new platform. So ⁓ any ⁓ how how are you guys tackling that right now?

Are you are you building AI into your tools? Are you is this more of a like training for your staff on how to do this? Like what's the approach there? So speaker-0: There is training for our staff and we've been doing that.

And ⁓ a lot of those is pretty fundamental cultural stuff around like design thinking and and taking a different approach to things. As an industry, we're very ⁓ I always say this, we're very we can't because minded and we need to get to how might we? So like I hear you, all those constraints totally, they're all value. Let's just set them aside and just play.

How might we do this if we weren't constrained like that? And that's really difficult for us as an industry, but it's so necessary. ⁓ on the AI side in particular. I think a lot of the issues that we're talking about actually are solvable or more controllable than the kind of like doomsday folks would imply.

⁓ hallucination is largely not not completely, but largely a function of the way you design and define the rules of that tool. So we need a tool that will not hallucinate, will not give bad answers, and will say, I can't answer this, but here are search results that you should review. Or You know, here here's the link to submit this to one of the attorneys to research for you, which is totally fine. So we need the the other pieces like ChatGPT, Cloud, all the the public tools, their objective is to satisfy you, to give you an answer because they want you to come back and use more.

And then you need to buy tokens and we need a tool that is just as happy not satisfying you as satisfying you because it has to be right. So that those are definitional points. It's like don't make something up so that the person feels good. Give them the correct answer or say, Gosh, I don't know.

But here's a way you can find out. And that's perfectly valid. So that is definitional stuff. And that's what we're building now is one is is training it off the model, off the ⁓ the the corpus of knowledge, but then also looking at the results.

So our attorneys will use this to see like how good are these results and these answers, and seeing that it stops when it can't. And why can't it? And could we get past that or not? And if not, that's okay.

It's funny. speaker-1: I'm going back it it's probably only been like less than a year. I want to say like nine months ago when AI agents evolved from just being prompt based to like be introducing skills and rules and guidance. And all of a sudden you could really you know, so I'm I'm I'm in my head when you were talking about that, I'm like, ⁓ yeah, like you just need to build a skill which is like some instructions, which kind of tell it like, listen, you know.

Y you need to be ninety nine percent right before you tell me that you think you're you know, s some kind of guidance. Yeah. I think you can get the results that you're talking about. Yeah.

And the systems have evolved really quickly. It's I mean mind blowing. speaker-0: And if they haven't yet, the answer is yet. I mean, I always say like you you tell it an engineer of any kind, not just software engineer, like this is impossible, in their mind they've just added the word yet to the end of that.

Or maybe so far. Same same. speaker-1: Yeah, it's like, ⁓ can it do this? Like, yeah, just give me give me a week, right?

Like yeah. speaker-0: Or yeah, I mean I know like you're you're doing vibe codings like, or give me three minutes and it will do that. But yeah, 'cause it needs to be speaker-1: Expla explain to me what you want and we will build it for you very quickly. Yeah.

speaker-0: Yeah, yeah. So that like that that's the more direct way that we're looking at AI. And the other is like I'm this sounds obnoxious, but I'm like a thought leader and I hope people can see me doing air quotes or or can hear it in the industry. And so that means like, you know, I'm speaking at conferences and putting out thought leadership and whatever ⁓ quite regularly.

And so I I do get into kind of where is, especially on the carrier side, where are we at when it comes to AI and how we're thinking about it. And there's there's a lot to that. Part of it is we can't because the regulators haven't told us what's okay. And that kind of bifurcates the market.

I wouldn't say fifty fifty. It's probably like eighty twenty, those who are like waiting for clarity that you're not going to get. And the others who are like, well, we're going to move ahead. And if we have to adjust or apologize, like we will.

And I just had the the president of the NAIC is a commissioner of insurance in Virginia on the show. ⁓ on my show. Sorry, I have a podcast too. And he was sort of like, people are waiting for us to tell them what to do with AI and like, We're figuring it out too.

Because I was sort of I wouldn't say putting them on the spot, but like the industry is waiting for clarity from its regulators and you're not giving it to them. And he's like, Yeah, because we don't know either. I was like, ⁓ yeah, it's not like you guys are Max Hedge Room, you you're 20, 20 minutes in the future or whatever, like you already know the answer. It's like they're figuring it out too.

And I think the worst thing we could get from them is an overly prescriptive set of regs on AI, because by the time they're done writing them, even if they don't take 18 months or two years to write them. Even if they took two months, it's gonna be totally different game. So how do you solve for that? We've never regulated in such a fluid, fast moving context.

So yeah, for some carriers, I think they're they're waiting for Godot. Like it's never gonna come. And there's others who are like, we got to move ahead. Or you get sort of the middle group is like, we'll do internal stuff, you know, operational improvements.

speaker-1: Yeah, I guess the general rule is like until there's a regulation, you there's nothing stopping you, right? But I guess the problem is you you operationalize something and then there becomes a regulation and you have to Yeah. speaker-0: ⁓ Remember, we can't because so this is a regulated industry, so you can't do anything. Okay.

⁓ I mean I got that with drones. I was on a is when I was running claims, I sat next to the head of claims at a farm bureau carrier and someone was asking every question in every conference back then with claims people was when do I lose my job to the drones? It wasn't just AI, like it was the drones before that. And so this guy I was about to answer because they asked me, and the the guy next to me cuts me off and he's like, Well, we can't use drones because they're gonna be regulated.

speaker-1: Right. Right. speaker-0: I'm like, if that's your answer, why do you work in insurance? Because our whole industry is regulated.

So if your answer is if it's regulated, you can't do it. We don't exist. So like we're like, if it's regulated, you have clarity, figure out what you need to do. Like you have to get licenses or whatever, take that and move forward on those rules.

But you can't just say, We'll never use them because they're going to be regulated. It's like well then insurance doesn't exist. speaker-1: Yeah, th so you you use the how ⁓ how might we language. That's a a classic sign of an innovator.

And I'm pleased to hear it on a conversation with another fellow insurance industry executive. So thank you for bringing that to the sector. I think it's important. speaker-0: And with self awareness, I'm still super risk averse because I've been in this industry forever.

But but I if I'm less risk averse than others, maybe that's a that's a start. But yeah. speaker-1: Good, good. ⁓ it it it I think it would be unfair to our audience if we didn't at least talk a little bit about the relationship between what you're doing with P L R B and AI and how that affects ⁓ the agent and the broker space.

⁓ you know, what comes to mind for you as you think about the adoption and evolution of AI and you think about the work that you guys do and then tying it back to our original conversation about how do you gu you know, how does your work impact the brokers out there? You know, what What should our audience be thinking about in that context? speaker-0: I mean, ultimately, this is a bit like aside from PLRB, but this is this is why we exist, or part of why we exist, is the same the same thing that I I kept at like in my heart when I was running a claims organization is the best thing is to get to the right number as quickly as possible to, you know, put XYZ back together, whether it's a business or an individual or what.

It's not to overpay the claim, certainly not to underpay the claim. We generally ⁓ the carrier I looked at worked at We always said if it's gray, we pay. And I know there's others who said, no, we were in specialty line, so everything is gray, but that didn't mean we paid everything. But it's always better and easier to pay the claim than to deny it.

It works out better for everyone. So we were we looked for coverage. If there's an organization that supports you in doing that as a carrier, that will lead to better outcomes for you, for the insured, certainly, for the distributor who's sitting in between that relationship because it's easier on them. It looks better for them.

It backs up why they said, yeah, you should go with these folks for your coverage. So if we are helping, we PLRB are helping carriers find the right coverage as quickly as possible. So that problem can be resolved, that's a better outcome for everyone in that equation. And and I say like we had to deny claims at the carrier was at, it happened.

We still got five star ratings on denied claims. My team was always scared to like send the survey. But the reason being we didn't just say like you're SOL. What we said is like, ⁓ you know, like, listen, this is what your policy actually covers.

Actually, it's not this policy. You should be going to your landlord, you know, if it's a commercial business that has a space, like, and this is where their coverage would actually step up for you. So, like, we were trying to help them find coverage, whether it was with our policy or not. We were happy to cover what was, you know, legally we were supposed to be covering, but also not to just turn our backs on them.

Just because we couldn't cover. Every now and then there's nothing, you know, we got we we had a burst pipe in a movie theater and the broker sent it to every single policy that that insured had. We were their terrorism insurer. So I'm like, listen, we're we're out.

Like unless unless there's something more to this, like we're out on this. And I think that was a pretty easy note. Yeah. We didn't I don't think we had to say, like, have you tried the property insurer?

Because that might be, you know, that might be where the coverage is. But ⁓ generally speaker-1: what up yeah, I think what I'm hearing from this is, you know, if AI is gonna help you and it's good then it's gonna help your insurers, it's gonna help your agents, it's gonna help your customers, the win for everybody, but you gotta you gotta do it right. You gotta be careful. speaker-0: Yeah.

I mean that that first period between the loss and knowing where you stand, covered or not covered, is so nerve. I mean, I've had claims myself, like it's really scary when you're like, it's already bad enough what you're dealing with, and now you've got all this anxiety. I'm like, and I don't even know if we're gonna be able to put ourselves back together. So like getting to that clarity sooner is better for everyone.

Whatever the next step is, like better to have that clarity across the board, not just yes, no, but why. And what do we do about it? So I I know that's helpful to agents and brokers. speaker-1: Yeah.

I'm thankful that I haven't been on the on the claiming on too too many claiming sides of claims to feel that way. The few times I have, I I do know that anxiety and it is it is deeply uncomfortable. And it's good to know that you've got support from, you know, the brokers helped you pick the right company. That company's standing behind what they said they would do.

So believe it or not, Brian, I I I could talk for for hours about ⁓ AI and insurance. ⁓ been talking about it a lot recently, but I'm afraid we're gonna have to bring things to a a close. This is This has been an enlightening conversation. It always is with you.

If there's anything else anything else you'd like to share with the audience, the brokers and the carriers out there about either you or the PLRB or AI, ⁓ I'll give you the mic. speaker-0: I would just remind them of why we all exist. And it's, yeah, the claim story is important in putting lives back together or businesses or what have you, but it's a lot more fundamental than that. Nothing happens in the world without insurance behind it.

So everything around you is facilitated by the work that you do to find people and businesses coverage. And if that's not a good reason to get up every morning and try to find the right answer to protect people so risk moves out of the way and they can move forward. I mean, genuinely look around. Nothing has has the ability to move forward directly or indirectly without someone moving that risk off the table.

And you're the one who facilitates that. So I always try to remind people of that. Like the claim story is very important, but like the entire world grinds to a halt without us. So that's that's pretty important stuff to keep doing speaker-1: Important message.

Yeah, it's an important message and aligns closely with our with our mission, which is to, you know, support the brokers who help protect the businesses that change the world that we live in. So good message to end on. Brian, thanks for being on the show. Look forward to connecting soon.

And if you ever feel like writing that book again, just don't be afraid to give me a call. speaker-0: Hundred percent. Thanks, Jason.