October 10, 2025 | 11:58
Andrew: Thanks for having me.
Dani: Gonna jump right into a question, thinking about trust, but also more broadly, like opportunities for insurers. It's a for-profit industry. Where do you see money being left on the table from your perspective?
Andrew: Yeah, so in the homeowner claims arena, there are really about four places where we see we've got big opportunities to make sure we pay a wheel every time, and that's accuracy, right? The first big spot is estimating. So every time somebody has a loss, we have to understand how much, how much is the depth, right, and how we estimate that loss in terms of the scope and the pricing and the products that we use. It's super important getting that right. And if you're wrong on either side of the equation, if you're underpaying, even upset customers because you haven't paid enough, right? You potentially break trust. Or on the other side of the equation, you've paid too much because you've been inaccurate. And now you've put your company financially at risk. So estimating is a big piece pricing is another piece of as we look at the contents, right? Understanding we came for the right things, the right products that we're placing them at the right values. And small mistakes, they don't kill you, but it's death by 1000 cuts. So, getting that accuracy right on every single plane, every single estimate, is super important. The other two areas, you know, fraud, right, there's a small chart, what we do is insurers, but because it doesn't happen often, right, you have to be extra vigilant to catch them. And so, thankfully, we've got a lot of tools out there that are getting better and better with AI, they're helping us find fraud and fight fraud for just those customers that are trying to be fraudulent right and so that we're not putting everybody else through that same rigor that same experience and really just dialing into those areas where we know that we're at risk of paying what we don't know and then separation right the opportunity to get some money back for our customers for our company. That's another space where it's really intriguing because you have those opportunities on small numbers of claims. Anytime you do something a few times, you're never good at it. And so where technology can help us flag those claims, flag those products, and then get that information to the right people so that they can do the work that they're good at helps us recover those funds much more efficiently.
Dani: Absolutely. And I think this all sounds right on point and I want to ask you about the death by a thousand cuts a little bit more because it does seem in some cases like you know for example you said fraud is a very small portion and all of these things but almost like well we can still keep doing business and we're fine and kind of just accept these thousands of little cuts you know but there's going to be a critical point where we can't keep doing that as as an industry like what are your thoughts there
Andrew: So I think it's a competitive advantage right so death by a thousand cuts well and I agree I think like fooling yourself into saying it's okay we can manage it we're getting by just fine. But what if you want what if you weren't paying out all that extra money right then your premiums go down. Then your marketing expenses can go up. Then you can grow as a company because you're selling your product at a lower price and you're putting yourself on to the marketplace at a cheaper cost. So like you can't ignore, you know, hey, oh, it's only ten dollars… But ten dollars by a hundred thousand claims like it adds up And so I think we as you know as a claims leader is leading claims operation I owe it to our company and our customers to make sure we're not paying what we owe, So we can push that back into our product and our pricing to make that better for them.
Dani: Yeah And there's also the piece which maybe we'll turn to the trust aspect of this or leave it in like the Costs higher premiums like things get pushed down to the consumer anyway, right? So then that's a whole other set of issues and maybe we can go there now: consumer trust. It's taken a hit You know, so what do you think can be done to rebuild it?
Andrew: So from my perspective, having a claim is the moment of truth in the insurance equation, right? And when a customer has lost their property, damaged their property, it's often like the worst day in their life. And so for us, being there at that moment of truth, we have one moment to build that trust on that first call with that person of, we're going to take care of you. And then we spend the rest of that claims process delivering on that promise each step of the way. And so it's something that you can give once and you lose forever, and it's so true in what we do. And so for us, a lot of that goes into training our adjusters, right and making sure that they know the right promises to make and how to deliver on them consistently. And that just touches the whole arc of the process. The good news is technology out there is helping us do that better and better than we ever could before.
Dani: That was going to be my question. Where does technology fit into the trust building?
Andrew: I think part of it is, you are for that customer who's filing their claim online, it's like, well, they're trusting us that we're going to get it right. And so even that very first automated experience they might be having, what's the output? Are we telling them, hey, here's your adjuster, here's their phone number, here's where they're going to call you? That's a great first step. And then as the customer is moving through that process, We want the adjusters to be responsive and set the right expectations. Now, 10 years ago, you could only do that after you kind of cut your teeth and figured out, "Oh gosh, it's gonna take me 10 days and not three days." Today, with AI, with better technology, that's kind of giving that adjuster a nice hug, the tech is helping that adjuster move that claim along and set the right expectations and then meet them. So when something's starting to go off track, is there a piece of technology there to help the adjuster get it back on track? When the customer's communicating into us, do we have technology to help us communicate back out? And so those are the things that have really helped us rebuild trust with a lot of those customers because they feel responded to, they feel like they've got the right expectations set and then at the end when you do deliver on that we're here we have a more satisfied customer.
Dani: Absolutely makes total sense and then to take that a step further homeowner claims perspective you know sometimes like those claims can be longer processes might have to you know send someone out to take a look at something like a look at a lot of paperwork. So thinking about the trust of the consumer by the insurer like what it could mean if you could more confidently trust the information that you're getting from the consumer. You know what would that mean for your processes, for your people, for your business?
Andrew: Speed, right? It's all about speed. We spend a lot of time verifying the information that we're getting. If we can trust that information as it's coming in and know that it's good data, then we spend less time verifying and we can push that claim along so much faster. And whether that's something as simple as measurements, pictures of the damaged area, estimates for contractors, all of those things, if we can trust that data, well, maybe I don't have to have somebody drive two hours to go put their eyeballs on it, right? Well, now that claim is now four hours faster. Or days faster because, oh gosh, that adjuster was somewhere else and I can't get out there for three days from now. So like that, trusting a piece of it on both sides of the equation can dramatically speed up what we do.
Dani: Absolutely, and you think of the cumulative effect of that and for the long term, that the consumer loyalty as well. And I think the mention of the data pieces is really interesting because there's, you know inherently if you use historical models for example sure we can predict certain things but that's not the whole story not near and you know coming from your perspective you're just saying we need to make you know we need to have good data what does that mean for you what does good data like look like?
Andrew: So good data can come in a variety of forms right so I kind of laughed, I chuckle to myself and I think like what does good data mean right? 10 -20 years ago was a good day. It was like a Polaroid picture..
Dani: Yeah, and here's a spreadsheet.
Andrew:. Yeah, and the spreadsheet's a great example Right. Yeah, we think good data is I give you a spreadsheet Here's the format I want it in and you do the work and put it in there, right? Yeah, and we were kind of forced to do that because we didn't have a good way to adjust anything else other than the spreadsheet. Yes, right. Yes. He asked me today what I think the data is. Good data is what I can ingest in a way that I can act upon it. And that is dramatically starting to expand in terms of, gosh, now I can OCR a really grainy picture of a condominium document that's 55 years old. It's like, wow, I couldn't do that before, but now I trust it. Now I can ingest it. So I would say good data looks like any piece of information that I can ingest, verify, and act. And take action on.
Dani: I love that. As we wrap up, thinking about, you know, other industry leaders who are listening, what is something that you would implore to the folks listening or something, a takeaway that you think folks should be doing right now or do more of?
Andrew: So, I mean, I love these conferences. I love technology. My team hates it when I get back because I'm like they were to do this thing and this thing and this thing I would implore everybody. Don't do that, right? Yeah, focus back on the adjusters, Focus back on the people who are doing the work, and listen to them, so the folks that are gonna be able to tell you whether what you're doing is working or not And how you can make it better and if you use that as an informed position From there to build your about how you're going to deliver your product, you'll be wildly successful. And so I would say, listen to your frontline, they know what's going on. We're at risk of leaning too much on technology and losing that personal touch and losing that perspective.
Dani: Love it, I think that's a fabulous way to end. And what I'm hearing from you, Andrew, is keep the customer in mind, also keep your end user in mind internally in the org. Those are the folks actually building the relationships too. And then figure out how that ladders back to outcomes. Love it. Andrew, thank you so much for being here.
Andrew: Thank you. Pleasure to be here.