October 9, 2025 | 15:58
Dave: Yeah, thank you for having me
Dani: So let's talk about life for a moment and not philosophically and more the underwriting perspective so and then why trust is critical to the process
Dave: No, and I'm totally curious and I'm biased of course, but I think that's a great place again again you know they're reflecting on that and that question of just doubling down on that being really the cornerstone of our facing this model and I'm curious you know as we kind of compare it to other interviews whether they would say this thing or otherwise uh uh they don't make like the case for it at the end of the day at the end of the day we trust in the consumer to bring us accurate information. Yes, we've got ways of verifying it, but none of them really sort of removed that foundational element of trust. But really conversely, and maybe even more importantly, the consumer is trusting us to be good financial stewards of the underwriting dollar, such that we're in a position to cheap that promise not five, ten years, but easily 20, 30, 70 years for now, that's an incredible amount of trust that the consumer is placing in the process. And on the face of it, nothing about this business model should work. And yet, it has persisted largely on perturbed for 150 years. So 100 % I could put forward that trust is the cornerstone of our business model.
Dani: In that vein, I mean, in building the trust, we chatted a little bit earlier about questions that you might get in this regard and around trust and data sources that are being used and using the most sensitive information possible. So that too, it kind of adds to the complexity but also the criticality of that trust in that situation. Where do you see money being left out on the table? And is there a consumer trust factor that needs to be better addressed.
Dave: So, you know, there, I know it's a 15 minute podcast, but I just have to take a little bit step back and answer that question, 'cause it is a bit of a story, right? And again, apologies if you're well familiar with that story, but at the end of the day, we realized several years ago that in comparison to adjacent industries, we really have a consumer journey problem at the end of the day. There's just, these are in a comparable process, if you will, to another product where it takes weeks and weeks and weeks, it takes physical examination, we might draw your blood. What other product is there like that, and is it feeding for consumer wallet, we realize that's just going to be a barrier going forward. To solve that problem, and here's the critical bottleneck, is those exams, those labs, they are highly predicting. To solve that problem we needed to bring on other data sources. And we did, and we did it in abundance with the exuberance we brought on these other data sources. But then we look around there, and our underwriters back home will say, "Yeah, Dave, thanks for nothing." But at the end of the day, we literally have doubled the file sizes that our underwriters need to navigate through in a short period of time. And what we are hearing echoed across the carrier landscape is yes we love data source A we love data source B we love data source C we can't have them at the end of the day so where money is being left on the table is efficiency i absolutely believe the keenest area underwriting competition on the go forward is not any more the competitiveness of the offer of course that that that's critically important but really the keenest is the efficiency, the ability to sit during this information in a cost -effective and a timely manner.
Dani: Yes. And so, you know, what can we do about it? Because like you said, that's also putting additional, say, stress on the customer. If there are all these data sources that have to be sorted through, you have to do follow -ups, and the customer is waiting longer to get some kind of resolution. And then in the meantime, there's a lot of pressure on your resources internally as well. So what can we do?
Dave: Well, at the end of the day, it does involve taking a bit of a step back and what I mean by that is the key problem in our industry about these data sources. On the surface, they look relatively similar, right? So these are things like your clinical lab history, your medical claim billing data, and electronic health records. They'll give us various pieces of medical information, but I think what we are probably underestimating is the difficulty in comparing the protective value across those data sources. And because it's a real moving target, begin with. Just as an example, I go out and order an electronic health record, what are my chances of finding an actual piece of information that the answer to that And the good news is it's improving on a daily basis. The bad news is it's changing on a daily basis. So as we're doing our cost benefits analysis, it's a moving target. So what we're doing here at RGA is we're spending a lot of time on that foundational piece of comparing the protective value across digital data sources. And we're calling that digital underwriting evidence playbook at the end of the day. But that's our key initiative going forward to be much more surgical and personalized in the other at your requirements journey.
Dani: Yes, absolutely. It makes a lot of sense. And we've been hearing today and a lot of the conversations just around how you can better personalize the experience for consumers, meeting them where they are as well, making it easier for them to access what they need and all of that kind of consumerizing the journey. When we talked earlier too, you had a bit of a hot take on the state of innovation in underwriting and maybe that there's actually an opportunity to do more than maybe the industry is currently doing. Can we talk a bit more about that?
Dave: Always fascinating to hear others' opinions on it, but it feels as though we're at a philosophical kind of reaching point in underwriting innovation, right, because there's just absolutely no doubt about it, and we'll sugarcoat it, that every underwriting shop is under tremendous expense pressures. And whenever that happens, of course, the dollar goes towards those things that have the most concrete and immediate return on the investment. And so I think that then becomes the real sort of philosophical to carriers and reinsurers alike is, yes, of course, that's gonna help out with problem B and C, you know, towards the end of the year. But to truly gain competitive dominance, we all realize that we have to be looking around the corner. And in this expensive pressure environment, the question then becomes, is what's the right amount? On a really practical basis, what's the right amount that we should be budgeting towards innovation when we don't know all that what that ROI is going to be and we do know that it's going to be less than some of the things that are on the plate today you know.
Dani: There does seem to be sometimes a bit of analysis paralysis. You think innovation, you think oh big oh spending like this huge thing rip out all the systems we have but you know from your perspective it doesn't have to be that way.
Dave: Okay so you just hit on like other philosophical debate right and that is that debate between do I go for sorry for the sports analogies but is do we go for the singles there because that certainly improves the likelihood of that that ROI there but at the end of the day everybody should and I go You know, this is what I end up believing. At the end of the day, when you take a look at the strategy document, the pillars that you've created, you have to-- you just only have to look at that and say, is the home run somewhere on this page? And that's what we do, just on a yearly, not a great web page.
Dani: I think that's a great way to put it. And I had another conversation with somebody else who said something similar where it's, you know, instead of, you know, sitting there and trying to stack everything and figure this is just looking for the outcome. Is it there? And then figure out how to get there and then just throw out some of the barriers to change in that regard. If I can ask you if there's something you would say to leaders listening, whether about taking action or something you think that folks should be thinking more about? What would that be?
Dave: Okay, so I will take credit for going an entire 10 minutes without mentioning artificial intelligence. But actually, I think it ties in really well with these conversations around and trust. And I think the challenge that I would put forward to insurance leaders is that when you think of that intersection between artificial intelligence, underwriting, and trust. I think the natural inclination is to immediately revert to the defensive, right? At the end of the day, the mental shortcut is to a robotic decision delivered in a black box fashion. And what I would challenge industry leaders is that what if you took that defensive mindset and literally just flipped it on its head. It took those and said, can we make those selling points, if you will, of the AI initiatives? And what I mean by that is I think there's a tremendous opportunity to actually better explain the decision logic in our underwriting decisions through the use of artificial intelligence. And the reason is, it's actually a really manually intensive process to document for underwriters why they came to the decision that they came to. We're sitting in great immediate strides with artificial intelligence to provide efficiencies in just that. And what we're doing right now, it is far beyond, far beyond already today, what underwriters are are capable from a time and efficiency standpoint of documenting and we cannot bring these breadcrumbs if you will to our decision to present them to both you know carriers distributors consumers most importantly and really actually improve the transparency of our decision -making process and again flip that that question on its head. And then there's the question of the robotic piece and here I may be taking a You know a bit of a flyer, but I've got to say and I'm sure you're the same That when I'm interacting with these large languages, of course, I'm impressed by the knowledge base that it's getting together. I'm impressed and I'm also partially creative with this human nature that these are taking on like in the process and the emotion I, you know created just this little silly essay. And I just said, just make it 10 % cheekier and it delivers. You know what I mean? So the point of all of that is, if we think of it then any output of the artificial intelligence relating to underwriting is just purely robotic. But I think there's the potential of an opportunity there. And whether it's fully human, I don't know, but it's certainly better than I think our perception is in terms of what, you know, the type of empathy that we can bring into the process as well.
Dani: I think that's an interesting perspective because partly the human technology interaction does bring in, I think, some of the empathy to that output. If you think about it, you have to know about prompts, prompt engineering. We have to have a human expert to understand what the outcome is that you want from the input. And then, I mean, another question would be, what does that say for our underwriters of the future in terms of their skill sets or what could things look like for them going forward?
Dave: So at the end of the day, you think about sort of what this would hopefully be taking off of the table. And I think the common mantra is not only for underwriters, but just for every job USA is, right? Is that this would allow then underwriters to operate at the top of their skill set? So I think the question then becomes what is the top of the skill set for underwriters, right? And I think part of that is going to be critically thinking and probably bringing in now the combination of outputs from models with other elements that are not included in the model. So just on a really practical level that then will become for an underwriter you have the medical piece and the financial piece. And for a variety of reasons we're really focusing on a medical piece in terms of of where we're bringing our AI efficiencies is of combining it then is actually really where the underwriter plays a critical role in sharpening the pencil and making the offer actually more competitive than it would have fit through algorithm alone. The second piece is just what you mentioned I think there's going to be a need for the ability like ultimately distributors care when there's that need for interaction, they don't want it to be with a robot. So the communication skills that you're going to be, you know, just really critical and then I would default to the audience, right? Our underwriters and myself included just on a constant daily basis, our striving to improve our data, our AI fluency.
Dani: Yes, I love that. We have gone through our questions so we can wrap, but I did want to ask you, Dave, if there's anything else you wanted to share perspective -wise or anything else that came to mind while we were talking.
Dave: I think it maybe gets to one of the questions actually that we were talking about in prep. And that was just around other ways, or what would that look like, if you will, if we were able to improve consumer trust, and in particular, prove it earlier on in the process. Because one of the trends that we are most definitely seeing with all of these data sources, we're taking the advantage now, finally, of the fact that they are instantly available. And so almost by definition, these data sources are being reused earlier on, earlier on, earlier on in the process, and in particular, being used to compare with the information that we received from disclosure. I think at the end of the day, there's no magic about what the implications of that are and they are both positive. I think they will ultimately allow us to use less data in the subsequent parts of that process. And they will ultimately be able to improve the customer journey further by being able to reduce the need to offer less questions in that process to begin with. Application disclosure matches with the data, no need to dig in for it.
Dani: Exactly, yes. And again, going back to the previous conversation I was having gere, the folks were saying, you know, it's time for insurers to build for customers versus building for insurers who need to get a job done. job done. And I think that's a great example. So think about the systems that are in place and think about it from the customer perspective. So I love that. Let's leave it there. Thank you so much for being here.
Dave: Absolutely.