Transcript
Robin: Hello, everyone. It's InsTech podcast time again, and I've got Ben Ruddle with me. Ben is the senior principal in the insurance team at Publicis Sapient. Ben, welcome.
Ben: Nice to see you again.
Robin: So, tell us a little bit about the role and how long you've been there and, and so on.
Ben: Yeah, sure. So, eight months at Publicis Sapient, which isn't that long, but I come from a background of strategy consulting and then actually just hopped over from five years over at Hastings Direct where I headed up our strategy function.
Robin: Some may know what Publicis Sapient does, my description would be it's a global digital transformation consultancy. It's, I mean, it's big, some 20,000 employees, annual revenues, I see, last year of $1.3 billion. Would that, would that be fair?
Ben: Yeah, absolutely fair. So, we are a, like you said, a global digital transformation partner. Lots of people will know us just as Sapient. We were founded in the nineties to help existing companies prepare for a digital future, and that mission hasn't really changed. So, we're really well known in banking, retail and travel.
Ben: We're growing out our insurance practice at the moment because, fundamentally, we think insurers need the things that we offer. So, anything from systems modernization to data infrastructure to just delivering great digital customer experience. So, we're now Publicis Sapient, we're part of the Publicis Groupe, which is the global media and communications group.
Ben: So, we bring that real customer understanding as well.
Robin: So tell me what, what do you think the skills of the insurance team are? What have you put together, and what do you think you do best?
Ben: Yeah, I guess ultimately, we think that we can be useful anywhere that technology is holding you back. So that could be providing a digital experience that actually really engages customers. It could be getting your data into a format that lets you overlay generative AI and those use cases. It could be replacing your core systems, like your policy admin system.
Ben: But we think we can be useful across personal insurance, commercial specialty, life and health. Ultimately, those things are much more similar than they are different, and technology now sits at the heart of all of them.
Robin: But given the focus on digital transformation, is it inevitable that you'll then spend a little bit more time in the kind of general insurance retail space than you will in the specialty space?
Ben: I think so. I mean, the different parts of the industry are clearly at different levels of advancement when it comes to technology. Personal lines and small commercial probably being slightly more advanced and some of the corporate and specialty lines being perhaps a little bit further behind. But ultimately the technology is now becoming much more accessible to everybody.
Robin: Well, that's part of the InsTech thesis. There's not much happening in the complex specialty commercial space these days that hasn't been done in retail and general insurance over the last 10 years. So I have a strong sense that there's much to be learned from the retail and general insurance world.
Robin: And that actually, bit by bit, you can see that starting to play out. Let me, let me move on to your thesis called “Beyond Beige.” Well done on the title, because we all struggle to find interesting things to say that pulls you in. But the Publicis Sapient thesis is that there's a huge opportunity for insurers in providing cover for individuals and small businesses with unusual or specialized needs, those with characteristics that normally place them outside that sort of comparison website, standard insurance footprint.
Robin: Tell, tell us a little bit more about that.
Ben: Yeah, absolutely. So, we noticed a real polarization of the market in personal and SME insurance, and we're thinking about the U.K. as well as Europe here. So, in personal lines insurance, I mean, materially, everybody in the U.K. now is buying through price comparison sites. And in other parts of Europe, comparison-based brokers are becoming much more common, which is encouraging really standardized products where the insurers are basically competing only on price.
Ben: So although there's the illusion of choice, so if you're a customer who's in the mainstream, you might appear to have 100 to 150 different offers for your car insurance, but realistically they're all materially the same, so that's what we call beige.
Ben: You're basically just being offered 100 different shades of beige at different prices. But there's another side to the market as well. When we looked at it, we saw that 30 or 40 percent of customers are being left behind by that status quo. So they might see very few results on price comparison sites, so they might still go through a broker or just go without insurance entirely.
Ben: So, these are customers who have markers attached to them, which might put them outside the footprint of most of the mainstream insurers who basically just choose not to compete for them. Plenty of the largest insurers still only have an underwriting footprint of about 60 or 70 percent, and they're offering competitive prices to much less than that.
Ben: So we call that other part of the market the long tail. It has millions of profitable customers in it, but there's just not the data available to identify who's a good risk and who's not.
Robin: Give us a few examples of an underserved customer.
Ben: Yes, there's lots of reasons a person could find themselves in that long tail of customers who aren't getting as much choice. It either means they have risk indicators against them that encourage insurers not to quote for them, or it might just be there's really incomplete data available.
Ben: So those risk markers could be things that you might expect, like criminal convictions, or they live in a cottage with a thatched roof or they live on a floodplain. But perhaps also people who were in the armed forces who leave their homes empty for months at a time. So they have to answer “yes” to that awkward question about whether they leave their home empty for more than 30 days at once.
Ben: And then there's the group of customers who have incomplete data available. So, they could fundamentally be a good risk, but they might have recently migrated to the U.K. or spent time abroad so they don't have the same level of information on their credit file as, as you or I. And all of this adds up to way more people than, than you might think.
Ben: So, actually 11 million people in the U.K. have a criminal record, and all of this adds up to a societal issue as well. It's not just a problem for individuals. Sixteen million people in the U.K. have no home insurance or rental or possessions cover at all, and those people who are underinsured are concentrated in young segments and people on lower incomes who are the same people who are least able to absorb those financial shocks that might come with a loss event. And that holds back everybody.
Robin: I have some experience of that because I'm lucky enough to have a cottage that I go to in Suffolk at the weekend. But because I don't live there seven days a week, it falls outside the normal criteria, and I have to go through a specialized facility.
Ben: You don't get the same level of price competition from different insurers, so they're probably making quite good money from you at the moment.
Robin: Well they were until the roof blew off the, the wood shed outside, but we're about, we're about even now, I reckon. So, I, I look at this and I think, well, you know, in this day and age when there's so much data available and we live in a digital world, how's this arisen?
Ben: It's a market failure, because until now, the cost of understanding these customers and getting the data you need about them has been greater than the potential profit that comes with writing that risk. So outside of the mainstream rump of customers, insurance is actually still a pretty inefficient market.
Ben: It can take years of underwriting a new segment to, to make it profitable to get the amount of data that you need to really understand it, and, and not everybody has, has appetite for it. So, consider the example of somebody who lives in a, like an old, listed building, for example. And until fairly recently, for an insurer to get the information they needed, they needed to send somebody out in person with a few clipboards and checklists, wearing a hard hat, which is really expensive, right?
Ben: You could only do that for maybe two or three customers in a day. Now, you can get all that same information about that building from a variety of different databases, and you can do it in an instant while the customer is still part of an automated quote and buy journey, and the cost of doing that is substantially less. So, that's our thesis is that the, the cost of finding the information you need about these customers to make a market has come down, and that presents a huge opportunity to seek out those customers who present the opportunity to make good money.
Robin: But if, if insurers haven't done that in the past, why are they going to do it now? Do you sense some sort of ground swell that's going to have the industry recognize the opportunity and, and invest in making the most of it?
Ben: Yes, it's a great question. The thing that's changed is the pace of technology that's allowing insurers to access these customers much better than they were able to before. And those new technologies, so we're talking about the data that you need to understand these segments in more detail. Data, which was scarce and expensive, is becoming abundant and cheap. And the tools you need to analyze it to extract the meaning from that data, that's not just the preserver of a few doctorates from MIT; those machine learning models you need to understand that data are now available to anybody who can write a bit of SQL.
Ben: The infrastructure that all of this technology runs on is becoming much cheaper, and it's based in the cloud so it's much more flexible and scalable. The tools that you need to offer personalized customer journeys and targeted marketing, all of that is coming along at such a pace that it’s going to help insurers to make a market for these customers that they weren't able to before. Ten years ago or five years ago, Robin, if you were running a commercial lines insurer and you wanted to launch 10 new products for small businesses, how long might that take? That could actually be years of work, right? You need to write a bunch of different policy wordings, get them all signed off. You, to launch new customer journeys, new landing pages, you need to write a bunch of new content to optimize your search engine performance, and you need to develop targeted marketing materials. All of that would have been really manual. So that could have been years of work. But now, using, you know, digital component libraries and a bit of generative AI, you could do that 10, 20, 50 times faster.
Ben: That changes the equation. So those products that it might have taken you a year or two years to get to market, nowadays you could do in a month.
Robin: Imagine if there were some insurers out there that were listening to this, and the lights come on and they go, I should have thought of that a long time ago. What do they need to do to get started? What's the sort of basic ingredients that you need to do this?
Ben: Well, the insurers who are starting to see most success here have been in the insurtech space. If you're an incumbent insurer, you do have a scale and a, and a capability advantage. But ultimately to be successful here, you're going to have to start operating more like an insurtech.
Ben: And if that's not possible at scale, you need to start with a single team that's really focused on the customer and offering them a product that they want rather than the policy wording. As insurers, we're often guilty of saying the word product when we're actually referring to a 50-page policy wording document. But now the product has to be the whole proposition we deliver to customers, it has to be relevant for them, and it has to be backed up by data-driven underwriting. So, there needs to be a real mindset shift of approaching these new groups of customers, starting with a couple of, of easily defined groups, but building an understanding of them using data and then delivering a, a great product in a personalized way.
Robin: We've often written about this. Do you think it's best to go greenfield site? Is it something you can do within the existing framework of your insurance company? Or is it best to start from scratch and, and rethink the whole way you do these things?
Ben: Well, insurtechs have the advantage that this is their whole business. This will be the only thing that they do. So, larger insurers should start by setting up a task force to look at niche segments but doing that with minimal distraction to their core business. But we believe that those insurers will quickly find that the capability they build, looking at those niche segments off to the side, will then really quickly start to support the core business.
Ben: So, things like rapidly finding and analyzing differentiated data, or offering personalized propositions, targeted marketing, Agile, MGA and reinsurance models to scale quickly. All of those are capabilities you develop looking at the long tail that you could then apply those to make your core business run better and more profitably.
Ben: So this isn't just writing nonstandard groups of customers. Insurers have been targeting non-standard customers for, for years. This is doing it at scale using technology to access dozens of different segments that were too expensive or inaccessible to go after before and doing it cheaply and quickly.
Robin: It all sounds terribly easy, but is there anyone out there you can name who's actually going down this path who you think has sort of done a good job of it?
Ben: Yes, so the best examples so far, unsurprisingly, have been from the insurtech space because they're able to focus on doing this as all that they do. So, take Avantia, for example, in the home insurance space. They started out focusing on nonstandard segments, using data to grow much faster than their competitors and doing it through an MGA model. But then they used this to go mainstream.
Ben: Now they offer quotes on 97 percent of homes. So, in the mainstream space, sure, some, some of the larger motor insurers are starting to increase their appetite for higher premium business, but this is more just a gradual extension of their core business rather than targeting completely new segments.
Ben: So, we think that the people who are going to be most successful are those who can shift mindset to think more like an insurtech, really organize around the customer and what the customer needs rather than organizing around the underwriter, which is what we've been slightly guilty of doing in the past.
Ben: Another good example would be ManyPets. We know them now as serving insurance products for pets, but they didn't start out that way. They started out as Bought By Many, investigating many different segments where they felt that there was a level of underservedness going on.
Ben: They tried out a bunch of those segments, found that pet insurance was where there was the biggest gap between what was being offered and what customers needed, and chose to focus on that.
Robin: What do you say to the skeptical element of the podcast listeners who say that was a good thesis, we all had it five years ago. And that insurtechs had this great opportunity, but looking back through uh, the last five years, very few have been able to sustain it. They got good money on the basis your thesis was right, but not enough have written profitably.
Robin: And that probably the reason for that is we underestimated the need for scale, the knowledge about how to do this profitably rather than the knowledge of how to sell. Is that a bit unfair?
Ben: I don’t think that's unfair at all. I think that plenty of insurtechs have, brought the, the right approach to the table, but fundamentally, like you say, have struggled for scale. Now, as an incumbent, you have the advantage of existing scale and some of the economies around cost that, that go with that, and your huge bank of, of historic data that you can use to support your underwriting and pricing.
Ben: The thing that the insurtechs have got is the cultural thrust to go after these niche, underserved segments because they can't immediately compete in the mainstream. As a larger insurer today, you've got to think about how do we leverage the, the scale and the capability that we've got, but try to think and be more FinTech in the way that we operate.
Robin: Or buy them, which is probably what a lot of people see as happening and probably isn't happening as much as we all thought.
Robin: Publicis Sapient operates in a crowded space. You know, what is it about the company that you think makes it a compelling choice as a consultant in, in this area? What would you say to the listeners?
Ben: Three things, Robin. The first one, we've done it before. So, we built the experiences that customers are having across banking, retail, leisure, the experiences that they now expect to have in insurance. Secondly, we are front-to-back specialists. We tie together technology and the implementation of it with customer experience, agile delivery and AI tools, all of it while delivering commercial and strategic value.
Ben: And the third one is our reputation precedes us for getting stuff done on time and on budget.
Robin: And then lastly, we often ask this question, if listeners take one thing away from this conversation, what would you like it to be?
Ben: The technology, the data, the AI that you need as an insurer to serve new groups of customers is out there and it's moving quickly. So, if you need a helping hand to start applying them and staying ahead of the competition, give us a call.
Robin: Well done, Ben. That was most enjoyable, and I'd like to think that it was beyond beige. But we'll let the listeners be the judge of that.