You good afternoon, so what I’d like to do is to start off by making a prediction I might nestled within it a bit of a challenge for us in shorter companies, I’d like to pivot from there to a question that I’ll throw out there and then Park It tell you a little bit about how we at lemonade think about the challenges that face us would like to indoctrinate you into some of our thinking share with you some of our experiences and then perhaps come full circle towards the end and try and answer I’ll. Give you my answer to the question that I’m going to be posting posing. So I said, I’m going to start off with a prediction: the brands that dominate today dominated during the era of the horse-drawn carriage there’s been tremendous longevity and the question or the prediction. I’M going to make, if you like, is whether those same brands are going to dominate a generation from now. Are we the last people to be able to say the sentence that I did, that the brands that dominate today dominated during the era of the horse-drawn carriage – and I think the odds are that, yes, we are. I think that what we’re going to be experiencing the coming years is a significant changing of the guards and I’d like to add a bit of color to that. But my prediction is that the brands of tomorrow already exists.
They may have already presented on this stage and that we’re going to see a very significant, perhaps not sudden, but very significant shift and I’ll try and come back to this theme at the end. But the underlying reason that I say that is that the assets that insurance companies have built up over these last hundred plus years are now revealing themselves to be liabilities, whether it’s their brand, whether it’s the distribution methodology, whether it’s the IT stack, whether it’s the corporate Culture all of these have served them so very well, but the tides of changing – and I think the companies of tomorrow going to be natively digital they’re, going to be created on a substrate. That is data by its very foundation and, as I put it, playfully they’ll be staffed by BOTS, not brokers by AI, not by actuaries, and I think that this is a bit of a challenge to some of the inshore techs ourselves included, which is to go for Gold to look at the big prize not simply to saw to sell tools to existing companies, but to look at the fact that companies that succeed in this place that become the brands of tomorrow perhaps have the promise of a hundred of 200 years of dominance. And very very size able business.
How will how will this play out? What shape will it take? I like to phrase this as a question of. Are we facing a Wikipedia moment so Encyclopedia Britannica started in their 1700s roughly the same time in the same place as Lloyd’s of London, and they both did very well under trying circumstances. They weathered the Napoleonic Wars and the Revolutionary Wars and two world wars in the Spanish flu until in 2010, Britannica encountered a website, and that was just too much and Britannica folded and it, of course, doesn’t exist. Anymore. Britannica brought out 15 editions over it’s two and a half centuries Wikipedia updates ten times a second. It has 30 times more content just in English, not to mention all the other languages and it doesn’t cost a thousand dollars. It’S absolutely free and it’s searchable and pocketable, and its advantages are very clear and the question that I’ll leave hovering out there as a meander through the journey of lemonade. Abhart is, is our industry? Is the insurance industry facing its own Wikipedia moment? I let that one linger and I’ll switch gears for a minute, and I’d like to tell you a little bit about how. As I say, I want to indoctrinated into how we think a little about the challenges that we face as an industry and then a little bit about how we are trying to solve them and how those attempts have been received during our short time in the market And to do that, I’m gon na travel with you back in time we’re going to start not in the 1700s but in the 1300s, and I like to start this off with Francesco Francesco.
Is writing letter to his wife in the 14th century in Florence and is complaining about insurance companies and what francesca writes is. It is sweet to them to take the monies, but when disaster comes, it is otherwise. Each man draws his rump back and strives not to pay. Now I confess I don’t know exactly what that means, but I don’t think it’s a compliment unless you think that well, this was a long time ago times have changed I’ll. Take you seven hundred years forward in time to the urban dictionary, the crowd-sourced dictionary that defines terms, and we look at the term insurance which, since 2008 has been been defined us a business that involves selling people promises to pay later that are never fulfilled. Channeling Francesco. Just in a more contemporary language and for good measure, the urban dictionary adds the usage of the word as good dictionaries. Always do Goma paid flood insurance premiums for years, but the insurer decided to go out of business when the flood came, because management had spent all the premiums on hookers and private jets, not too auspicious you want to know the pulse of the people. Look up open dictionary now we can argue all day long about whether the reputation that has survived intact since the 1300s until today is earned and deserved or not. I don’t want to spend any time on that question. What definitely preoccupies us at lemonade and should preoccupy asses and industries? Why does it persist? Insurance is, and certainly should be, a social good, not a necessary evil.
Why? For seven hundred years have people been bickering that it’s all about taking the monies and not parting with them when the claim comes, and that perception doesn’t only mean that people don’t want to buy insurance and all these truisms about insurance is sold or not bought and All that kind of stuff it actually drives economics and behavior 25 % of Americans tell people when surveyed that it’s okay to embellish claims. I like to quip that the other 75 % were brought up not to admit that kind of thing to strangers, but think about that 25 percent. It’S very unusual. Usually fraud is people, stealing credit cards and hacking in and all that kind of stuff. No, no. No! The fraudsters are normative people, it’s us guys. We regard ourselves as law-abiding citizens, we abide by the law all the time and then, when it comes to insurance, we let the devil out, and then we go back to being law-abiding citizens. Something about insurance brings out the worst in humanity and, in fact, our chief behavioral officer, professor Dan Ariely, who spent ten years researching this reached the conclusion that if you tried, if he set out to create a system to bring out the worst in humanity, it would Look disturbingly like an insurance company just about every facet of what you should not do. If you want to bring out the best in humanity is manifest in insurance companies. Now I want to show you a two minute eggs out from a two hour documentary that Professor, I really made. The one thing you need to know, since we’re going to jump into this middle of this documentary is that one of the experiments that he ran involved? Having people fill out, maths questioners doing maths exercises and then he would have you mark your answers that give you the answers. Mark them, you’d come to the front of the hall declare I got seven right, you’d read the document and then he’d count out seven dollars.
His shredder is doctored and he can see whether for one dollar you’re willing to lie or not, and then he can play with different parameters. We’Re going to see two variants of that experiment, and you can see how impactful behavioral economics can be on fraud. Let’S watch together, my name is Dan Ariely and I’m interested in human behavior. In the last few years, we’ve been focusing on dishonesty as long as which is just a little bit. We don’t have to pay any price in terms of the image and the way we view ourselves and we call this the fudge factor. So this is the ability to misbehave and think of ourselves as good people, and you can think about all kinds of ways in which, in your own life, you have a fudge factor the speed limit. Maybe it says 55, but are you okay in driving 60? What about cheating a little bit on taxes? What about exaggerating their online dating profile across many studies? We find that everything that changes the fudge factor, also changes people’s ability to be dishonest. There are dozens of elements that can change the magnitude of the fudge factor and we’ve been able to observe many of them in the lab. So imagine this the same experiment I described earlier. You fill in your sheets. You solve these little problems. You shred the piece of paper and you come to the experimenter. You tell them how much money you deserve. You tell it in tokens. I solved X problems.
I deserve X tokens, so now you pay them in pieces of plastic. They take this piece of plastic, walk. Twelve feet to the side and change it four dollars. So when somebody looked you in the eyes and they lie, they don’t like for money, they lie for something else, but that thing becomes money very quickly. What happened in our experiment? People double their cheating. Thank you. We went to UCLA and we asked about 500 undergrads to try and recall the Ten Commandments. How many of them do, you think, recalled all Ten Commandments zero, that’s right by the way they invented lots of interesting ones. What happened after people tried to recall the Ten Commandments, even if they weren’t successful nobody cheated okay, so dad’s experiment shows and he’s got many variants on this, and tremendous amount of research has gone into this so in social sciences, but I just showed you two simple Variants in one you’re asked to recall the Ten Commandments before answering the questions in another. The money comes only after you convert it from tokens, and these two ridiculously simple steps had dramatic impact on the cheating right. It brought it down to nothing in one event and doubled it in the other.
So the impact on the kind of trustworthiness and the way we behave is easy in the best sense of the word to manipulate. In other words, it can be something that we can bring out the worst in people or if we construct the game differently, you can bring out the best, and I have to say that we don’t first, second believe – and I’ve been called on this a couple of Times so let me be very explicit. I do not think that there are any bad people in insurance, or at least that that is not a prevalent problem. The problem guys is not the players in our telling it’s the game. We’Re big believers in game theory. We’Re big believers in the ability of a certain game to predict outcomes, and in this particular game the outcome is highly highly easy to predict. Conflicts of interest and perception of conflicts of interest, bring out the worst in people’s in the ways that I’ve spoken about. In other events and work won’t belabor the point too much, but what this did do for us is it drove us to create a new kind of insurance company? We didn’t for a second believe that sprinkling technology, pixie-dust style on top of an existing edifice of a hundred-year-old insurance company, could affect profound change. It doesn’t mean that if you work in one of those edifices, you shouldn’t sprinkle technology on it by all means, do but understand that there’s a glass ceiling to how much impact that can have and for us rebuilding insurance from the ground up and all the hard Work that that entailed was in order to be able to create this substrate that I spoke about earlier of social sciences and Computer Sciences, behavioral economics and AI, and to create a business model where we do not make money in denying claims where we take a flat Fee that we write about and have spoken about on our website. So a lot of the behavioral economics.
All of Dan’s research plays a role in the business model, but also artificial intelligence and I’d like to show you how they interplay between the two and we really see them as being highly complementary to one. Another can hopefully affect meaningful change, so start off with the idea that we take a flat fee and we donate to charities Charities of your designation whatever’s left over if, indeed, money is left over now. On the one hand, that signals and signaling is an important part of game theory. It signals a lack of conflict of interest, the idea that we don’t pocket that money anyway. It hopefully elicits better behavior in us, because our hands are tied. We have no incentive to deny or delay your claim, but I’m hoping that it also brings out better behavior in our customer base, instead of letting the devil loose when it comes to insurance. What happens when you’re met with a screen? There reminds you that your claim is not made as against a nameless, faceless, huge conglomerate with whom you feel you have a conflicted relationship. But if you’re excessively claiming you’re hurting your kids school, which you designated as your give back, cause, go back to Dan’s research and think about how much that can have a binary effect on our behavior, not so much to bring crooks in line. But to make sure that the folks like us who account for most of the fraud in the first place, stay in line all along time will tell we’re young company data is still gathering, but in the last few weeks we’ve had six customers return claimed money. We paid them and they individually one by one contacted us, hey the laptop turned up I’d like to return the money. How do I do that? We haven’t got such a big book of business. Six claims in as many weeks is an unusual number to come back and the old time is in our company, tell us that they hadn’t encountered anything like it, so it perhaps down was on to something.
But the other piece is that if you manage to lower the conflict and if you manage to neutralize any desire to deny or delay claims, that’s when a I can click in. We made a bit of a splash by announcing that we’d paid claims in three seconds. We now pay about a quarter to a third of all claims instantaneously that happens on a substrate or on a basis of a more trusting relationship. These aren’t binary outcomes, but a more trusting and if you do not have the incentive to pay claims instantaneously. Even if you don’t have a an elevated level of trust relative to today’s baseline, it’s very difficult to offload this to a bot and say: hey, just go and pay the claims. So to us again. This AI in behavioral economics, interplaying, is really very key to how we pay our claims. Let me give you an insight into some of the results so far, some them quantitative, some of them qualitative. The first thing: I’ve noticed, we’ve really been Whistlestop working. We’Ve really been overwhelmed by the reception by the consumers. Insurance is not something that people tend to get excited about. If people tweet about insurance, it tends to be with expletives and not the kind that you want and yet we’re finding a tremendous amount of sharing of virality of word-of-mouth around what we’re doing, and I think that if I try and analyze it for you, it’s really A cocktail of three value propositions that are, inter playing in a really powerful way. One is value for renters in the u.s. today we’re able to offer a policy that is dramatically cheaper, oftentimes, 70 or 80 % cheaper.
We’Ve got a blog post explaining how that can be done in the context of insurance. We can’t do it across the board, but for entry-level insurance, renter’s insurance. We can and sudden you get to a price point that is an impulse buy. Insurance has never been an impulse buy, but five dollars a month, which is our most popular product, people are discovering it they’re buying it. They didn’t set out to buy insurance that day, but they end up buying it. The process is seamless. The price works. It’S a cup of a price of a cup of coffee, as a few of them have told us it’s cheaper than their Spotify, so they go ahead and make the purchase. So the value has been a key one. The values is the other one. So I spoke about avoiding conflicts of interest. I think all of us, and particularly the youngsters, find that values and mission driven companies speak to them in a way that traditional insurance has a hard time speaking to them, and here those 700 years of pent up animosity. Perhaps help young companies like ours, people want to root for the David versus the Goliath and that place and helps us no doubt, and then the third part is the technology. There’S no question: those of you have played with the app get the experience and understand that insurance can be fun. It can be playful. It may not be something that you want to spend all afternoon doing, but when it surprises you and at the end of the process is like well that was kind of cool you talk about it, you share it. It surprises you and a gate, as specifically against explicitly against the backdrop of rather lowered expectations so again that that helps, and that has translated into some significant results, albeit very early.
The company is still very young, and I think we can all agree that it takes some years before. We really know how an insurer is doing and what you’re seeing here is our weekly sales numbers, and you can see that what we’ve really been experiencing is exponential growth since launch we launched just over a year ago. So this is basically one year of sales. What that translates into is about seventy thousand policies in our first year so still by traditional standards, a small book of business, but blew away our expectations, we’re now selling in one month more than we thought we’d sell in one year. So for us, this is way ahead of anything that we’d predicted or expected and we’re thrilled with it. I’M going to show you a graph that looks similar but actually starts coming back to the AI piece as well, and this is something that we haven’t spoken about. Much policies per human or policies per employee, one things that we’re finding incredibly powerful and we’re tracking pretty religiously, is how much we’re able to scale the model. How much are we able to use technology instead of people and in our company, as with many and Shore tech companies or startup companies in general technology is not a cost center. It is the company and one that, when the folks in finance say to me Daniel, we need another hire in finance because there’s a lot of regulatory filings, my aunts invariably is you need a person in finance. So do we need another engineer and when support says, hey we’re short-handed, we need another people in support.
I say: do we need another support professional or do we need another engineer and I’ll tell you that nine times out of 10? The answer is, we need another engineer, because regulatory filings or financial reports can be done by BOTS. Support can be done by BOTS, adding jewelry or changing coverage can be done either by the consumer by BOTS and as soon as you think of technology. As the core of the company, not a cost center, that’s building a website for your product. It is truly transformative. What we’re seeing already is that we now have about 1,200 policies or customers for every one employee that we have so. Seventy thousand customers policyholders less than sixty employees. We think we’re going to go to ten thousand. My understanding we haven’t done an exhaustive survey. We just sampled a few of the largest insurance companies. I think the number today is already better than most of the large insurance companies and the trajectory is pretty compelling so again the interplay of technology, and that translates the scalability translates into Geographic scalability. We just launched a seventh state in our first year of operations. We’Re licensed in 22, we’re live in seven California’s by far largest state, it’s one of the largest states in the u.s. in all of California, north and south LA San, Diego San Francisco Silicon Valley. We have rounded up to the nearest number zero employees. The closest employee in California, is five to six hours flights to the eastern New York and we’re able to really grow and scale an entirely virtual manner.
So the digital platform allows for very rapid deployment and massive scalability. We launching state after state when we get our rates and forms and licenses approved, we’re usually live within 48 hours and without having to move any people around and we’re using BOTS in ways. That may be less obvious than just looking at our website. So when you onboard with us Maya, I bought asks you. If you have an existing insurance policy, Maya then cancels the policy for you now that isn’t just a front-end form that generates a task for somebody. In the backend to do actually no human being does it our systems have a database of different insurance companies how they like to receive cancellations to what address what fax machine invariably and Maya produces. The letter sends it off and no human beings are involved and the list goes on and on how were able to use AI and bots in our back-office functions, not only in our consumer facing ones. We launched an API a couple of weeks ago. The idea that you can teach a bot talk to human is cool, the native tongue is a machine and they love talking to other BOTS, and if you can get insurance in 90 seconds when talking to a human, you can do it in 90 milliseconds when you’re Talking to another machine, so we think a lot of the future is going to go through api’s, once you’re able to generate bindable quotes algorithmically, allowing a machine to talk to a machine and becoming embedded not only on our website and our app, but on a gazillion Websites and a gazillion apps is an incredibly powerful thing and again bespeaks of scalability, and finally, I think that this kind of an architecture and a digital natively digital company allows for transformation deep in the insurance product itself. So, a few weeks ago we launched our first foray into this, and this really is just the tip of the iceberg. We launched something that we call zero everything, so it costs you a little bit more. You can opt for this when you buy a policy, but you can have zero deductible, full replacement value and zero rate hikes. If you make a claim, you claim that thousand dollar laptop today with most insurance policies, you’ll end up getting $ 300 by the time.
You’Re done away with the deductibles and the rate hikes and everything else, and you may say to hell with it in your field cheated and tremendous animosity and in fact most fraud and insurance equals the amount of the deductible. So you think you’re gaining a lot by adding the deductible. It ends up getting netted out by the fraud often times, but in part the deductible is that in part, is there to deal with the fact that claims are so expensive to handle. Small claims are known as nuisance claims and they’re known for that, because it cost me five hundred dollars to pay that five hundred dollar claim and if I want to limit, I want to really do away with these small claims. Well, when you’ve got something like AI Jim, I bought, he loves small claims. He doesn’t know how to deal with a house that burnt to the ground, but your laptop was stolen. He’Ll deal with that at zero lae. The LA in the u.s. in our sector runs between ten and twelve percent. Ten to twelve percent on the dollar in the u.s. goes for the bureaucracy of claims, but the high frequency low severity claims can be handled by bots with tremendous alacrity, and that enables us to start to introduce new kind of insurance products because you change those fundamental Changes in the economics can drive fundamental changes in the type of coverage, the type of policy, the type of value proposition, and with that I come back to my opening question I’ll, be facing a Wikipedia moment in insurance and, frankly, my answer is no. I think that you’re not going to see the sudden collapse of any major insurance companies if you do would be a surprise to me. I don’t expect this to be a repeat of what happened to Encyclopedia Britannica, but I do think that industry is facing an amazon moment, so in 1999, Baron’s had the cover that said that the idea that Amazon, CEO Jeff Bezos has pioneered a new business paradigm is Silly he’s just another middleman and the stock market is beginning to catch on to that. Well, hindsight is a wonderful thing. They were right for a while when they wrote that article Amazon stock price was at 62 two years to the day later, it was down at 14, so had lost 80 % of its value over the following two years. They must have felt pretty smart. They were able to predict that this was a bubble, but of course we know this story, it’s grown ATX since then, and I think the message and their metaphor the analogy to insurance isn’t perfect, but it is telling the large retailers no. This is coming right. They see it, they gather in conferences such as this. They create innovation departments, they acquire tech startups and they all create websites with e-commerce. What are they doing wrong? Walmart huge purchases? Why is it that the shift in value has been so not sudden? 20 years in the making, but so dramatic – and you see that with every cycle that turns it becomes more and more of a runaway success, and I put it to you that this is very similar to the insurance situation, where the assets become liabilities. So it may be true that in front that retailers created websites and engage in e-commerce early, but they still had this albatross around their neck of the old culture, the old installations, their own world, rent agreement that they had the obligation. The quarterly results that they still had to meet, they had the classic innovators dilemma, and it is almost unprecedented for company to cannibalize itself, even if it sees the tide coming that Kodak moment where digital film comes along Kodak saw that coming. I spent many years at SanDisk and I used to call that the Kodak moment of the company, because it really displaced chemical film, the execs at Kodak, saw it coming, but it doesn’t matter if you see it coming affecting that a deeper change in jettisoning everything that You built over the last hundred years in order to jump ship to a new paradigm, is almost unprecedented. Almost never ever happens. Might it happen? Insurance yeah conferences like this might just affect change, but I put it to you that if it does it’ll be the first time in the history of the world that it has their ups, my presentation, I really thank you for your attention – have a great day.