The. Time we have will. Get some perspective and insight in terms of how this. Six trillion dollar industry, the. Insurance, industry, is. Being disrupted, and. So we've has we we have way, who's. A founder, of a, company called accident, that's essentially. Going to. And, is disrupting. Insurance, so. Way before we we get started, maybe it's in, a wharf basically. Giving, us, a sense of what axonal, is all about what is a vision of axonal, and what are you trying. To do in. The insurance industry. Thanksful. And yeah. So my name is way too, excellent. Is a short. Text art based in Singapore. And. Actually I have a very. Short video. That we can use to describe. A little bit sure. The. Global, insurance industry, is set to grow at a faster pace than the global economy, in 2019. And in. 2030, we, expect premium, volume, to be close to eight trillion, euros, almost. Double what it is today. But. This gargantuan, and ever important industry, with over 300, years of history is plagued. By legacy IT systems, high, manual, intervention, and lack of customer, satisfaction. This. Results, in massive, amounts of untapped, data missed. Opportunities. And distrust. Amongst the customers, how. Are they going to sustain success, in the digital age, we. At arc sanon are leveraging. Data and technology, to transform, this our. Neural, network based machine, learning algorithms, enable. Us to process, and analyze millions. Of complex, unstructured. Data points, in real time to, produce risk profiles, and customized. Premiums, in milliseconds. This. Empowers, Asia's, leading e-commerce platforms. To have the entire online shopping, experience insured. Returns. Damages. Lost, parcels, quality. Issues and more, the. Same tech expertise, powers, are direct to consumer, product, igloo, with. Customer, centricity and fraud, detection at, its core our phone. Screen protection product, leverages. Machine learning algorithms, to examine, screen conditions, in seconds, regardless. Of lighting and environmental, variance, this. Enables, us to issue policies, instantly. Seamlessly. And with minimal, margin, of error so. What's next well. With. The accelerated, growth of smart, technology, and Internet, of Things the. Only limit to our impact is our, imagination. Great. Great, introduction, and and and great overview I guess, my my, first, question, is you, know why. Insurance in the first place of all, the industries. That potentially, you could have gone after why, insurance what attracted, you to to. To the industry. Yeah. Thank, you that's a really, good question and, people ask me a lot, even. If, somebody asked me like say five ten years ago would. I ever see myself you, know in the insurance industry I, would, say no. So. I actually don't have backgrounds. In insurance. Before. I started, accident. So. Yeah my my, prior you, know career over. You. Know last twenty, years it's. Just all that's been in the tech space you know I, was, I, was, at Facebook, I was at Microsoft I, was also that right sharing company in Southeast, Asia. So. So, why insurance well. I think, it bikes you. Know my experience working at either post Facebook, as well as grab in Southeast, Asia is that. You. Know when you see a old. Industry. That. Has you, know baby hasn't moved, the whole lot for, a long time and, there. Is actually, great opportunity, for you to go there as a, technologist. And try, to disrupt it we. See the same thing happening with how, uber, you need to stop it, transportation. Industry, which you know again I think you know was something that's pretty much under, serving the customers, and I. Think, in many ways people's, feeling about insurance, industry, is also. Not a very satisfactory. And I, think that's where we really see great potentials, yeah, yes, so. Everyone. A, little bit a sense of what's happening in. The industry so, if you look at the flows. 2002. Ish there. Were about 300, million or venture capital funds that are going into that right. Around 2018, is about four billion so lots. Of activities, lots of interests, in. Insure tech obviously. A lot of that is happening here in the US I think about 2/3 of that but, but Asia is where accident, is and we also know there's a lot of sort, of business model, innovation. You. Know happening in, Asia and specifically, we've seen you, know startups, like strong and built, their, businesses, on on sort, of Alibaba. Top platform, so these ecosystem. Plays, just. Just want to have your sense of it. You know what is that something that action on particularly. It's playing into sort, of these ecosystem. Model and trying to tap into pools of customers, you. Know to distribute insurance yeah. Definitely.
It's One of the areas, so. Asia, as you mentioned, is. Seems. To be kind of recently, hotbed, for a lot of innovations, on FinTech and. If. We look at the areas that we're focusing on in Southeast, Asia the, insurance, penetration, is really low it's only like 2 percent so. Peoples. Are. Like, familiarity. With, traditionally, insurances are not, that great and also, you know in the last few years the. Very, rapid, you know purification. Rapid. Adoption of smart. Devices smartphones. I think. Enabled. A business, model we, really tried to go pure, digital pure. Mobile, focused ones and. That also involves, working with what. We call the digital economies. Like, the e-commerce, players. Which, are growing really fast in Southeast Asia, so we're. Potentially, trying to create business. Models, on p2p site that, integrate, tightly, with. E-commerce, travel. Sites etc, to, address. You. Know various, scenarios. That happen with the, new digital economy, so, on the e-commerce site the, first, part of that we introduced what's. Called return insurance, so, this is what people go shopping online and, if. They don't like a product they can return it, typically. In the US the buyers in the Amazon is. Shop. Owners who bear the cost of logistics, for. Returns but. We are making that as sort of an insurance form so, that you, know you. Know the insurance company, will actually bear a risk when it comes to returns so, that that's one of the example we're doing for you. Know the new economy, on the creative scenarios, yes. I think one, other thing that you know you talk about is its how you are, trying to I think, part of the objective of the companies actually to come up with products, that actually. Basically. Try. To address the. Lifestyle, needs you. Know if customers, in. Asia in general, and. So you mentioned return insurance, I mean can you talk about you, know some of the sort of broader needs you. Know that you're seeing in places like Indonesia, when. It comes to insurance. Yeah. So for. Us, we. See there's a you, know a large. And, young population. The. Millenniums, and and, those. People typically, don't, have. Exposures. To insurance. Not. Very you, know like well. Versed on, usage of insurance, and it's typically. Actually the, kind of type of generation, that. All, insurance company, are pretty, desperate trying, to get. Ahold of, so. For us I think we, want to reach. To that population. And also to solve, some of the other issues related to, you. Know I. Would, say income. Protections, if, you look at Southeast. Asia. It's. Still very much a developing, country you. Know outside places. Like Singapore so. There's a very, large population, of people who you. Know, really. Need protections. Because the, social, safety net in those countries are typically not that great but. Traditional, insurance products, are. Not very well suited for that, population, the. Premiums are pretty high and. You. Know it's disproportionate, to people's income, so. We think that's if we build you know from scratch a really, digital, mobile focused, mobile. Focused. Insurance. Product that. We can significantly reduce, the. Fixed cost and overhead, so that we can really truly go into offering. Various. Micro insurance to people. That's. A, good point around sort of affordability, of all. These products, and I think what. What we're seeing is this micro, products, or these on-and-off products. That. You know customers, will obviously. Easily. Purchase. Online now. One, of one, of the question, those I obviously, technology is coming in to drop, you, know more efficiency, and. An, affordability. But. What are your thoughts around you know financial, literacy obviously, in. Some of these markets like the at Nam or Indonesia. You. Know the the the the, understanding. Of even. The needs of the financial, need is not, necessarily, there is action on actually. In, addition, to. Obviously. Being able to distribute directly. To. To these customers you. Know what are your thoughts around financial literacy and how, obviously. Technology could actually enable. That in in in that kind of scenario yeah. Great. Question and for, us I think our. Goal is to make. Like. Some other financial products, such as insurance. Make, it simple make it easy making it more accessible to people. A lot, of times in the, traditional, insurance world you. Need agents, because many. Of the insurance products are pretty complex and if you read their Terms, and exclusions, it will take forever and that sort of also you, know kind of keep that. That. Segment, of you. Know each, financial. Part away from people because their intimate, it is they don't have time to deal with this massive amount. Of complexities, so. We. Wanted to start with something, that's simple and that's something that address. People's, needs at. Smaller, level okay so so. Like the, first direct. Consumer, product, that we introduced. Just recently, is. It's, called the phone screen protection insurance, so.
What It does is actually very simple we're. Just trying to provide a very. Very affordable, insurance. For. People's, smartphones. And. You. Know if you think about phony, insurance right a lot of times people think about Apple, care right but that's like $250. Or $230. You. Know for premiums well, we like, our scream protection. Insurance costs. On average I, think. Five dollars. For. One year of coverage, to protect your screens and, and. That's, you, know and that's purely down through a mobile app and. Our hope is that through the technology, where we really, automated. The underwriting, and. The, verification. Of screen conditions, and the, whole thing goes to a, very simple, claim process. And then hopefully our hope is that we, build a bunch a little micro. Insurance, product, that, will actually educate. People to, get. Started to say oh this is you, know this insurance is actually useful, and, simple. And then. Gradually. We can introduce, more and more product, all. Around the simple, and easy to use and, sort. Of micro insurance scale, level and hopefully, that will be really. Like get into the younger generations, mind, excellence. Like I guess my just, a quick one on that top, around. Distribution, so you mentioned. Agents. Obviously if, you look across in. The region, there's thousands, of these agents you, know still selling insurance product, and part of part, of the issue there is a complexity, of these products, and and ultimately how you get customers to understand, you. Know what those products actually. Are, about do. You do you think that you. Know as the rate of adoption or technology. Increases. You. Know in the insurance base, do. You think that the agents, are going to completely disappear. Or, you know what what's your take on that. Yeah. For. That I probably owe to, an analogy. To you, know the. Other side other business such as you. Know ecommerce versus, traditional retail business. Ecommerce. In the last 20 years has, really developed significantly. Right you see the. Growth of, giants. Like Amazon. Like. You know in China. Alibaba. So. Many. Women of, course in South since there are many big players, but. Even, even. If you see like Amazon. Alibaba, being mentioned everywhere, being, the Giants but, the. The total, penetration, of, you. Know ecommerce as a percentage. Of. Retail. Is still, I think is on average less than 20%, and. I, think the. On. The insurance site would definitely see significant, growth for, pure, digital insurance, but it, started on very small base so. I you. Know I think will be extremely lucky if we get to like 20% you. Know by, you know twenty years from now and so. I think there, still will, be a very, large role to be played by traditional. Agents, in networks. Switch. Gears, a little bit maybe a little bit of, so. We. Got these unicorns. And these massive platforms. Already in Asia it's, good, names here and I think we, have will, have go check at some point on stage. You can go check tokopedia etc. And. And, then we see these super. Apt sort. Of type of morals, in Asia right, so you know if you look in China, with we've got you. Know we've got recharge, you, know you go to Japan. This Rakuten, you know etc so, and. And, I know there's some of these sort. Of massive, platforms. Are now extending. Their offering you. Know to go into insurance and other financial services you know, tap tap offerings, so. What. Is your view um you, know this notion of super, with, pretty much everything in one place seems, to be an Asian phenomenon. I mean what's your take on how, successful, you think that model is gonna be and why, is it not necessarily, showing up as much I guess. In the US for example yeah. It's. A fascinating topic and, I, myself. I spend probably like you, know half of my life in America and they, have the other half of my life in China and Singapore, and. Sort. Of yeah I think I've experienced, both side and is really I think, it is kind of a it might be a Asian phenomenon, where. You, know you see the big players in Asia they. All wants to be. In. Some ways they do one wall builds a super app and what, is super up some ways I kind of feel like there's, sort of like a walled.
Garden. Thing. If, you look at America. I. Guess, we're super, happy if. There was one was, probably like long time ago like 20 years ago when when, there was this thing called, American. Online a, well, how. Many guys still remember area. Yeah. Sort. Of the area was actually before the internet and. An, AO was. You, know like the. Giant Ani today's right it's like basically, the, when. We talk about online we're, talking about AOL. But. But, you, know the the the downfall, of AOL, was also very rabid as. This, new medium, of internet and web browsing come. As well so, I. I. Think the jury is still out there, it, it, will be interesting to see I definitely see tremendous, success. Asia site, especially. With Tencent, and. Their wage had platform, it's, incredibly, useful if. I, was if I was Facebook, I would, definitely want to build you. Know payments, I want to build mobile payments and there's, a whole bunch of things it's the financial services that are really interesting. But. I think. Yeah. It's I don't know I don't, know why yeah. Well. Let's let's begin to into. You. Know the AI side, obviously. Insurance. Is is you know the insurance company use a lot of data obviously. To be able to, you. Know assess risk and price, risk you, know can you can you talk about how you, know using AI. You. Know to actually. Improve. The way you're looking at you know reflection and reser pricing. Right. We. Are lucky in, a, way that because we are a tech, startup, and, like. Almost, everybody, in our company actually come from you, know technology companies, and not from insurance, industry, so we, also have a chance to be able to like. Build many, of the stacks. Involved. Injuries. Value, chain from. Scratch so. That allow, us to really. Build our, own like, you know pricing. Engine and risk assessment. Using. The latest technology. Now for example we've. Been working with Google and using, Google cloud as. Well as, Google's. Ml. System. So. Great example, is that when, we try to assess the. Risk. Of a consumer. Returning. A product, that they bought online, so. We. Basically. Gathered. You know over the time you. Know millions of transactions. And. Then we, try to build this what we call a real-time risk engine that's. Gonna try to price, risk at individual. Transaction. Levels and then provide a premium, at individual. Transaction levels we. Started off without using a I because, I don't have any data right so we, just build simple rule engines to, do that. And then as we, got some data we started to you, know start building that machine.
Learning. Model you. Know by, partnering with Google, and. You. Know the beginning we actually use a system that has I think are are the. Weights is like more, than 1 million attributes. Later. On we did to the model. Compression. And reduce that and. You. Know so. That's actually. Give us some really very interesting, results, I one. Example I gave is that our. System, found, out that. Whenever. A, product, description. Contains. The word B, does. The. It's, an indicator of higher. Risk of returns so. At the beginning like you know we didn't know why but. Then you if you actually go see the products, yourself then. You realize oh it's. Actually. Those guys are selling shoes Abby does shoes, it. Does remind you of adidas. But it's not so. As we turned out those tend to be knockoff, shoes that, people weren't at some store the selling and other. Reason how much they actually have a higher chance of returns is, again, those are all things that you, know with. The, machine on your model that we can build things I think much faster. And much more accurate, than, if I were trying to attempt to do that with as. A traditional, rule based engine, and. One, of the things that your video pointed, out is is, the fact that the industry is obviously plagued with you. Know in efficiencies. You. Know manual. Intervention, etc, we. Can you, address the topic of automation, in. Some of these processes and, and how, you've been able to potentially, reduce. You. Know either processing, time things. Like claims, etc. Yeah. Definitely. So so for. Us we we try to automate it whenever possible, and. Try. To build system, that has a potential, to really, scale horizontally. So, good, example that we. Need a price to. Post. The underwriting, as, well as the claim processing, is how. We use. The machinery. And the computer vision for. Our underwriting. Of the phone screen protection, insurance so, our phone screen protection insurance allow you to basically you, know buy. Insurance, for. Any phone even if it's used phones you know typically, insurance for formulas is you know you can only buy at point of sale when, it's brand-new when. The insures, knows the condition of the phone so. So, how do we so then the question is how can we easily. Detect. Existing. Cracks on a, phone screen because. In, some of the other our countries, like China where phone. Screening just dedicated, phone screen insurance also exists, the, the, basically the number one, concern. For insurers is the. What we call the moral hazard where. People you, know buy insurance and they go that's already their phone screens or it cracks the next day they.
They Go make a claim and we, want to do it in such a way that still. Make the user attorney, to be extremely, simple and friendly and fast, but. At the same time reduce, the fraud and so, that's why we used a. Combination. Of computer vision and machine. Learning so, so, we built a pretty interesting feature, where. Our app will ask users, to go take a selfie, with your, phone so so. That it will just guide you, to. You know to bring your phone against, the mirror and, and. Then then, our computer, vision system will recognize the exact location, and position angle. Of the phone and it, will guide you through. Through. Like hin so through like you know like command, says you, know tilt turn, put. The closer and he, reaches a sort, of the optimal. Position. Where, we can take a full screen shot of, the. Of the of the phone and. But. Then at the same time, then. We will start to overlay, a, digitally. Signed. Signature. That, contains, all the attributes of, your phone unique signature, of your phone and bunch of other. Anti-fraud, features, and then. That one gets submitted to, our back-end so. Then, that's where we, use a. Deodhar. Machine learning based system. To detect. The features the. On the phone to detect if there's any cracks and so. That combination it. Really automated, process, and, made. It significantly. Reduce, you. Know can never claim hundred percent you know, no. Fraud but significantly, reduced it. I. Guess. They're a world you. Think where. You. Know all of those things will be automated obviously, you've got you. Know IOT, devices you've got sensors, you've got you, know all sort of stuff that's coming through that, that. Might enable that you, think we're going to get to a world where if essentially. You, know the entire claim process, and some of these back office processes, will be fully. Automated without. Any human intervention. Um. Yeah. I would say probably like 99. Or 99.9. Percent will, be automated, eventually, they're. Always going to be some outliers, that requires, human, intervention, but, yeah. I think if you look at how history. Repeats itself in, other areas. It's. I think, I think it will happen yeah. I'm. Engineer, so. Let's. Touch on one of you, know the pain. Point that. You know obviously insurance, companies have you. Know been having. For for some time so fraud, is a big deal in. Insurance, and billions, and billions are actually lost, every. Year because, because, of fraud so. How. The accident, set up to actually address the issue in. House technology, is essentially, protecting, in. The company not to be exposed to fraud for example, right. I guess. They, the, way that we are trying to address fraud. Is relooking, other ways to do. As much automation, as possible, and. Use. You know a combination, of machine learning as well as I, think, quick iteration.
The. They. Wanted is that. The. People complain about traditional. Insurance companies, are, they're. Just pretty slow to adopt. To. Changes. And. A. Lot of times you, know like things that I've learned working. At, tech. Companies, that, you. Know sometimes. It's really the process, of. Execution. That. Is really important, I. Think. For us it's about taking actually, its benefits, it's. Been funny that you, know we're sort, of an insurance company but where. We need to take risks it's. About taking, calculated, risks. Breaking. Things that move fast try. To iterate. By. Fast. Execution. And and. And be. Willing to automate. Things and be willing to take risks. So. There's a there, was a bold statement by, Peter. This morning about the. Fact. That you know as, AI. Evolved and our ability, to be able to. Predict. Risk, you. Know with very high confidence you. Know we'll live in a world where insurance, obviously. The need for insurance will cease to exist I mean what's, what's your take on it yeah, it's great great question yes so, actually. Peter. Came up with that that. That. Thoughts when, I asked him a related, question yesterday. We. Didn't have a chance to debate about it yesterday. Unfortunately. He's I'm not sure if he's here. But. I. Think. Luckily. Or. Choose. A sir. AI. Is, not like. The greatest it's not like so Shinto everything, and AI is not, it's. Not an Oracle if. I reach a stage where he can predict, with, 100% certainty, of. Of. Events I, think I, think. Probably the moment of singularity, already have reached and he in, trouble. More. Likely what, we're. Trying to do with AI and, machine learning is, really, to help, us improve, the, odds so that we can do a better job of, particular. Risks but, it's still gonna be a, percentage. It's not gonna be a hundred percent certainty, and when, you don't have a. Hundred percent certainty. In. In, you, know various, things that you do in life with this business where, it's your house you, will still need, protection. To. Give you a safety net so, so. I would say insurance is still. Gonna be needed no matter what and hey, I would actually help to, make the insurance, more. Efficient, more, fair to people yeah. So, one, area that's actually. You. Know been you, know interesting, for for for insurance company in general is this notion of prevention. Right. Which essentially, with, you. Know the power technology, we are able to anticipate, in. A certain event and as a result, you. Know take action, and and and in fact it's you. Know some of these insurance companies looking at this as a way to you. Know provide, meaningful, services. To you know today customers, know. So we've seen companies. Going. To things like smart, you, know you, know smart, smart pipes, you, know water pipes etc you, know smart smoke, detectors, and combining, all that to be able to anticipate things, like fire and water, leakage etc, and where, does that fall within the vision of AXA not you know, especially when it comes to smart living yeah. It's, a fascinating area I, think. You. Know one. Of the things that you know accident is really passionate about is to. Build, insurance. Around various. Gadgets and, smart devices that. People will have, around, their homes on our living so, we. Started, with you. Know phony. Insurance but. Then you know on. Our roadmap you providing, a general, whole, range of gadget. Really the insurance but, as gadgets, get smarter, there's. Really, great potentials. To actually benefit, people's lives. Make insurance. Better. For people especially. For example I, have. Like air purifiers, that are. Actually quite smart yeah it's it. Actually it's Wi-Fi connected, it, detects, the you, know particles, and smokes, in. The room and similarly. You know if you if you buy some of the robots.
The, Cleaning robots they they're also pretty smart right imagine we can just add a little bit it publishes, some software, into that and we. Can turn those, you, know smart. Devices in your home such as your. Air purifier to, become a better. Smoke detectors, we, can make, your cleaning, robot to be able to detect. Moistures. Right because clean robot you, know my name is may actually detect, moisture, you can use that to be able to help detect flooding in your room and. Similarly, small. Locks. You. Know I think recently, Amazon. Had bought, a. Manufacturer. Of startup for smart lock for like a billion dollar because they want to look, into that for you know like helping, with last mile deliveries, but, that, also is connected device and you can do very interesting things, in terms of help with. Home protections, you know to, reduce theft. And other things and not have direct, implications to. Insurance, so, I think there's lots pace, that we could do and it's something that accident, is, is very interesting, exploring. To, be able to utilize, the. Smart devices to. Make insurance, cheaper. Easier. For. Consumers yeah, right. So. One, other thing that we notice, and especially as you know we look at you know investing, in companies is, we seeing a lot of innovation. Around. You. Know sort of GI and, things, like you, know car insurance, and home insurance and. Travel, insurance but. You're not necessarily saying, as much innovation. Yet. On. The life insurance side, obviously. A much more complex, products. Longer, duration product etc, so. What's, your take and what, are we gonna see. Sort of an inflection, point on, the. Life insurance side, and is, this part of your roadmap but accident. Yeah. Right. So as you just mentioned insurance, start you know typically divided into you. Know life and non-life and, the. One characteristic. Which is kind, of bad for tech. Company is the. Long duration. Typically, associate, with life insurance, when, you have longing, long. Duration, and novel of samples. Actually. Makes bit. More difficult, for insurance, for like, a fast tech companies to be able to quickly iterate as, I mentioned earlier one, of the key things that. Technology. Companies, tend to do is to do fast iteration, and you. Know so like so, Motors, is that we're getting into we didn't get into life is because. Yeah, it's it, just takes longer, but. I haven't said that I think there, are other things that's you know in, short tech companies can do to help life insurance, what, is gonna be like, making the claim processing, simpler, more automated faster, to, make the presentation, explanation.
Of Life policies. Easier. I think there's other, areas that we can get into even, including things like blockchain, which can be useful for certain, life, insurance, that are long-duration. So. One. Other thing and especially when you're thinking about business model, and some of the you. Know building, modes and and, and, in sort of the. Future of insurance to some extent right so. You. Seeing models where startups. You know like, yours are either, partnering. In. Partnership, with you know incumbents. You. Know players. And. Some of that often time is not necessarily about you, know design it's, really about access to the, balance sheet right, so essentially, just. For everyone's benefit, you, know if you're gonna sell an insurance product you obviously, incur, liability you, need to book that on your balance sheets and so therefore. That. Is a critical, part of you, know being able to sell, insurance so we see these partnerships. We. Also see that you. Know the insurer tech startups, have a vision, to build full-stack. And. In solution, so, what's. Your take do you think that at some point these insurer tech companies are going to be so big that essentially. The incumbent, players are, just gonna be balance. Sheet providers, or do you see some kind of equilibrium at some point yeah. So I'll, provide my sauce and I really want to hear your thoughts as well after this is very because you have been in the insurance industry, for, so long and. Knows, is inside out. So, for me why again I try to draw an analogy about. The. Internet, right so. Before. The internet the communication, is all just provided, by your. Local telephone companies, and then. Then. You know we started to have once once the internet started, you, see a big application layer, being built on top of the. Fundamental, pipes, of. Communication. And. Then. You have all those you, know companies. Where, it's Facebook. Where it's Google, that, have you, know many ways far. Surpassed, the. Value, of the. The underlying. PI providers. And. People. Like you know many times people you know make. Fun of you. Know. Mobile. Carriers for. Religious. Handover, the, SMS. And the communique, text. Messaging, to, the. Internet, companies that provide which had provided, what's, up. But. I I kind of see that as inevitable, just, because, they're different. Fundamentals. And a different DNA's. How. To do how, to do a good job and, holding balance, and. Doing those financial, management is it it's quite different, how. Do I say. DNA. From. Building. You, know consumer, products. Or something that's so fast and. I think innovation really, will have to happen on the application, layer site and. I would say the same saying for. Insurance. Companies I think we. Will have to divide into sort of two parts right why is the ones that are really doing. All the technical. Innovations. I'm the insurance. Ecosystem. And then there's underlying, sort. Of hope. I hope, I, believe, eventually, be more, invisible, balance. Holder big insurance Giants, that. That's that's what I thought the future might look like I, yeah. It's it's it's it's not gonna be an easy fight in the sense that you. Know I guess the challenge from the incumbent is that if they. See. That and, and then basically they get cut off from access to customers, I think you, know some of the companies. That are going to be able to innovate and transform. Below. Obviously fall in the category where, they won't just be you. Know commodity, provider. Of balance, sheet so I think there. Might be a world where in the some will lose but obviously some will win because they're, able to you. Know to get into into. That space as well quick. One on that topic so the, topic of. Essentially. Providing. A utility. To potentially, over insurance, companies so this this notion of you, know maybe a true. Insurance. Or insurer tech platform as a service is that something that's part of your your, vision. Yeah. We're. Being a technology company and, I think there's pretty. Definitely. A lot, of space where, we can eventually. Try to build you. Know in you, know like you realizing our technology, to provide a sort. Of a platform technology platforms. And eventually, you know making insurance as, like a service. Yeah. That's probably something in. The. Future. You.
2019-05-04