Stephen Brittain, co-founder of Insurtech Gateway, explains how insurance technology, ‘insurtech,’ provides solutions to real-world problems. From aiding farmers in India to deal with the ‘hot cow’ problem to rethinking commercial flood insurance in the US, startups incubated by Insurtech Gateway are crucial players in helping people and businesses better handle risks.
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What’s covered in EP240
- Introduction. (0:00)
- Incubating startups in the insurance industry, reducing early stage risk. (4:53)
- Innovation in insurance industry, including use of data and AI to predict risk and personalize policies. (9:40)
- Using parametric insurance to manage flood risk. (14:28)
- Flood insurance and risk management using technology. (19:36)
- Using technology to mitigate risks in agriculture and the insurance industry. (24:44)
- Disrupting the insurance industry with new technologies and innovations. (31:21)
- De-risking climate innovation and insuring against natural disaster risks. (37:17)
- Using technology to manage natural disaster risks. (40:48)
Takeaways
- Insurtech is leveraging technology to fundamentally change the relationship between insurers and customers, focusing on transparency and proactive risk management.
- Technological advances in the insurance sector are now tackling real-world problems by enhancing predictive models and using data more effectively to mitigate risks.
- InsurTech innovations improve customer service and efficiency and can also address big challenges such as climate change and disaster management.
- Collaboration between tech innovators and traditional insurance companies can potentially redefine industry standards and expectations, leading to more tailored insurance products.
- Regulatory challenges remain significant, but the evolving landscape of insurtech suggests a promising future.
Links relevant to the conversation
Insurtech Gateway website:
https://www.insurtechgateway.com/ (scroll down for the video summary of what they do)
Article about the cost-benefit analysis Gene did for IND Technology:
https://adepteconomics.com.au/early-fault-detection-for-rural-power-lines-can-reduce-bushfire-risk/
FloodFlash:
Transcript: How Good was Adam Smith? 4 Tax Maxims from 250 Years Ago that are Still Fresh – EP239
N.B. This is a lightly edited version of a transcript originally created using the AI application otter.ai. It may not be 100 percent accurate, but should be pretty close. If you’d like to quote from it, please check the quoted segment in the recording.
Stephen Brittain 00:03
The ability for both sides of the equation to understand their actions and their risk implications and the pricing that comes with it and the transparency is, we’re starting to see a very different relationship between the insurer and the customer. Because what we’re, what we’re saying is if you do this, this is what the outcome will be.
Gene Tunny 00:30
Welcome to the economics expored podcast, a frank and fearless exploration of important economic issues. I’m your host gene Tunny. I’m a professional economist and former Australian Treasury official. The aim of this show is to help you better understand the big economic issues affecting all our lives. We do this by considering the theory evidence and by hearing a wide range of views. I’m delighted that you can join me for this episode, please check out the show notes for relevant information. Now on to the show. Hello, and welcome to the show. Today we’re diving into the dynamic world of Insure Tech where their esteemed guests Steven Britton, co founder of InsurTech gateway, Stevens has been at the forefront of insurer Tech’s disruptive journey, and I’m thrilled to have him on the show. insurer tech or insurance technology is revolutionising the traditional insurance industry. It’s harnessing cutting edge technology, big data, analytics and AI to mitigate risks, enhance customer experience, and to introduce new products. In this episode, Stephen will share how these technological advances are not just theory, but they’re solving real world problems we can all relate to. A standout story that we’ll explore involves the hot cow problem that farmers face in India. Here and insurer tech solution can prevent milk spoilage due to unexpected heatwaves. This is a compelling example of how technology is making a tangible difference in traditional sectors, improving lives and livelihoods. Without further ado, let’s dive into the episode. Enjoy. Stephen Britain, welcome to the programme.
Stephen Brittain 02:10
The Many thanks for having me.
Gene Tunny 02:11
Very pleased to be here. Oh, it’s a pleasure. Your company so your co founder of Insure tech gateway, which is in this insure tech, spatial or field. And it’s different from insurance. So one of the things I’ve I’ve seen you say your insurer tech investors, not insurance investors, could could you start off by telling us what is in shorter gateway? And what do you mean by this distinction, please,
Stephen Brittain 02:46
are too many thanks for giving me the chance to clarify that we always need a glossary with all these new words like InsurTech. So we’re interested in risk. And we’re interested in the overlap of risk and all the amazing new technologies that have come to market. So if I was telling you that we were investing in insurance and technologies, the assumption would be that we’re just making insurance a bit slicker and a bit faster, and a bit cooler to millennials or something that it’s a kind of a nap, a natural evolution of insurance to just look a little more modern. But I think that behind the scenes, those of us that really got our teeth into this, I really understood the power of data too. And the power of predictive models, to not look at the risks in any way, in the same way that we used to, which is to say that we we now feel empowered to predict and mitigate and reduce risk in the first place. So that we can, we can inform and educate and, and change the way people behave, we’re going to be far more effective to solve things or sorry, we are, we have an opportunity to be super effective to solve things pre what we would traditionally call an insured event or a catastrophic event. As opposed to being really slick and fast to resolving the claim or the loss after it’s happened. And all those things are true. But I think the things that are particularly excited me is all the stuff that happens before the insurer gets the phone call that we could do today. So I’m particularly I came from outside of insurance with an excitement about the potential of technology and particularly a big data and saw the overlap of risk and data being a game changer in pretty much everywhere I looked. And I understood insurance purely as a business bond. This is just a way to distribute really clever technologies to market in long term annuity models, which looks brilliant on a business case. And there’s got some amazing game changer components to it. We can dig into some of those bits because even that’s just introduce a whole new new glossary of terms for you. As I said, I tried Yeah, simpler. But so we have effectively gone out to the tech market and to people who understand, you know, the clients of insurance and said, What are your problems? Can we help you too? Can we help by incubating the kind of products and services of the future for you? Like, what are you needing? What are the pains you’re going through? Because with a friend with a fresh eyes of technology, and data and risk mitigation, we can we can identify, and we can attract early stage startups who and we can help them then to market?
Gene Tunny 05:29
Okay, okay. There are a few things I want to explore there. First, what do you mean by being an incubator? So? I mean, are you venture capitalists? Is it like, to what extent are you venture capitalists? To what extent are you? Like, how do we distinguish between a venture capital investor and an incubator? Is there any distinction? Can you help me explain that place?
Stephen Brittain 05:55
So, we’re event we’re an early stage venture capital company. So I guess our, our outputs, early investments, and other people that back us, you know, they call themselves LPs, limited partners, if we were a venture capital firm. But the critical thing we understood was, I mean, it’s, it’s really difficult to do early stage investing, because you genuinely have this incredible amount of, you know, market risk, distribution risk and early execution risk, particularly in the regulated market of insurance. So we did, we kind of built the business in reverse. So our definition of an incubator is that we have a regulated sandbox, we have the ability to take an idea, a software, model, a new piece of data. And we can, we can authorise it within the insurance regulation so that we can test either products or distribution channels. And by having that capability ourselves, effectively, we have our own mini Launchpad, we were able to reduce the early, early stage risk considerably. That meant that we didn’t work that matched beautifully with an early stage investment business. And so we would often have visitors saying, could you give us $10 million? Because we’ve got this impossible task? To get this product to market? We could say, why don’t you just take a you know, half a million dollars, because we’ve got the doorway into market. Because we aren’t gateway first. This is a gateway, a regulated channels straight into test stuff. So the journey is just going to be so much shorter, and the lessons of whether we can share from so many things we’ve done. So that was our definition of incubator.
Gene Tunny 07:40
Right? So I guess it’d be good to talk about some of the, the businesses or the startups that you’re incubating. Because I’m interested in this concept of the gateway. And who’s the gateway to? Is it to insurance companies? Is it to reinsurance companies? Because you’ve got with the insurance market, you’ve got retail insurance offerings, don’t you? And then you have the is it wholesale? Or the reinsurance market? Like it’s a quite a complicated market, isn’t it? So where are your like, I’d be interested to explore where your startups fit into that whole. That whole market. We’ve
Stephen Brittain 08:16
done 36, we’ve got 32nd Live businesses. So in truth, we’ve got a bit of everything now. Right, we’ve ended up with, because we’ve been businesses that have approached us from many different parts of client value chains. There’s obviously there are also some businesses that have been working across the insurance value chain itself. How do we do better claims? How do we do better assessments and things, we get those two, but it would generally be in new sectors, like peer to peer rentals, or, you know, the kind of Airbnb networks of properties, looking at ways of maturing that market and working through the various value chain and some of the challenges of a fragmented market with point solutions that are turned into businesses that could affect eventually be regulated as brokerage firms, or as datasets. So, so I’m trying to, can I go back and answer that question in a slightly more structured way for you? Because I think I’m wondering,
Gene Tunny 09:18
oh, it’s not gonna keep keep going. I mean, it’s interesting. I think I understand what you’re saying, but it sounds like you’ve got Yeah, they’re in there doing all lots of different things. And it’s that sounds like it’s a like it’s expand. It’s offering a new retail product or product for you. We’re talking about what Airbnb was it and peer to peer. Yeah.
Stephen Brittain 09:40
And I wanted to ask you, you’re such a good question about what does it get, you know, the gateway bit and then also, we built it initially, thinking that the gateway thesis one was, let’s take people with a really good insight of their own market. Yeah. And they know they need a regulated solution, they need to regulate what they’ve got. So they couldn’t get to market. And we just effectively became an access point into market and for the regulated market. So, Gateway, this is number one is taking non insurance people and ideas and then allowing them to enter the regulated product space.
Gene Tunny 10:17
Right? What so this is home insurances and medical insurance. So
Stephen Brittain 10:24
far insurances and, and flash flood insurance is back in 2016 17. It was basically sort of unusual, quite disruptive models about how we might want to consume insurance. As as the world was becoming more fragmented services were becoming more fragmented. And it’s iterated is involved now, because we’ve just just the nature of what we do, are people trying to solve a wildfire? And some people are trying to put the entire reinsurance market on the blockchain? I mean, it’s just right. It’s everywhere. Yeah, you know, can we put a $3 trillion market onto the blockchain is a lot of project that requires not just the regulatory support, but people with a deep understanding about how the cogs work in the back end or insurance through to the right, or the people are just like, how do we convince the insurer to pay to cover somebody per mile when they might in the UK, by the way, you could have like 100 million pound liability, and the insurer is going to be taking three pence a mile. How do you how do we convince them to try this? Because every commercial bone in their body? So this is, this is ridiculous? How do we get we get that kind of face? Some of the things we have to do are very much about relationship. Building. trust
Gene Tunny 11:39
building. Yeah, gotcha. Okay. So there’s a lot of innovation there. Can I ask about, like, you talked about the data and prediction or data and predictive models, you’re not doing things the same way that they used to be done? You’ve got a lot of these firms have got new models, they’re using the data, there’s AI, or machine learning, or whatever it is, what what do you mean, by the way that things used to be done? And what are some examples of how they’re being done better?
Stephen Brittain 12:09
characterise in the most simplistic terms, the fundamental model of an insurance is historical datasets, like the primacy of the intelligence of an insurance company, is the actuary and the actuarial model. So they can say we can look at population level data of, you know, a million people to work out the likelihood of certain health events happening, for example, fire events, whatever it might be, but it’s done on enormous datasets. And I guess, the switch in mindset, the fundamental switching mindset that, you know, is taking some time because everything’s been based on that scale of empirical evidence is that we’re now shifting to a more dynamic view of risk. Which is, you know, that that may have been the case for the last 50 years, but you know, the increased frequency of weather events, doesn’t doesn’t tell him that the the ability of people to change their risk, because they’d be made aware of it. If I told you that, if you lost five stone, you’d live 10 more years, there’s no doubt that that conversation isn’t included in any insurance policy that you’ve got right now. Whereas if we had more of a dynamic thing, and we were working together, I could, I could really be a behavioural part of your behavioural change. I hope you don’t mind me picking on you, I can barely see through this tiny little camera. So that wasn’t anything personal. But it’s but it’s the idea of this thing being but being a much more dynamic and aware conversation about risk. And I say conversation and see, it’s the ability for both sides of the equation to understand their actions. And their risk implications. And the pricing that comes with it. And the transparency is, you know, we’re starting to see a very different relationship between the insurer and the customer. Because what we’re, what we’re saying is, if you do this, this is what the outcome will be. And, you know, that takes time. And that’s caught deeply embedded culturally in the insurance sector, that is historical data. Whereas we talked with, you know, digital businesses, digital native businesses who say, but we’ve radically changed our business in the last three years. In fact, our premises are three times bigger, and our staff counts doubled what it was last year. Why are we still paying the same? Yeah, I mean, just that stuff, in very practical terms, is to you we can all find examples in our own lives, our lives to change, but our relationship with our insurance just become is this all historical thing. So I think that’s the fundamental shift in in the way we’re thinking now, it’s data and allied engagement around risk and awareness, a risk means it opens up new possibilities for us to take on some of the really difficult risks in the world and see if we can tame them a little bit. it, okay,
Gene Tunny 15:00
and what’s the an example does one come to mind where that’s been done by one of your businesses,
Stephen Brittain 15:06
I’ve got too many examples, but I’ll give you an example that is a big shift in thinking so. So flood is one of the biggest risk classes in the world, certainly when it comes in, in the world. So we we have, most contact most listeners will be aware of in terms of either a domestic level or a local community level. And it’s just becoming a, you know, at a national government responsibility level is becoming unmanageable, it’s a risk to the point where there are entire regions that have been refused flood, because it’s not inherently viable. You have, you’re more likely to have a conversation now with an engineer, if you live in a high risk zone that saying, We can’t insure you you’re on your own, or you’re gonna have to really, you’re gonna have to rethink where we where we build and what we do. So that becomes a bit of an end game for the insurance because no charity, there’s the idea is to try and smooth things and, and work on large numbers so that we can take the risk, but if it’s certainty in large numbers, you just, that’s just there’s no insurance model in the world, that will that will cover it. But the some of the solutions emerging are in our in the there’s a case study called flood flash, and you could find on our website, or go to their website and flash flood flash. And they’ve used a mechanism called a parametric, which is an event, the glossary of terms, it’s event based. So in the event that I’ll give you a very real example, in the, in the event that the water level goes over one metre, we will pay you $1 million damages, full stop, and no more. And we’ll pay you in six hours. That is entirely, you know, that conversation alone that statement. So historically, that statement would have been, yes, your coverage for flood. And yeah, we cover it for everything, and then the flood happens. But the reality of that moment is that it’ll probably take three to six months to have some kind of Loss Adjuster come and check what’s been damaged and where it’s been damaged. And that will be corroborated between a public and a private valuation team. At some point or another, something will be agreed. But the reality of of, you know, when you’re certainly dealing with small businesses, that that period of three to six months is enough time for that business to go bust. So basically, if you’re not up and running within this something like 10 days and 95% of businesses never bounce back. So floods been around since, you know, since the dawn of the dawn of man, and well before that says no, I think there’s a reference for you to know her in a discussion. And here we have a segment a small business segment that have been given some choices. So up to a metre, I could afford to pay that. So what happens to everybody under the metre, I’ve got to take the risk on it. All right, start thinking in smart about risk. Maybe I’ll lift all the cabling up, maybe I’ll take the expensive IT stuff in the server room, which I’ve some reason built on the ground floor. And I’ll put it on the second floor. Maybe I just have to sort of partly take ownership of some of this risk and think a bit smarter about how we live in this space. Because this alternative really works for us because in six days, I don’t know what the money we’d need to keep running. And we would just we’d have continuity, which is the only thing that really matters to us, because nobody wants to go through this this situation. Now, that is a principle can be applied to 1000 categories. Yeah.
Gene Tunny 19:02
And where’s flood flash operating is this in the UK?
Stephen Brittain 19:06
What tends to happen is we we pile a wheel well, we often pile it in the U. K, because we’ve just got some some opportunities to try small new experiments here. But they’re in Florida. So we they piloted in the counties of England when we had lots of floods around the time we were there lots of time to practice. And they’ve they’ve recreated a base in Florida and urinals on you. And they’re also looking at Yeah, I mean, we’ve got a team, our own team in ours. And we’re also talking about doing some planets that too.
Gene Tunny 19:36
Oh, good because I’m in Brisbane and Brisbane is notorious for flooding. We’ve had some major floods. I mean, we’ve had well, I was in Yeah, I was caught up in one in 2011. And then we had one a couple of years ago there was a famous one in 1974 yet where we were used to them and up north. We’ve got cyclones and there’s a big problem with insurance. And then it’s really costly. There are concerns that people won’t get coverage. So that’s why I was really interested in talking to you. And just seeing I mean, you’re just learning about this tech and like, to what extent are these? Can we get around some of these problems? Can we make sure that people can get affordable insurance? Because it’s a Yeah, it’s a really big, big policy issue here.
Stephen Brittain 20:25
But it’s also coming from the beyond. Can we afford it? You know, that I’m really trying to move the conversation to say, can we just be a bit smarter about how we think about risk? And can we embed that into everything? Like, even when the guy comes around to instal the server? And he looks here and says, seriously, you want me to put it on the ground floor? Why don’t you just says, And that conversation should be happening all the time now?
Gene Tunny 20:47
Yeah, absolutely. I agree with you there on this flood flash? I mean, I know that they’re probably they’ve got proprietary technology, of course, but can you give us a flavour of I mean, what are they doing differently? From what traditional? I mean, you mentioned they got this, this special type of insurance, but are they doing more sophisticated modelling? Are they got better data that other insurers all
Stephen Brittain 21:14
over the world? They’re really a tech provider to insurance, okay. They’re a broker in that sense, where they are the intermediary to client and insurer. And I mean, the the neat bit of it, they have a device bolts on the wall. So that one metre conversation I mentioned to you before happens around, where do you want me to stick the device, which is the trigger, that triggers the payment effectively, when it gets wet? The money lands in the bank account very basically. But, and behind that, is some very clever, like 3d, a three dimensional risk map that sort of said, so if I were, if I came to your office now gene and said, I’d be able to pull out a device, a quotation does it and say, right, this is where I’m standing. Yeah, risk this height. This is the price I can give you per month for putting the sensor right here on the basis of this payment of this price. So it is what they call their simply three dimensional pricing model, which is proprietary to them. And the device that is able to you can imagine all the IP and device that you can’t throw money in the water on a million dollars that goes in your bank account, before any of your listeners are thinking about it. They spent the first year trying to work out all the different ways that they could stop that event happening and corroborate it from other sources and things so that they could be that they could be as good as their promise to pay out
Gene Tunny 22:38
instantly. Yeah, okay. And some other businesses I saw on there’s a good video on your website. I’ll put a link in the show notes. You talk about OB, sir, is that which do which is insurance for? Is it for farmers. And then there’s Medusa if, if I remember correctly in health care. Can you tell us a little bit about those two players? The
Stephen Brittain 22:58
first one is easier b I don’t even reduce the reason that we got a name change or something. He
Gene Tunny 23:02
seemed maybe I misheard it or miss Ross. Obviously, I thought it was Medusa. I could have misheard it. But I watched your video. Let it go. Do you mind if I borrow it? That sounds
Stephen Brittain 23:15
good if you turn turn people into stone.
Gene Tunny 23:17
Yeah, actually, I’m not sure if it is a good diet for health care and health insurance company. I’ve probably been hurt. But yeah, the
Stephen Brittain 23:26
arthritic suffers. So the first one, Ibiza is, is particularly I mean, we say farming but I think the business is particularly interesting about it is that it’s a really decentralised smallholder farming. So this is the hardest bit about it isn’t solving the farming problem it was solving how do you how do you help a million farmers who are distributed across you know, the plains of India, Africa, to to be both, you need to be able to mitigate and also benefit from insurance. And typically, these groups don’t have insurance. They don’t have any protection whatsoever. And as we all know, or if both of you know that 70% of the world’s food supply comes from people like this. This is our the big secret of global food is it’s coming from these millions and millions of smallholder farmers who are providing the grains and the milk and this is all assembled through cooperatives and local you know local assembly points, aggregators, until it eventually finds itself into the supply chains of Nestle’s and Heineken beers and all the other local brands that you all know and love into your veggie mind somewhere along the line. Not to push on the stereotype to are there. But they say what’s clever about a visa is that they found firstly, they found a way to get to that kind of last mile. So they’ve been with so that they are having conversations with farmers. And they’re picking up their seed. In fact, they’re helping embed technology into the seed itself to give a greater flood of resistance, flood frost resistance. They are dealing with the local cooperative groups to enable them to come together and work as communities who could be all insured against things in a local life. So if you have a heatwave, and there are 1000, farmers affected by it all can benefit from the same cooperative cover. And it is an it is a wonderful thing about the traditional side of insurances. I kind of the way that it can neutralise groups together, that are fragmented, is that you can assemble communities otherwise, you know, possibly aren’t connected. And it’s meant that a very small tech team called IBC, who are based in Luxembourg, with a couple of people on the ground in India, are able to provide the protection around, they’ve just passed. I think that passing 300,000 separate farms at the moment, from a small group based in Luxembourg, that we’ve been backing, right? And they are, they’ve got some amazing statistics of you don’t understand the scale of this stuff. I’m getting carried away and excited about it. But they when they explained the project, project, hot cow, I think they’ve named it something clever a sense, but we’ve made us all laugh. Yeah, but he does it when you get a heatwave. And the case study was in India, it spoils the milk, they literally just cooks the milking the cow. And waste it’s, it’s just a waste. And we asked what’s the scale of it because you know, we live in the UK and this stuff is feels quite like it could be quite manageable. In a quite robust supply chain we have, they waste as much milk in a day as we consume in a year. So this is like one a heatwave days is enough to like, really damage a local economy. And to disrupt the value chain into a group like Nestle making a yoghurt or something. I mean, as an example, there are many different groups. So they were they’re putting in the, the, they’re able through their direct link now with the farmer to send them an SMS message and you know, warn them look for shade, to you know, do different behaviour and things that come you know, unexpected events that are coming, they can take out, they can give them some buffer, but also they can, they can create a payment that will go through the community, to the farmer and help them so why because when this all goes really wrong, you’ve got a humanitarian crisis. This is a point of economic migrants and all sorts of problems when the weather gets just too untenable for those those farmers. So I think that’s a series of examples are just highly fragmented markets. And the lessons we’ve taken from that have come back and forth and things like micro scooter projects and things that we were looking at where we the other fragmented markets and the technologies and models been deployed there. So it’s been a really good way of us understanding decentralised models.
Gene Tunny 28:02
Okay, we’ll take a short break here for a word from our sponsor.
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Gene Tunny 28:36
Now back to the show. Yeah, I like this. So I think that those stories you’ve told, you’re talking about how well with the Insure tech, there’s elements of mitigation, or it’s helping mitigate risks, and that’s helping reduce the cost of insurance, it’s helping make new insurance products available, it’s getting, it’s getting the person insured, involved in trying to manage the risk and therefore have, you know, lower cost of insurance. So I think that does that that’s that’s sort of what a that’s, is that correct? That’s them on the right track there.
Stephen Brittain 29:14
Just just a more holistic view of an open and transparent view of risk. And that I mean, when you there’s another there’s another aspect to this, which is very much a developing world conversation. But the third challenge, we sort of we, I feel like I get way too involved with some of these businesses as an observer and supporter. Some of the first challenges they’ve they’ve had to encounter is a total lack of trust with the insurance sector in the first place. Because every day we’ll have somebody’s cousin or brother that didn’t get the money they were promised. And it was you know, for some pizza small print or something. So that what they now have is their you know, that these insurtechs that were that was supporting. I’ve got so For a good relationship with the, with the community that is really changing their way their thinking, in fact, we’re trying to lose the word insurance, in many cases is really holding us back. Because they’re getting a text message to say, who should we send the money to? And they’re sending into the wires, because it’s more likely to get to the community in the family then sending into the farm, you know, as in they’re really thinking through Yeah, how to make this as a sustainable community. Because, you know, in the past, it could have been that the money was sent there. But nobody actually said so. And they disappeared with it. And there’s been all sorts of history, stories of black market around payouts of insurance and things so we’re able to solve so many problems with this. Great.
Gene Tunny 30:41
And did you say Are they in? Did you say they’re in the Netherlands? They were they based in Luxembourg? Sorry. Yeah. Excellent. Yeah.
Stephen Brittain 30:50
Not in the scheme of things for you. It’s, it’s a short car drive.
Gene Tunny 30:54
Okay, that’s, that’s fascinating what they’re doing. Right? Can I ask, what does this all mean for the whole global insurance industry? Because, I mean, we’re used to some, you know, like in Australia, we have Suncorp. And then I know that these insurers, they, you know, they get reinsured for the risk that so there’s a big global market, there’s there’s some big players in that. What does all of this mean for that market? What is the scope for disruption?
Stephen Brittain 31:23
Being? That’s a big question. I love the bits that I Yes, most humbly the bits that I am excited about. I’ll start there. But yeah, I think it means from a positive truth disruption perspective, I think it means that we are we right now we’re characterising new trillion dollar asset classes that I think couldn’t have been characterised in cash before. So who knew that milk yield in India was an asset class, who knew that the, the exclusion of flood could turn into an asset class, you know, in the protection of some of those business, a risk base that we can now cover? So I think it’s what we’re turning problems into commercial new opportunities. So for me, it says growth, growth growth, by solving real problems. So I think that for me, the positive disruption is, we can hold our heads up high and say that we can innovate in a way that’s genuinely solves problems and genuinely has a commercial case to it. And will further the progress of innovators and pioneers to solve some of the things that are ahead of us, that insurers should be working hand in glove with pioneers of renewable energy have ways of solving for floods, and all sorts of other catastrophes. And we are absolutely part of the Innovators Toolkit. So that’s my comfort zone speaking to that. So it speaks to purpose. And the next generation of talent entering the insurance market are going to want to hear their businesses are supporting these kinds of ideas, because they’re reading about it from their friends and hearing about it. These kinds of ideas should be should be played at a grander scale. Yeah, the other side of the disruption to it is it’s really quite hard to, for any business industrialised itself 200 years ago, in terms of its scale operation to take. Yeah, so I guess what it really the there’s a there’s a massive amount of legacy in the insurance sector. And the bigger conversation for all of us is trying to work out how to scale some of these businesses using the mitre the insurance sector, as the as the insurance industry rather than just boring their models. Yeah,
Gene Tunny 33:38
yeah, I guess what I’m interested in is whether will there be complete disruption and mean some of these new insurer tech companies will take over and the old sort of insurance giants, they’re, they’re the dinosaurs, they’re going to die off because one of the interesting things you said on the climate confident podcast is if you look at something like Uber, well, it wasn’t in transport or Airbnb, it wasn’t in hotels, these are new businesses that have just completely disrupted the existing markets and taken, you know, taken over a lot of them. And it’s, you know, it’s been, it’s been bad news for a lot of the traditional players. So I’m wondering is insurer tech like this? Is that Is that what we’re gonna see? What I
Stephen Brittain 34:23
mean by take Uber as an example, it’s a really good example. But Uber don’t make cars that has been done and who knew that booking and instant availability of cars would be better it is worth now 50 100 billion pound company, when they when they started, what were they disrupt where they would, they were just disrupting the behaviour of us going out sticking your arm up? As far as I understand, and it was just more about the instant availability of vehicles for us. And so in that sense, it was a positive disruption. It was consumer first they really thought about what consumers wanted. But what they didn’t do As the automobile, they replaced the inconvenience of trying to get hold of a car and you needed a car.
Gene Tunny 35:05
Yeah. And
Stephen Brittain 35:07
obviously, it had an impact on the incumbent taxi firms and other aspects. But now they’re they’re starting to use those same systems themselves. So it was a, it ran ahead of the system. I guess why I went to the efforts to labour there is because that certainly the error I’m looking at, which is at the top of the funnel, when and where the customer need is, I think we’re just finding really good ways of engaging with customers and giving them kind of propositions that they want, whether they be a man in the street or business, in threat of wildfire, or, you know, a government worrying about flood. They’re just groups of people that are able to go in with a new set of tools and really understand risk better. What does that then mean to the I mean, when you go into the insurance sector, what they’re really good at is managing risk, and disinfecting really risk that that is, you know, the root system of insurance. And that doesn’t, you know, that’s amazing, that is just as a work of art machine there. You know, and I don’t think we’re really messing around with it, like, we’re not rebuilding the car for the Uber model, or we’re just having people book it. So I think the positive disruption of in for the insurance sector is that we’re given them a new face a new front end. But until routine to get more out of their amazing machine for dissipating and managing risk. And that’s certainly where I, where I have the most enjoyable conversations. I mean, when you do sit in front of an actuary, and they tell you what they do, and how they, and then the way that risk is transferred to that it’s extraordinary. It’s an extraordinary assistance in involving 10s of 1000s of people and trillions of dollars. It’s a very clever mechanism. And I’m not going to party because I couldn’t, I’m not experts enough to do the justice for your listeners. But also, because generally, when you’re dealing, as we do with clients, future clients, what they’re really talking about his use cases, use case as a risk data use case as a risk. And that’s where we really, that’s where we’re really disrupting them every day is a new use case for what we’ve got.
Gene Tunny 37:16
Yeah, gotcha. Okay. As far as I know that, yeah, I’ve seen some innovation in insurance, or I’ve learned about it with because I’ve talked to actuaries that are making use of geo coded data, like in Australia, we’ve got a geo coded address, database, Gene F, geo coded national address file, and that’s been used to help better get more accurate premium estimates, rather than just base a premium on a certain geographic area, you can get really precise on the risks affecting a particular property. So I think that’s really clever. So yeah, I could see the potential for innovation and insurance and offering a wider range of products and hopefully, cheaper products, and also getting the consumers involved in trying to mitigate some of those risks. And so yeah, it’s, it’s fascinating. I guess, one thing I’d like to, I’d like to ask to, to, you know, because we’re getting close to wrapping up, this will probably be the final, final thing. So because I think, yeah, this has been, there’s been a lot and a lot to think about, and I’m gonna have to explore it. A bit more. You talked about, in your bio, it talks about your seeking founders to de risk climate innovation to put fairness back into tech. What do you mean by de risking climate innovation, and I suppose what I’d be interested in for thinking about Australia and thinking about the challenges we face in the north, in particular with the risk of cyclones, and there’s concerns about climate change, and, you know, elevated temperatures, and all of that is, is there really the prospect of that we will be able to insure against these risks? Or is it or your, or will we have to mitigate it? I mean, we have to mitigate them in some way. But does that mean that, you know, some people actually, there has to be out migration from some of these regions? Is that one of the signals that that will be sent by insurance? I mean, how are you thinking about that? So, yeah, I guess on de risking climate innovation first will be good that those those other thoughts were just, you know, things I’ve been thinking about, but if you’ve got any reactions to them, I’d appreciate them. It’s
Stephen Brittain 39:38
some I’ll take it a bit at a time. Yeah, there’s quite a lot. And I’ll put it this way I would, I need a few hours to think about.
Gene Tunny 39:45
Sorry, I just started riffing on started thinking about de risking climate innovation. But yeah, please go ahead.
Stephen Brittain 39:52
I think it’s, I think, if I break it down, so the question one might be, how do we help climate innovate tools? theory says yes. So I, you know, if I, if we were to meet a group trying to distribute some more wind farms at a local level, they’re going to have some common challenges that if they were solar farms or some other kind of decarbonize, sequestering some neat bit of tech, that’s got a chance to scale and be a proper scale up solution, they’re probably likely, they’re probably going through a bit of a flat period at some point, because their technology is proven they got there, but they just haven’t got enough. They just haven’t got enough data, bind them, this thing working. They’ve got developer risks, they’ve got licencing risks, they’ve got all sorts of unknowns that are coming towards them, like, will this thing work? And how well will it work? What kind of yield? Or will I get from my solar panel as much as what I get from my cows milk in India, I mean, these are the same, the licence the development and the operational risk. And in many cases, this is just there’s just not enough time that’s passed, for anybody with a kind of an insurance historical mindset to look at it and go, we know what to do here. So I think we can help the insurer, the insurer tech group. And I’m also looking to your audience, for people who are in the prediction space forecasters and their predictive model designers and various other groups who, who think, who think in a different mindset to this, which is, we have to, we have to move to a new kind of thinking that says this will probably work within a given tolerance. And we need to find ways of unlocking these innovations by saying, yes, we’ll cover your development risk. And yes, we’ll cover your yield reveal the intangibles of your idea, we will guarantee the outputs of this turbine, this solar farm, why because we’ve done something similar, close enough, because we’re going to take a risk on innovators. Simple as that. So I think that we can help characterise the risk in a way that will help unlock lenders, and it will give bring confidence to ideas in that delicate point in growth. And I really, I, personally, and my close team, really want to be an agent to help at that moment to say, I think we can help you get some of these balance sheet, risk off your lender, get some of the developer risk out, get some product, you know, warranty risk, so that you start to look more like a mature product. And we need to do it quickly. Because the world can’t wait for you to do this over 100 years or so is like 50 years for the motorcar, we’re gonna have to do this over the next three to five years, because you’ve got a scale business to build, and you’ve got some urgency to it. So I think we can work in, in partnership with part, you know, with various pioneers of technologies, to help them to try and run as fast as they are in, in, in proving out their model is robust enough to scale and replicate. So if that’s the one that they’re that particularly has grabbed my attention, I think, you know, they need to be working with a group like us to stop that flat patch happening. And I’m actively seeking those groups who have got a hook in market and are looking for those kinds of tools, people that can pay their data and extrapolate and do things with it, and get the insurance are okay. And the various capital providers to take a bit view and say that we should just try a bit more which stretched the model, we don’t have historical data, but we’ve got enough to go. Right. Okay. So that’s my, and why I’m here. And, you know, that’s where I think the biggest potential is. Can you mind me the second part of the question,
Gene Tunny 43:30
what I’m interested in is just what are the prospects? So for regions where they’re threatened by natural disasters like North Queensland with cyclones or various parts of Australia with catastrophic bushfires when we had a huge I mean, you probably saw it on the news that 2019 bushfires were half of the east coast was on fire. I mean, it’s just apocalyptic. And you know, when the smoke would, would come into the capital cities, like, what’s the like, is insurer tech a way to help us manage those risks and to provide better insurance products? I mean, how do you see because because that’s what’s really concerning people here. Yeah.
Stephen Brittain 44:15
I think I mean, the first answer to your question, the main answer, yes, yes, yes, this is doing it in my view, because you know, it’s just getting more frequent and the losses are getting bigger. So we’re going to get into this in a different way. We can’t just say, big surprise, here comes another one, instead of being a $17 billion payout is a $22 billion payout, you know, whatever it’s going to be, we can’t just save up for that event and just keep paying out for it. That’s just daft. So we need so it needs to be and I of course I also read the stories of ideas of burying the cabling and the various thoughts of ignition points when it comes to the fire or, you know, larger protective walls against Danvers rivers bursty. And we can put all those kinds of defences in which is very, very costly and requires quite a lot of planning and saving up and all the reasons it takes forever to do. And I think in that equation of all the physical things we can do that for us, we could cut down and things as a software thing we can do, there’s a tech thing we can do. And that tech thing is to, is to see the risk, understand it and translate that to the key stakeholders that connect and mitigate and prevent. So whether that means the school kids are aware of the farm or aware of their own responsibility about their first cigarette, they haven’t 15, whatever it is, I’ve been, yeah, I mean, there’s just a general consciousness about my own actions. And what happens through to the way we build and where we build just becomes more common, because it’s the only way we could take on something as biblical and also apocalyptic in scale. If we’re just really designing that kind of resilience, and the only way you can do that is a very clear understanding about on an individual and business level. What can I do? What parts can I play to reduce the risk here? Because I can’t go head to head with it anymore. Yeah,
Gene Tunny 46:10
yeah. Just on that, like, I like what you were, you were saying there just reminded me, I will probably have to get wrap this up soon. Sorry. But I just want to mention, there’s a firm that there’s a firm that, well, you reminded me when we were talking about this in terms of using data and better managing risks. And there’s a company ind technology, which I’ve done some work for, which is they have these devices that they put onto power lines in rural areas, and that will detect whether there’s a fault that electrical fault, and that signals, okay, you got to do some maintenance on this power line on these power lines. So that doesn’t later cause a bushfire because least one of the major fires in the Black Saturday fires in Victoria 2009 was caused by these rural power lines, fault, you know, basically, you know, braking, and although you know, problems with the power line, and then causing a fire. So, that’s some really interesting tech that’s using some interesting, you know, data acquisition and software to analyse it to send that signal. So I think that’s an example of that, too. It’s
Stephen Brittain 47:24
a great example and transfer. And we get a lot of pitches from people who think about devices to put into the, into that risk problem generally, whether it’d be putting ice into a, into a house for a leaky washing machine, or putting something into somebody’s watch to anticipate a stroke or a heart condition. I mean, these, this kind of advanced sensing is very clear, one of the the assumptions that people make is that the insurer will pay for it. But somehow that makes sense, because they’re the ones that will pay out. And that assumption is quite hard to, to explain. But in the case you just described, it’s I’m guessing, and guessing that the insurer put in an exemption and then the power company had to do it, had to instal it as opposed to the insurer paid for it.
Gene Tunny 48:09
Or will this technology would have to be brought in by the the, like the power utilities, they have to instal it on their their network? So yeah, there is an issue about how it’s paid for. And that’s something that, you know, the the company has been thinking about, for sure. So I’ll put a link to the the study that I did for that company on the in the show notes, so people can check it out. Stephen has been terrific. I pick your brain on quite a few issues. And I think there’s a bigger, you know, some really bigger philosophical economic issues about insurance and, and the future of insurance and the future of how we adapt to climate change and all of these catastrophic risks. But we’ll probably have to say that for another conversation. Is there anything else before we wrap up this time?
Stephen Brittain 48:58
He’s up for being so curious Jean, what can I say? Thank you. I appreciate the you know, you put me to test on some very open questions about the space. Very good. Well, yeah, and I wouldn’t Yeah, I would like to add the I mean, I’m really wanted to speak on you know, to you and your to listen your to your listeners, because I’m looking for great people to work with. Whether you are a rising star climate innovator and you’re now recognising either that you need to remove some risk and manage the risks within your current business. You know, we want to work with you as your kind of pilot partner, whether you’re a brand new startup tech modelling forecasting person and thinking about the future and got new solution and need a place to incubate your idea, get in touch, or if you’re an insurer, trying to work out or get into this space, come and invest in some of our funds and you can look at a load of stuff, but just get in touch. We will write you a place for most people with with energy to do something with a with a future mindset. You’re
Gene Tunny 49:59
in luck. And then you’re looking all over the world for opportunities. And Australia.
Stephen Brittain 50:02
We’ve got the team and team in London. And yeah, we operate in. Hana, you sent me a note, is it 98 countries? But yeah, there’s projects going everywhere. But we genuinely we look to where we can start fast and then scale later. So we’re open to all.
Gene Tunny 50:18
Excellent. Okay, Steven Britton from insurer tech gateway. Thanks so much for your time. I really enjoyed the conversation. And I certainly learned a lot about this great new field of insurer tech. So thanks so much. It’s been great.
Stephen Brittain 50:32
It’s been a pleasure, Jean. Many thanks, indeed.
Gene Tunny 50:36
rato thanks for listening to this episode of economics explored. If you have any questions, comments or suggestions, please get in touch. I’d love to hear from you. You can send me an email via contact at economics explore.com Or a voicemail via SpeakPipe. You can find the link in the show notes. If you’ve enjoyed the show, I’d be grateful if you could tell anyone you think would be interested about it. Word of mouth is one of the main ways that people learn about the show. Finally, if your podcasting outlets you then please write a review and leave a rating. Thanks for listening. I hope you can join me again next week.
51:23
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Credits
Thanks to Obsidian Productions for mixing the episode and to the show’s sponsor, Gene’s consultancy business, www.adepteconomics.com.au. Full transcripts are available a few days after the episode is first published at www.economicsexplored.com. Economics Explored is available via Apple Podcasts, Google Podcast, and other podcasting platforms.
