The Asia InsurTech Podcast spoke with Yannick Even, Global Analytics Business Partner at Swiss Re, about the use of data in (re)insurance. Data has the power to transform insurance as we know it and enable insurers to offer better, more personalized products and help close the protection gap. Yannick shares how data allows insurers to cover new risks, such as type II diabetes patients.
Find the full transcript of our conversation with Yannick below:
Michael
Hi, this is Michael Waitze, and welcome back to the Asia InsurTech Podcast. This is the only podcast in Asia focused on insurance that gives entrepreneurs thought leaders and investors a platform to discuss how technology is reshaping the insurance industry in Asia. And in the whole world, frankly. Today I’m joined by Yannick Even, Global Analytics Business Partner at Swiss Re based in Hong Kong. Yannick, it’s great to have you on the show. How are you doing today?
Yannick
Hey, thanks for inviting me. And that’s actually my second participation in the podcast (Find our first conversation with Yannick here). I’m a big fan, listening to all the issues with a lot of interests, so really looking forward for our conversation.
Michael
It’s great to have you back. We’ve been looking forward to having you on an individual episode for a while. So thank you so much for doing that. Let’s just jump right into it. What do you think is the biggest trend in InsurTech in Asia?
Yannick
Well, we see what’s happening, and particularly accelerated with COVID-19, is a dual shift, a technological shift and a behavioral shift, where a lot of the customers are actually starting to consume and expect actually to interact with insurer a very different way then what insurer provide them at the moment, and more and more digital way, where people expect to search for information, even to buy, even to be served much more digitally than what they had in the past. So this behavioral shift will and is already dramatically changing the impact of digital transformation for insurer and a need to partner more and more with InsurTech and big tech giant companies that can help them transform faster and provide more value to the consumer. At the same time, as I said, to support this behavioral shift, there is as well a big technological shift where there is a big improvements in all the sensors around us from our mobile, of course, but also from all the sensors in our home, in our cars, in our smart cities, in the in the airports when we travel, etcetera. So, improving in connecting with this data real time, but also some of these sensors are becoming more and more intelligent to actually be proactive and act based on what’s happening around them. And this creates an explosion of data volume that is now being accessed more and more by insurance either directly through the digital touch point with customer and their data partner or indirectly. And now, all of this explosion of data of data can actually be compute as more and more insurer leverage the computational power of cloud analytics platform in particular, to transform all of this data into meaningful customer and risk insight. So, the role of InsurTech companies is ready to accompany the insurance industry into this transformation into this much more data driven insurance where the way we interact with customer will or is already dramatically changing supported by new expectation from consumer, but also much more data driven insights to continue to further automate the digital transformation of insurance and then move into a much more predictive much more personalized environment where not only you will be able to underwrite a segment of the population, but you can basically be much more dynamic, real time much more personalized to not only assess the risk, but also prevent the risk and help consumer to adapt their behavior to add up less risky behavior especially to the risk they are personally exposed to. And similarly on the claims similarly on the pricing so this works all across the value chain. So I see a lot of potential value that InsurTech and big tech giants can bring value all across the value chain to help ensure and reinsurer for like us to really create a difference at scale.
Michael
Can I ask you a question? So historically data has been used to do what I would call sort of descriptive analytics, you know, basically, go back and look at data, figure out what happened in the past and then just report it so people could understand it, right? But things have changed over the past, let’s say 10 years. And I would say that a few of the things that have changed is, you have massive amounts of data being generated. But also storage for that data is ridiculously cheap. And you also mentioned this idea that like the GPU and CPU power makes the compute so much more powerful now that this move into sort of predictive analytics has started to happen – we can talk about that in the context of insurance companies – but do you see it moving into prescriptive analytics, and maybe this gets into the personalization, where it’s not just saying what we think is going to happen, but prescribing something based on the insights as deep down as just two individuals for personalization? Is that something you see happening as well?
Yannick
Yeah, definitely. So of course, all of this will happen only with the very clear regulatory framework and environment. As you know, insurance is very regulated for good reason. As we, it’s risky, but we also here to to protect people and to be there when bad things happen. So we, we don’t want all of this data and analytics to be only a way for insurer to only target the very healthy customer or good drivers, right. But more a way to, as you say, add people better understand at the personal level, what is the risk, they are more exposed to as their peers, and what are the behaviors that they need to change, to actually reduce the exposure to their personal risk. I give you an example. So in life, and hence, we have actually worked hard at Swiss Re overall in the last couple of years to enrich our life guide model. So the traditional mortality, morbidity models that we’ve built since centuries, and enrich those with data points, that now insurers start to have access to covering what we call the big six. So the diets, the level of exercise that you do, the substances you’re exposed to, the environment you live in, your mental well being, the quality of your sleep, we all know that there is a link with all of this lifestyle behavior with your mortality and morbidity. Now, what we’ve done is actually look into into science backed by evidence, and include all of these potential data points from from these big six into our life guide to actually support insurer to create this much more personalized engagement model that they’re starting to build throughout their wellness program, to actually not only provide prevention advice to the customer, segment by segment, but go much more at the personal level, where you can interact on a day to day with the exercise level, with the quantity of wine you drink, or your sleep quality, and tell look, based on what we know about you and your personal exposure, you really need to make a dramatic impact into this, this and this and we can track and we can give you all the tools to help you change your behavior for good. And that’s really something that a lot of people in the industry are very passionate about, that will totally move the dynamic and the perception of customer to see us as an industry, not as someone who just pay claims and ask question during underwriting to exclude people and ask question during claims to make sure you’re it’s not a fraud and be suspicious that it’s a valid claim or not. I believe that data has this power, that we can actually automate much more all of these processes and ensure as well value that it brings to the to the customer at a personal level, because if they don’t see the value, they will not be willing to share the data. And and this will not happen. Yeah. So that that’s just an example. But this happens across all line of business.
Michael
I want to back up for a second and get a better understanding for people about exactly what Swiss Swiss Re, right? And then we can go into more detail about how artificial intelligence and machine learning and how some of this stuff will be customer driven or company driven as well. So if you can do that, that would be great.
Yannick
Yes, sure. So Swiss Re, maybe it’s it’s known within the insurance industry, but maybe not outside because we are not primary insurer. So the effort we use on our brand is really focused on the insurance industry. So we are a global reinsurer founded in Zurich in 1863. So it’s been a while, 14,000 employees all across the world and 2500 across APAC which add a lot of growth across all line of business in the last few years. We have three main business models. So most people will know us in the first business model reinsurance company, where we support the primary insurer, especially around helping them to better manage their risk portfolio at a time of underwriting as well and claims. So providing our risk knowledge to our clients to basically add them support their risk exposure, as well as create the new product that the insurer needs in various markets. Then the second business model is called Swiss Re corporate solution. Where for commercial insurance, we have a bit more direct approach where we have our own product, our own brokers, selling protection for companies of mid size and large corporate. And then the third business model, it’s basically looking into digital and direct insurance, call iptiQ by SwissRe, where we provide end-to-end digital insurance underwriting capabilities. So bringing on our risk knowledge into an end-to-end digital platform that can be then deployed very quickly by direct insurer, or any of the digital partners that want to sell insurance online. And we support these three business model with a lot of function like, micro function called group data services. So deploying at the group level, our data strategy and including advanced analytic capabilities. And we have also another cool function called Swiss Re Institute, that is our very well known research and thought leadership unit that is providing a vision of how insurances is gradually moving into this data driven industry.
Michael
Right. So one of the things you said earlier was that the technology is going to drive massive change, whether it’s behavioral change or technological change in the insurance industry. I don’t think that’s going away. Right. But do you think that this is being driven from a top down perspective, meaning, Swiss Re is driving that up? I mean, driving it down to their customers or customers expectations driving this change? How do you think that works?
Yannick
Yeah I think you’re spot on. There’s three main trends that I see. And the first one is customer expectation is driving the change. And this is very clear that in the last five years, a lot of insurer company have worked really hard to transform themselves, to be less silo oriented, less process oriented, much more data driven, much more digital and provides this digital touch point to the customer. So the customer now basically able to select the channel, they want to interact with an insurer. And that’s very important. And and that’s clear, that’s basically in response that customer expectation is changing. And the way customer buy things with the e-retailer on their mobile, the way customer manage their finance with their banking app, and their electronic wallet, the way customers manage their mobility with all the offers now online, on your mobile, I don’t have a car, I use apps to basically move to a point A to point B within the city. This has drastically changed. And all is done in a few seconds on my mobile. I, as a customer, I expect to have the exact same services from an insurer. If my insurer want to be my wellness planner to help me to stay healthy longer. I expect these services to be done online, I don’t want to call anyone, I don’t want to speak to an agent about my health. I can speak maybe to a personal coach that is paid by my insurer, this could happen but through my mobile, and I want this personal coach to make sense of all the data, health data that I have, on my mobile, to to tell me what are the risks I’m exposed to? Am I well protected? Where are the gaps? Can I fill these gaps easily? And to come back to the big six and in the health context. What do I need to change in my behavior? For my personal risk to, for me to be less exposed to my personal risk? And in the in the events I have an exposure and we can take the example of COVID-19, I expect my insurer to be very fast if if let’s say one day – touch wood this will not happen – but I’m positive, I expect my insurer to tell me exactly what I need to do and pay for the associated services combined with what the government provide to me. So I think we still have a long way to go to reply to all this customer expectation. However, a lot of insurer working really hard in making this happen. And especially in APAC, we’ve seen a lot of good progress, in China, across APAC on creating this experience that the customer really expect from from an insurance.
Michael
Sorry to interrupt, two things. Do you think that consumers are looking at other insurance companies, when they compare the services and sort of the digitalization of those services that they’re getting from their insurance companies? Or do you think they’re looking at other platform companies, like you said, like looking at the ride hailing companies or looking at the e-commerce companies, in other words, I’m moving outside the realm and saying, I want it to be as good as this. So it’s not good enough to just be the best insurer. They have to be the best app? Does that make sense?
Yannick
Definitely. And that’s, I would say, one of the risks, even in our highly regulated world, that’s one of the risk overall. If we are not moving fast enough, as an industry, there might be some new entrants that have access to customer in digital ecosystem that know how to quickly create these embedded services within a digital ecosystem that can scale and can reply to this customer expectation. And that might happen actually. We did a survey a few months ago, that shows that across APAC, 54% of the customer are more likely to buy insurance online. But also that 76% of the customer actually prefer digital channels such as e-wallets, bank website, ecommerce platform, to basically purchase protection in the future. So that’s a big number. And that’s reflect, I guess, where the industry is today, in providing the solution customer expects. And there is a risk that there might be disruption there, if we are not, as an industry acting fast enough, for sure.
Michael
So that’s a really good point, I was gonna back up and ask you this, too, if customer expectations are driving this change? And we’ll get to the AI part of it in a second. How do you get this feedback from customers? In other words, you can’t just build the app, put it out there and ask for feedback. You mentioned surveys, are those surveys digital? Like, what is the scope of the feedback that you get? And how do you then take that and then build that into the services that you’re offering?
Yannick
Yeah, thanks for the question. Actually, as insurer have worked hard in the last five years to digitalize the entire value chain and processes, they have now access to much more touchpoints, digitally, and also, offline, with their customers throughout these processes. And they can collect throughout all of these touch points, where things goes wrong. So that’s a first way of course, throughout all these digital touchpoints that insurer now are working across all the silos where traditionally they were looking only to data time of underwriting or to data time of claim or looking to the portfolio only when they want to cross sell. So this is long, long gone. Now insurers are able to look to the customer in a single view. And better understand what are the trigger points? What are the changes in in, in your life, that could actually result into a much more meaningful discussion between the distribution channel and the customer. The next step, and it’s starting to happen, is to enrich all of this insurance data across silos with alternative data to have a much better exhaustive view of what’s the customer needs and what’s the risk about. And insurance data is already good to look at it in an exhaustive way. But it’s not enough yet. As you know, we don’t have enough touch point to really understand in a very granular what what is the customer new customer needs, what could be the new sales trigger, how to fill this huge prediction gap that we have today. And that’s inevitable that insurer needs to work very closely with their data partners. So e-wallet company, a lot of digital system but also find ways to to provide value to customers so they are willing to share a bit more, all the data on the mobile or the sensor data we spoke about. Industrial IoT in a commercialized context. And as they start to have access to this much bigger data pool, they will be able to basically link it back to the to the insurance data to enrich the AI model and data driven model that they’ve already built, like need analysis, propensity to buy, risk segmentation, propensity to claim, to lapse, renew, but also the other much more data driven approach to create the new product to create services that are embedded into digital ecosystem. And that’s basically where I see AI starting to bring a lot of value in creating this enabled solution across the value chain of insurance.
Michael
Can you talk a little bit about maybe specifically about how artificial intelligence and machine learning will impact these particular parts of the value chain? Like you said, maybe like claims or marketing or underwriting or even client engagement? Like if you could give a couple of examples? That would be super.
Yannick
Yes, sure. So maybe, let me take one minute to explain what AI is because you can ask any data scientist and the definition might slightly be different. So, for me AI we can define as a set of computerised tool designed to achieve objectives that usually required human intelligence. So, AI is not there to replace human, AI is here to augment human And what you need for AI to work you need data, and we just spoke about it, how insurer will have access to more data. But we need also scenario, you need to put it in the context of a business challenge or a customer needs. So, what are the scenarios here that you believe data can can bring value? The second thing you need is data scientist or actuarial that understand data science, that understand mathematics, statistics, algorithm to basically then apply this algorithm to this data. And then computing power that we already covered. So then with AI, what you can do, you can transform data, structured and unstructured data, with powerful algorithm, machine learning is one of them that a lot of data scientists working on in particular supervised learning. But they are other parts of machine learning that could be applied. So transform data with powerful algorithm to create business value. And business value come, as for everything, either managing rules by creating this more personalized customer understanding that will enable you to create this this better services that will help you to grow your business. But there is also a lot of application in AI to managing cost. So further add value to the digital transformation and process optimization and automation, that is already happening with a with a more data driven approach to automation. And the third one are to create business value for insurer is to manage risk, and have a much better understanding much granular and data driven understanding of the risk you have in your portfolio, but also the new risks that you want to bring in. And basically, this can be applied all across the value chain. So looking into maybe more distribution and marketing. So with more data and AI driven approach, you can automate and have a much more contextual distribution to micro segments. And here, I really encourage people to look to what some of the Chinese insurer doing especially in a digital world, in more or less arriving in a in a personal level, be able to use this data online to to know exactly about your customer. And you arrive in such micro segment that it could look more or less very personalized for either customer and then have a better sense of the customer needs. Again with more data, better indentify the sale triggers, automate the sales compliance so that all your sales are automatically compliant with more tech and data. Then moving on the value chain that leveraging data to create much more precise, personalized, predictive underwriting solution and we have actually good experience across APAC to help the primary insurer to create predictive underwriting models for life and health, but also data driven underwriting models for P&C, where where we will use the data the insurer have access to, to identified the segment of customer that are less risky for a particular risk pool, to provide them guaranteed offer. So no question asked, we know that you we know your risk and through the data you’ve already shared with us. And you get a non-loaded price for a particular product that we believe you are less risky than your peers. Or less question ask. So just a few questions just to cover ourselves on things that we don’t know. So this is something we’ve already launched across APAC. Then moving on the value chain is what we covered a bit earlier, so create this more dynamic risk engineering processing. So dynamic pricing, dynamic underwriting where we don’t underwrite people once or all their life, we basically engage in a day to day with people at a personal level for them to better understand the risk they’re exposed to better cover them. So maybe take out a bit of the money where they’re extra cover and put it in, in areas where where they’re not covered where they’re actually more exposed than their peers. This could be something interesting to look at with more data and dynamic pricing, dynamic underwriting schemes where if you share more data with us, we can provide more personalized value. And we can more or less guaranteed that you will be less exposed to risk as you change your behavior. And if you continuously change your behavior, we can give you access to more services and we can cover you better. And that’s the idea with dynamic pricing and underwriting can can play a major role and major shifts in the insurance industry.
Michael
Just a quick question. How do insurance companies, particularly in APAC, right, where penetration of insurance is still low, convince their potential customers to give them enough data to trust them enough to give them enough data so that they can then start providing all of these better services including dynamic pricing, dynamic underwriting?
Yannick
It’s the key question. You will not get more data, if customer don’t see the value. Maybe I give you an example of something we did with an insurer in Southeast Asia. We did a lot of work in better understanding diabetes, which is a big ticking bomb, a big problem in APAC. It’s not well covered, and we all know this is coming and and the society at large is not covering enough. So we actually created a product together with with an insurer and we partner with a hospital, we partner with real time glucometer company, we partner with DNA company as well, a well known one, and bring all of this together into an app where we could we could tell type two diabetes. So people already with the condition, you know what, we actually want to make a difference to help you to bring you back into a healthy path and make a difference in your life. And we provide you personalized services with DNA to tell you what kind of foods you should avoid, what kind of medicine category you should avoid based on your DNA. And on contrary what kind of food you should eat more. With the real time glucometer we give you all the tools to actually manage your condition better. So and see the impact of your behavioral change, real time, leveraging all this data but also if something wrong happened in terms of emergency, there is also full mechanism around it. Then with the doctor and the hospital, that also part of the of this partnership proposition. They basically gets tools to monitor the patient outside of the hospital. like type two diabetes will not go more than a quarter or sometimes half a years, sometimes even yearly to the hospital. So there is a lot of information there that the doctor and the hospital don’t get. And suddenly they can again create a much more personalized advice to the consumer if suddenly they adopt better behavior, they do more exercise, they change dramatically their diet. Of course the medication should change accordingly. So this is all the idea behind. And as the people can actually see the value of us being fully part of this ecosystem, willing to help them, bring them back into a healthy path, then basically, they understand why it is important for a hospital for a doctor, for an insurer to have access to this data. And of course, we will limit, we will take only the data that we need for pricing and for underwriting, we are not looking to, we are not sharing all the data to to the insurer. Similarly, all the data needed by the hospital, each partner in the ecosystem have access only to the data they need. And this was possible only because we use the regulatory sandbox. In this particular jurisdiction to actually test that initially, to show the regulator, that first customer really understand this value proposition and buy this product. And then also that with having access to more data, we can actually create something beneficial, overall for the society and for, especially for the people at need. And that’s back to what I was saying before, there is an ethical rule that we need to play. And that regulator will be looking at, in our use of data and AI to create value for customer rather than using this to exclude people and to focus on the healthy people. And that’s the key.
Michael
I’ve got another question for you about data and about data ownership. So you make a good point about the fact that people will give data if they can be convinced that that data has value to them in return, right. And if they give it to you, they get this dynamic pricing, they get better service, they get healthier, everything gets better for them. But I wonder what happens in a world where – but the insurance companies, get that data for free? Right? They don’t pay anything for it. They just ask for it, and they get it. – But what happens in a world where you have this sort of idea of self sovereign data, in other words, I own all my data, and I’m happy to share it with you. If you pay it for me, if you pay me for it. Well, how does that change the business model, particularly around the implementations of artificial intelligence and machine learning? And how does it change the bottom line for things that are related to using data in the insurance space? If in the end, you have to pay individuals or even companies for their data? Does that make sense?
Yannick
Yeah, I see your question. I would say, at the at the moment, it’s not very different. First, no one got data for free, you need to build all of this ecosystem, you need to build the services you need to build the backend to collect this data in the first place. And then, and then as we said, you need to convince the customer, what’s the value for them? Yeah. So that’s actually a lot of money spent into creating this. The minute people understand that the data is, is their data, and they will value this data. It doesn’t change the fact that insurer needs to spend time and effort to explain to the customer, what can, how can they transform this data into valuable insight for them. And even if if the, at the end of the day, the customer has to be the one that will own this data. And they will be if the insurer is able to explain how they try and transform this data into valuable insight for the customer. The customer will still share this, I’m convinced. And maybe on another area as well is, of course, insurances is not the only line of business going through digitalization, everything is going through the same transformation around us. And we spoke about health, but hospitals are going through the same, the same journey, and we having more and more jurisdiction across APAC that start to have kind of universal electronic health record, where all your health data are basically recorded on the government cloud. And we actually did an experiment in in Singapore, again, with the regulator, to show them that by having access with the consent of the customer to the electronic health record, we can create something very meaningful for them. And here we were looking into a lot of new risk pools. So one particular that is not well covered is gestational diabetes. So when you get diabetes when you are pregnant, there are a lot of extra costs. That could be complication. The industry and the society is not covering very well. So we actually launch a product that, with the customer consent of the pregnant lady, we use their electronic health record data to cover them and provide them again services around that, to support them during their pregnancy, and to pay automatically the claim. So they don’t have to claim, they got the money automatically on the electronic wallet or bank account when they get diagnosed, or when they have complication at birth. So these are the type of products that were very well received by the customer as well as regulators because they see the value. And we didn’t really have perception from pregnant lady that “I don’t want to share this data with you”. Anyway, this data is on the cloud, we are just creating extra value with this data with your consent. And here we use blockchain to actually encrypt everything. So actually, the insurer, the reinsurer, we don’t even have, we don’t even know with the customer, at the end of the day, all is totally encrypted. Using distributed ledger technology. That’s something that that we can do now at scale. Yeah, it’s just an example. Yeah, this is where I believe the industry will move pretty quickly.
Michael
And before I get to my last question for you, is that a parametric product you’re just talking about? Where they just get a payout? They don’t make a claim?
Yannick
Yeah, so we could call it parametric health. So basically, the claims is automated, and the event is data driven. And underwriting is totally data driven. So five data points and underwriting is done. The price is fixed. So there are a lot of different model when you look to parametric solution. But the idea is that now that potentially, when we are embedded into digital ecosystem, we have access to much more data that we don’t really need to ask question anymore. We could use this data to underwrite, to price and to automate the claim.
Michael
So the last thing I want to talk about is partnerships. I believe that nobody, even big companies succeed alone. Do you want to talk about some of your global partnerships and the philosophy around why do you think they’re necessary and powerful?
Yannick
Yeah, definitely. So it’s actually part of our global business strategy. Partnership is at the core. We do believe that in a world that is becoming more and more digitalized, and, and everyone can see that the frontier of different line of business are blurring. Now the idea and very much to your point is that for us to actually create this data driven protection services and to embed this into this future digital ecosystem that will very soon represent a large portion of the revenues globally, we cannot do this just with insurer, reinsurer and distributor alone, the traditional ecosystem around insurer. We really need to expose ourselves to a lot of other partners. And we have been working in in the last five years to actually create this partnership ecosystem around Swiss Re working with digital tech giants like Microsoft, like Google, like Palantir and others, working with digital platforms, like Waterdrop or OneConnect. These are the names that are in public domain, so I can speak about but we have many more. Working directly with OEMs as we all know, that that more and more the risk of you driving a car will not be linked to much like it is today to your driving pattern, but it will be linked more to all the electronics and all the AI within a car. So, you will have less accident and the accident will be less I will say less violence with all these electronics embedded in your car, and these are already data driven approach that we took to to verify and validate this. So we are working very closely with some OEMs like BMW, Toyota and others. But also digital banks, WeBank and others. So I mean, we have a lot of partners across all line of business and the idea, three things we doing with them. One is, let’s build together innovative data driven insurance solution that could be tailored and distributed through your ecosystem. So we use them as a distribution partners for the insurer to build a data driven solution with their data that basically connect with their ecosystem that they can distribute. Second thing is we bolster our own Swiss Re solution with all this tech offering and data analytic, which is what my team bring, innovative risk model. So basically working with these companies on creating the data driven risk model of tomorrow. And basically selling this to our client, the primary insurer. And then the third one is looking much broader into risk management topic, global supply chain, society resilience, risk prediction and prevention, how can we bridge this huge prediction gap all across the world and look to this broader risk management with a data driven research and thought leadership orientation, that we can then bring back into either our client solution or either into this tailored solution for the ecosystem I was speaking about in the close future. So that’s the sweet topic on which we we focus on on our partnership across the group. And of course, we will have partners that we work globally, but also some more regional and some more local partners as well where we welcome these three goals.
Michael
I understand. Yannick, that’s a great way to end. This has been hopefully for you as good as it’s been for me a great conversation.Global analytics business partner at Swiss Re based in Hong Kong. Thank you so much, again, for doing this today.
Yannick
Thank you, thank you very much, again, for inviting and a lot of this is is on our website. So I really encourage everyone interesting to follow. Especially Swiss Re Research Institute website and and seek my report. We do a lot of customer survey around these topics. So connect with me on LinkedIn and all this is free. So again, I really encourage you to follow us and looking forward to to speak with all of you through a set podcast, maybe one day to show you a bit more. Some of the things we achieved already.
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