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Webinar ID: 720-553-236
Please join us for a 75 minute TDI Academy webinar in partnership with HKFI as we explore how insurers are implementing artificial intelligence and machine learning. Our webinar will cover viewpoints from Artificial intelligence & Machine Learning – Case studies & implementation approaches.
By participating live you can help to shape the panel questions and also participate in our live polls. Registered participants who are unable to attend will be emailed a link to the recording of the webinar.
The broad agenda for the webinar is
- AI 101 – a quick recap
- Use cases / case studies – examining and discussing 3 case studies of use of AI in insurance
- Implementation challenges
- Updates from HKFI and TDI
Note* – This transcript is Machine generated and not 100% exact. It is designed to help in search.
Timestamp: 0 sec to 59 sec
Okay, so good afternoon everybody. I’m Simon Phipps from the digital insurer based in Hong Kong and it’s our pleasure to welcome you to today’s webinar on artificial intelligence and machine learning. We will be taking a look at case studies and implementation approaches in the real world. And this webinar today is being brought to you in unprecedented times as I’m sure we will acutely aware and it’s our particular pleasure. I guess to be bringing it to both From the TDI Academy which will talk a little bit more about later and the Hong Kong Federation of insurers, and we’ll be talking to them very shortly. So thank you for your time.
Timestamp: 59 sec to 118 sec
Welcome and this is just a couple of really positioning comments from me before we get into the meat of the conversation. So let’s just take a quick look please at the next slide and and our panel today and first and foremost will be hearing very shortly from Selina Lau recently appointed chief executive of the Hong Kong Federation of insurers here in Hong Kong, which we’re really grateful for The time in joining us, Nora Li from AIA Innovation actuary and Celine Chiu from the HKIF as well as well as Andrew Darts. Andrew has been a sort of tech specialist in the insurance sector for many years ran the Strategic sort of development for CSC DXE in Asia. He’s currently in Australia and Beyond Myself, of course my partner in crime and original founder of the digital insurer Hugh Terry who’s based over in Singapore.
Timestamp: 118 sec to 177 sec
Or so we’ve got a real wealth of experience today and the ground we’re going to cover next slide, please just a pull up the kind of agenda in the framework of the discussion is in front of you now, and we’re going to start by just hearing a little bit from Selena and then we’re going to go quickly and sort of a bit of a 101 I guess on what AI is and where we are in the Journey of AI beyond that. We’re then going to get into some hopefully interesting case studies on how AI is being used in different parts of our industry. So we’re going to be looking at how it’s being applied to the management of chronic diseases and a particular case study there with wealthy, Andrew will be talking to us through that will then be looking at how AI is being deployed in claims and customer service and the lemonade example over in the US and then Nora will be helping us understand how AI is being deployed in life underwriting in AIA will then move into a slightly broader discussions around
Timestamp: 177 sec to 236 sec
I guess implementation learning so far and potential challenges for this technology. And then we’re going to get into a bit of an update from HKIF on some of the things they’re doing Beyond Salinas opening remarks and then then get into a broader discussion across the panel before few quick updates from TDI. This webinar is scheduled for 75 minutes. It’s quite an ambitious agenda and we’ve got some really interesting people on the panel as always so I can already sense that we might need about five minutes of Flex on this one at the end. So just to manage expectations at your end. Please try and stay with us until we round it out. But we will be looking to to finish pretty much on time respecting everybody’s schedules. So without further Ado, let me just start them by moving into a quick update and introduction to Selena, Selena for those who don’t know you is at a personal level fantastic lady. We’ve known each other for a while in Hong Kong
Timestamp: 236 sec to 295 sec
and recently appointed as the new CEO of Hong Kong Federation of insurers Selena. Congratulations for that appointment and I have to say knowing you as I do a little bit over the years one thing I would observe to everybody about Selena is she’s made a real effort. I think over the years to attend things in her personal time that has to do with digital and she probably didn’t need to so from our personal point of view in the digital insurer and I think on behalf of the industry is great to see someone in this senior position now and in a role that is able to sort of influence the industry in Hong Kong this got a genuine and authentic passion and interest in digital which is what the industry needs. So Selena, thank you again for you know, how kindly helping support this webinar. Congratulations on the appointment and I guess just in terms of framing a few words from you, you know, how does it feel you must be really excited? Probably a little bit anxious about the new role. But yeah.
Timestamp: 295 sec to 354 sec
Tell us a little bit about it what’s going to change and what’s going to stay the same kind of what are your initial thoughts please on where you going to take the hdfI
Thank you so much and thanks a lot for your kind words and it’s been a very exciting time and is a very trying time as well with this covid 19 lingering in the around the world, but I think as you mentioned that I have a passion and I’m really passionate about Tech and I have been doing a lot of very a lot of learning about technology and how it can apply it in our industry and I’m so pleased that we at the federation did apply some of the very state-of-the-art Technologies in our work which can help the industry as well as the community of Hong Kong as a whole. So this is what we want to do in the Federation and what also teaming up with them TDI is one of the things that we want to do for industry as well because some of the excited if they may be very good at business, but they are not
Timestamp: 354 sec to 413 sec
very familiar with tech and we want to introduce more technology and more know how to them and so that we can all work in the same environment and build an ecosystem for future and just in a minute. We will introduce more of that the tech thing we have launched and the solutions we have launched but as the CEO of the Federation, I’m trying to push for more technology enabled solutions for industry for the good of Hong Kong. So if I may I will go to my slide, a very short one, but I’m to do some background information to give you some background information about the Federation as because some of you may not know me or may not know the Federation it since it’s a very Global event. So I want to do more of the introduction if you allow me. So, can we go to the next slide?
Yeah, the Hong Kong Federation was established in 1988. We have more than 30 years of history in Hong Kong and we represent 137 insurers in Hong Kong
Timestamp: 413 sec to 472 sec
and all together will underwrite more than 90 percent of the gross premiums in the Hong Kong market next slide, please.
And I’m not going to bore you with all these missions. We had we have before the Federation. These are the key tasks. We find ourselves to be working on but I would like to focus on three particular missions that we want to that is relating to today’s webinar. So can we move to the next slide?
We think that raising public awareness of the value and benefits of insurance is very very important. We are an industry be undervalued and understood misunderstood for so many years. Lots of people only think about insurance as a sales business. They only want to get premium. They want to want to pay big payouts. So this is a huge misunderstanding. So what we want to do is
Timestamp: 472 sec to 531 sec
To educate the public to let them know more about ourselves to give them more clarity. One of the most recent scenarios. One of the most recent example is the insurance dashboard on Covid 19. We just launched a couple of weeks ago because of the Covid 19, there are lots of miss confusion among the market even some of the questions petitioners are not aware whether I will be compensated under travel insurance policy. So we launched this very quick one with all the information in One Stop Shop, so that people will know all about the Covid 19 related insurance coverage in one in one in one place. I think that providing such clarity can help change the Public’s perception on insurance and can also help us to raise our professionalism because we are providing more clarity more assurance to our public and can we go to the next slide.
Timestamp: 531 sec to 590 sec
And the other very important element of our work is to promote the proper protection of customers and Foster Public trust and confidence in our industry. So it’s not only about public education and their awareness is also protecting their interest at the same time. We are on the other hand. We’re protecting our interests as well to do this. We don’t we don’t usually we do a lot of custom applications through guidelines or regulations or consumer education, but we also use Technology to do so. So in 2018, We launched a Motor Insurance DLT based authentication system. We called it MIDAS – to help authenticate automotive insurance policies, which are written in Hong Kong. So back in 2016, we found more than a thousand of bogus insurance cover note and multi policy is being sold by the social media. It’s not good for business and it’s not good for reputation either.
Timestamp: 590 sec to 649 sec
So we launched this watching application to authenticate your insurance policies issued by our insurers. This is the first-ever blockchain application being launched industry-wide for the whole industry and for the whole Community. We’re very proud of it and one Beauty about this is that is scalable. We can apply it to other lines of business as well. So this is a very starting point that we use technology to enhance the customer protection and to enhance the image of the Industry. If we can move on to the next slide.
So this is the other Tech enabled solution. We launched about the same time it just cause they’re in insurance fraud prevention claims database and we are using deep learning and AI on this is database. This is nothing new around the globe. But in Hong Kong with very very stringent Privacy Law with very strong consumerism, which is a bit hard to watch.
Timestamp: 649 sec to 708 sec
Something catches and countering the fourth may be seen as infringing the interests of the policyholders, but we truly believe that if we can plot the loophole or fraud gardening claims, the premium can be brought down and it is for the win win for everyone. So we still pushing ahead we have already launched the motor line of business and we are launching more lines of business in the months to come the next one will be on travel as well as medical insurance. So my colleagues Celine will come up we’ll cover more about this solution at the end of this presentation.
So can we go to the next Slide? Okay, and one more thing that we want to add educator and we toss ourselves to do is to increase the to enhance the professional training across the industry. So and we’re going we do training. Maybe you you guys are very familiar with e-learning because we’re doing
Timestamp: 708 sec to 767 sec
Still meetings virtual virtual learning a virtual webinar, but in Hong Kong CPD learning is not allowed to be done. Electronically. I’m not until fairly recently. So we are using technology to enables our members to have more training more up-to-date training more success in training through electronic means and as you can see my highlighted in the green box on the right hand bottom Insur-Tech is one of the very important thing that we want to get across to our to our members, that’s why we team up with the digital insurer and to start off our first; through a topic on AI 101. This is very important because we want to go go back to the basic and learn about Steam from the experts and get some ideas about what AI is and what it can do for industry and we will hear from the experts in some experience sharing. So if this is what we want to do right Simon,
Timestamp: 767 sec to 826 sec
Did you get by and the TDI at the same time? We launched this first very first webinar on AI and deep learning.
Salina thank you very much and indeed. I mean it was actually aged-care fire that suggested this topic. So if people don’t enjoy it will blame them but I suspect everybody will and I couldn’t agree more that it is a very important subject to look into I think Serena, you’ve obviously reference that I mentioned in my opening remarks we are in unprecedented times and this more than any time there’s a time when the the importance of insurance and the importance of our industry really comes to the fore and therefore increasing actually and amplifying the importance of addressing the issues we’ve got in the industry. So Selena Your Enthusiasm personally as well as the team’s really comes through I think in the work you’re doing great to see some Progressive developments and delighted to be involved. So, so thanks. Thanks again. And I know that you might not be able to stay right until the end because you’ve got another prearranged commitments.
Timestamp: 826 sec to 885 sec
So Brooke if you can move on to the next slide, please what we’re going to do now is start moving into some broader discussion and for all people who are on the call, if you’re not familiar with zoom then on the bottom of your screen, you’ll see there’s a Q&A button. You can press that and submit a question at any time and our panelists will be looking out to try and answer those as we go through the webinar the same if you wanted to make a comment in chat, but if you’ve got questions particularly Selena while she’s around please put them into her and she’ll be watching that and trying to answer them as we go through I will pick some questions from there. If I think they’re appropriate for broader discussion later, but we’ll try and sort of answer as many as we can on the fly as we go just the last thing to say, if you are having any connection problems, it’s almost always these days a local issue zooms a pretty stable platform. So, please sort of check your local connections and if necessary come off and come back in again, but we’ve got a big number of people on this.
Timestamp: 885 sec to 944 sec
Webinar, so without further Ado we’re going to kind of move into the meat of it, Selena thanks again for your time and support so going to move over to you now to sort of kick us off really with a 101 on AI what it is and where we are in the journey Hugh over to you.
Thanks Simon. And thanks Celina as well as pleasure to be part and with HKFI I guess and I’m hoping we’ve got lots of people from Hong Kong but also got a lot of people from around the world. So if you’re feeling like you want to put a chat entry, let us know where you’re from. You can get a random sample and see where people actually dialing in from I’m going to keep this really short just a couple of slides really on what AI is I think we all know what AI is really we know it’s a critical part and integrated into our daily lives so that we go straight in and go to the next slide.
Timestamp: 944 sec to 1003 sec
now you can look up in Wikipedia. You’ll find the definition there, but just really my short form one sentence answers Simon and you know, the question what is artificial intelligence? Artificial intelligence is a computer program that allows machines to replicate human behavior.
If we go to the next slide, obviously, there’s a lot of components around what makes an AI and I guess you know where many of us would probably be of the generation that was sort of brought up on RoboCop.
In Our Minds Eye artificial intelligence is embodied in this mobile robots and I suppose and super intelligent super agile. Maybe that’s the way we’re going but clearly there’s lots of sub components that make up artificial intelligence and it’s developed very rapidly over the last few years and you’ll see today some interesting case studies. A lot of those case studies are focusing on this area.
Timestamp: 1003 sec to 1062 sec
of machine learning which is using algorithms to teach the computer how to categorize things how to recognize patterns how to respond in text and then coupled with natural and processes also the invoice as well. So today what we’re not doing and I certainly wouldn’t be qualified to talk about the core technology itself. We’re going to focus on the business application and if we go to the next slide
We’re using AI in our everyday lives whether it’s Facebook image recognition Google in terms of prompting responses on Gmail or in terms of the search that we use everyday Siri on Apple Alexa Google photos. You chose YouTube recommendations AI is all around and helping us to be more productive have more interesting lives have more access on to information and go to the next slide.
Timestamp: 1062 sec to 1121 sec
There’s something called the Turing test and this was after named after computer scientists called Turing in the 1950s and he proposed this test of artificial intelligence. And essentially what he said is if I’m an evaluator and I’ve got a computer in one room and a person another room and I can’t see them. So I’m only communicating via text. You said to have passed the Turing test if evaluator cannot recognize the difference between the computer or the human now, we’re actually Beyond this Turing test and I wanted to just go to the next slide which is a video really interesting video on Google and how much progress It’s Made on artificial intelligence using natural language processing. I think you’ll find it interesting. Let’s play this video the progress of the system.
Timestamp: 1121 sec to 1180 sec
As I said earlier our vision for our system is to help you get things done. It turns out a big part of getting things done. It’s making a phone call. You may want to get an oil change schedule maybe call a plumber in the middle of the week or even schedule a haircut appointment.
You know, we are working hard to help users through those moments. We want to connect users to businesses in a good way business is actually rely a lot on this but even in the u.s. 60 percent of small businesses don’t have an online booking system Sarah. We think a I can help with this problem.
So let’s go back to this example. Let’s say you want to ask Google to make you a haircut appointment on Tuesday between 10:00 and noon. What happens is the Google Assistant makes the call seamlessly in the background for you. So what you’re going to hear it?
Timestamp: 1180 sec to 1239 sec
Google Assistant, actually calling a real Salon to schedule the appointment for you. Let’s listen.
How can I help you? Hi. I’m calling to book a woman haircut for a client. I’m looking for something on May 3rd. Do I give me one second? Hmm for what time are you looking for? Well.
At 12 p.m. We do not have a 12 pm unavailable. The closest to that we have available is a 1.15. Do you have anything between 10 a.m. And 12 p.m. Depending on what service you would like? What services you looking for? Just a woman’s hair cut for now. Okay. We have a 10 o’clock.
10 a.m. Is fine. Okay. What’s your first name? The first name is Lisa. Okay, perfect.
Timestamp: 1239 sec to 1298 sec
Fili thought panic lock on May 3rd. Okay, great. Thanks great. Have a great day. Bye.
That was a real call. You just heard amazing thing is the assistant can actually understand the nuances of conversation. We’ve been working on this technology for many years. It’s called Google duplex. It brings together all our investments over the years natural language understanding deep learning text to speech by the way, when we add on the assistant can give you a confirmation notification saying your appointment has been taken care of. Let me give you another example, let’s say you want to call it a restaurant, but maybe it’s a small restaurant which is not easily available to book online. The call actually goes a bit differently than expected. So take a listen.
Timestamp: 1298 sec to 1357 sec
Hi, I’d like to reserve a table for Wednesday the 7th.
for seven people
Well, it’s for four people. Well people win.
When they happen again, oh, actually we leave her for like a pro like a fire people for beautiful. You can come.
How long is the way usually to be seated fuck when tomorrow or we gay or?
For next Wednesday the 7th. Oh, no, it’s not too busy.
See if you can come over.
Oh I got you. Thanks.
Game that was real call. We have many of these.
Timestamp: 1357 sec to 1416 sec
Samples for the calls quite don’t go as expected, but the assistant understands the car.
Yeah, so we’re going to cut that out there but Hugh thanks for calling that video act. If you haven’t seen it. It’s a real eye-opener and signposting. I guess what our lives are going to be like in the future and arguably, you know subjects are a few teething problems there. I think you know, they’re going to be better lives in some ways, right we can talk to people when we want where we want arguably choose to sort of person. We’re talking to a little bit more as well. So all quite exciting now, let’s move into some use cases that we’re seeing in the insurance sector specifically and we wanted to start by taking a look at a business called Wealthy which is which is based out in Asia and how they’re applying the use of the AI technology in the management of chronic diseases and Andrew is going to give us a bit of a bit of an overview of what they’re up to. So Andrew over to you, please
Okay. Thanks a lot Simon and thank everyone for joining.
Timestamp: 1416 sec to 1475 sec
This the Wealthy stay on that slide Brooke, Wealthy Therapeutics. I became aware of them a couple of years ago. There are digital therapeutic platform. So I’m not sure if all of you are aware of what a therapeutic is. It’s effectively a an evidence-based program where it’s almost tested like a drug. It needs to actually prove its efficacy through chronic clinical trials and the results need to be written up and presented at at Medical presentations where they wear their peers can can look at the results and actually validate the the the work that the therapeutic is done. So it’s it’s quite different from the sort of Health a health and wellness sort of programs where the sort of quite nebulous
Timestamp: 1475 sec to 1534 sec
these Therapeutics programs are targeted at specific diseases to to actually help people improve their conditions and I’m really attracted to this sort of Technology this sort of approach because this is something that costs ensures a lot in terms of the claims, but we can provide drug free services to actually reduce risk or even bring people that may be overlooked from insurance today and bring them back through these sort of programs either. These are something a technology that the insurance companies and Industry can really get behind because they’re so a real win for everybody.
So let’s next slide. Let’s have a look at the platform. So as you can see AI is at the very center of the of the program and if you look along the bottom, it doesn’t come out of the vacuum
Timestamp: 1534 sec to 1593 sec
So because we are dealing with chronic illness there’s a foundation of clinical science that the program is based on. So if you think about it is putting up the guard rails around what the application will do. It’s all based on, you know, 30 40 Years of science learning that we’re now using applications to really make it work. The second thing is that with a lot of the diseases we look at chronic diseases. They can be really influenced by Behavior change. And so Behavior change logic is really built into these kind of platforms and then intent in differentiation from say a wellness program where you’ve got generalized guidance, these programs are very specific. They’re targeted at the individual and that’s a key part where the machine learning helps.
Timestamp: 1593 sec to 1652 sec
target the messages make sure that they’re really working in the clinical way and effectively changing the behavior. You also need to be able to configure the therapy. So in this case, we’re dealing with a wide range of chronic diseases. And so depending on the individual there may be different types of therapies that needed depending on if they’re mainly diabetic or the got a heart condition or they’ve got a lung disorder. And so these the ability to configure the treatment is critical and finally we need to culturally adapt the program. So the the what we eat in India is different from what we eat here in Australia what we eat in in Singapore. And so those cultural nuances again a part of making the program a personalized and AI sits at the heart of all these these things in making it work.
Timestamp: 1652 sec to 1711 sec
Get on to that in a moment. So let’s go to the next slide.
so you can see the the range of diseases that the wealthy platform handle so going from diabetes through the kidney disease through the heart heart disease through their lung disease and it’s unusual for a therapeutic platform to be able to cater for so many diseases and this is another reason why I’ve been really interested in in the wealthy program it’s a fact that it can actually Target a range of range of related diseases that I really a bane to Society at the moment. You can see also cancer and women’s health things that are coming up. So again, these I Know in Australia the cancer
Timestamp: 1711 sec to 1770 sec
Has been a really major issue with other therapeutic platforms going forward with that. So I think this is interesting and you’ll see how AI comes in to the next next slide.
We move to next okay. So in terms of using AI is really great at being able to gain insights on an individual individual basis. So if you’re dealing with hundreds of thousands, so in the case of the wealthy program, they’ve got I think nearly a million lives under under observation and their intervening actively in something like about 25,000. So to be able to do that cost effectively you need an AI system that can actually read the inputs and start to provide proactive information back to the individual so they can then manage it in this case.
Timestamp: 1770 sec to 1829 sec
Looking at diet. So logging the diet are getting the asking the detail of what the meal was with the individual the AI is doing that and then coming back with some advice around the meal
next slide, please.
So it’s not the AI doing this alone. In fact the way the wealthy program works. It’s a holistic program and they do employ people. They’ve got para para medical people on board. They’ve got dietitians and so on and so what the what the AI and machine learning does its able to enable these Specialists to leverage their attention and be able to cover a much much wider span of of people within the program. So I think for the wealthy guys told me that
Timestamp: 1829 sec to 1888 sec
When they kicked off the program when AI was just very in its early stages of learning they could manage about 25 patients per health coach health coach. Now, they’ve been able to get 10 times 15 times that with the use of the AI to be able to highlight those things that clients need to give the best answer or range of answers suggestions to those coaches so they can really personalize the treatment and really engage with clients in a meaningful way if you think about it, if you’re trying to launch a program like this, the only way you can do it cost effectively if you want professional people to be handling and to be able to run that span then AI is really the only way to do it. Let’s go to the next slide and the the other benefit of this so getting advice its scale is the ability to
Timestamp: 1888 sec to 1947 sec
enable early intervention. So doctors are also on this program and so they can get advisory saying hey, I think this guide it looks like he’s trending to have a sugar event or he’s going to have some kind of a kidney event. So these proactive early interventions make it possible for the doctor through the use of the AI to really focus and really get to those cases that so they can be prevented from actually crashing out having a having an episode. So again, this is I think a really powerful use of AI in terms of a partnership to make a real difference to the risk to people’s lives and to the health of the community and this is I think this is one of the program’s I’m really really keen on I think that’s the last slide. I’ve got in this deck so you can go to the next slide
Timestamp: 1947 sec to 2006 sec
Yes, so Andrew, thank you very much. And I kind of agree with you. I think this is a really good example, but it is just one example. So what we wanted to do it in stages engage our audience in this topic and we’ve got a quick poll question for you. So a question is going to come up on your screen. Now if you can all please quickly sort of answer with the what you think is the appropriate response. So how exciting do you find the possible use of AI to detect disease early and help people to modify. Their behaviors is a game changer, really? Exciting is that lots of potential but you know more time and proof is needed that you were a bit skeptical or not really convinced relative to other areas of attack and aI is of opportunity. So have a quick answer of that. And in the meantime Andrew, maybe I can just ask you a quick question while we wait for results. I mean the wealthy approach is a bit of a blended approach as you’ve mentioned. Its of integrating AI with human. Is this the future for most sort of AI deployments in the foreseeable future.
Timestamp: 2006 sec to 2065 sec
I think we’re going to see a I taking over lots of jobs in the next couple of years.
I personally don’t think we’re headed for that. I think it’s called Singularity where the where the AI become smarter than us. I think for industry see a see it in in underwriting. We see it in the in the commercial property where the AI can actually really help improve the quality of decisions being made and and getting rates quickly and empowers maybe less professional people.
People that may not have been trying so much they can actually perform at a much higher level. So I think the AI is a great partner. I think nothing to be afraid of at least until Arnold Schwarzenegger comes down as the Terminator0
Okay. Yeah, and you’ll probably see and everyone will see the results and maybe of just come up on that question as well around you know, where we are on the journey and currents are potential. I think most people
Timestamp: 2065 sec to 2124 sec
leaning to the side of this is potentially exciting. But you know, we need to see a bit more evidence of how it’s going to be deployed first that and that’s generally a bit of a pattern for a lot of the categories of Insur-Tech right that you know, it’s still Insurers are trying to find real sort of ways to deploy at scale and get real value, right? Yeah. So okay, maybe we’ll come back to that result Andrew when we get into Q&A, but we now wanted to just flick over to the other side of the world actually for a case study on lemonade and And for the most people would have been aware of the fact that Lemonade’s had a lot of air time recently, but may not be as close to the business to know the dark see a lot of what it’s been doing is got a AI embedded in it. So Hugh is just going to give us a bit of context of this and and why we think this case studies interesting cute.
Yeah, thanks Simon. And this is part of our TDI Academy series and we’re going to talk about that a little bit later and we’ve recorded it. So what I’m going to do is
Timestamp: 2124 sec to 2183 sec
To go online and show you something my TDI Academy, which is a little case study on lemonade and it runs for about eight minutes. So I will share my screen and navigate through to where we need to be but this would be the academy area and I’m logged in here. I’m in the relevant section of the lesson and we’re going to go and straight into this lemonade new business model. So I hope you like this play for about eight minutes.
Let’s look at our first case study, which is on lemonade and I’m sure you’ve heard about lemonade. I guess it’s one of the rock stars that you like of Insure Tech and it’s area of focus and why it’s relevant for us in this lesson is AI for claims services and personalization and they’ve got a tagline forget everything, you know about insurance powered by Ai and driven by social good.
Timestamp: 2183 sec to 2242 sec
This Is a great example of a new?
I’ve lost the same care of you.
Okay, I’m going to well, I’ll try and reshare on that and the more they are so was playing the sound Simon. All right, it was playing sound and then after about a minute, it’s it stopped. I think for everybody we’re definitely got good engagement from the audience because we got a lot of people just pointing that out. So thanks for that feedback. Yeah. Okay. I’m going to re going to reshare and see whether see whether this works or then I’ll just rewind it a little bit ago.
Timestamp: 2242 sec to 2301 sec
Should be playing now. They’re claiming some fantastic results on their tablet and personalization and they got a tagline forget everything, you know about insurance Powered by Ai and driven by social good. So this is a great example of a new company. That’s come up. That’s put AI at the heart of its delivery has two chat Bots and that help in this area. So one Is around policy issuing and servicing a chatbox called Maya and then they’ve also got a chatbot that they use in the claims process itself and they’re claiming some fantastic results on their claims AI in particular. So they’re able to respond and issue claims assessments and approvals within three seconds. Got a very very high rating as you can see on the app store for the app they got
Timestamp: 2301 sec to 2360 sec
In this area and they’re doing really well. So they’ve got about three hundred thousand or more policies. I think reported as of last year about 50 odd million gwp, and they’ve got a valuation of two billion dollars and they’ve raised so far around 500 million dollars. They started in New York. They’re expanding within the US and they’re also I believe looking to expand into Europe perhaps into Germany.
It’s a really interesting use case and I guess it’s a use case where AI is not just the value chain tool. It’s become embedded in the delivery of a new business model. So it remains to be seen how disruptive lemonade will be but certainly so far has been disruptive. It’s achieving its objectives. It’s got some great shareholders in SoftBank and Allianz. So I think they are aim is to try and change the traditional.
Timestamp: 2360 sec to 2419 sec
Okay, so here we’ve got same issue again dropping.
Okay, it’s not working very well today. I will have one more go at it. And then if we do that again, I think we might have to do that bail on this as well. Yeah, that’s alright. I just give you a heads up. I’ve got a question for you on this you when we’re ready, which is what you just you know, you know this business model quite well in and what’s your favourite bit of how AI is being deployed in lemonade where are you seeing It most most exciting has been used all over the place, right? But let’s just have one more go first at finishing this off. Yeah, okay.
Okay, which takes a fixed fee 20% of the gwp and then they’ve got a specially constructed Insurance non-profit vehicle.
Timestamp: 2419 sec to 2478 sec
Actually is the risk-taking vehicle. Now. The question is over time. I guess there’s two questions are they can track the right customers the honest customers to have better claims ratio, so certainly got the processes in place.
Okay until want to achieve that but if they don’t will they be able to divorce themselves from that reinsurance than that risk elements as well. I guess that remains to be seen but it’s a really interesting use case will watching lemonade closely and seeing how that evolves over the next couple of years.
Before we move on to the next case study that’s just have a look at this five minute video, which is an interview with the founder of lemonade and I think it’s an interesting video. So that’s that technology will overhaul the home insurance industry by Leading a 120 million dollar round
Timestamp: 2478 sec to 2537 sec
In the startup lemonade the company uses artificial intelligence and Bots to minimize paperwork and speed up the claims process for renters and homeowners. So what has lemonade been up to since this high-profile investment. We are joined Now by Lemonade CEO and co-founder Daniel Schreiber in New York Daniel. First of all, you know, now that you’ve got this money, where have you been putting it to use and what sort of progress have you made since this cash infusion?
Well, I mean like you said, we’ve been investing a lot in artificial intelligence. And really trying to build an entirely new kind of company that’s built on a substrate of technology and data and what that means is that we can use AI to pay claims. We pay claims in as little as three seconds and most of our resources are going into exactly that building a new kind of company built on that substrate.
Now you obviously get a lot of very privileged information about your customers and you know over the last few weeks. We’ve been talking a lot about privacy about
Timestamp: 2537 sec to 2596 sec
Data Privacy, you know, how are you sort of handling your relationship with the customer internally and you know, have you learned anything at Lemonade’s and some of the revelations we’ve seen coming out of Facebook.
I think so, you know insurance is a social good. It’s an economic necessity but it’s not trusted. It hasn’t been for hundreds of years. If you look at the urban dictionary, you’ll see as defined as a promise to pay later that is never fulfilled. So trust and Trust to related issues have been endemic to insurance. Way before the Facebook issues Rose to the for so we’ve really tried to build an alternative business model that aligns us with our customers Insurance often finds you conflicted with your customer. If I deny your claim I get to pocket those monies and we built a different business model kind of a Ulysses contract where we tie our own hands to make sure that we’re really aligned with our consumers in a way that the traditional Insurance players and some of the leading Tech players have a difficulty doing
so if I’m a customer how might my experience with you be different than
Timestamp: 2596 sec to 2655 sec
And a traditional Insurance giant.
I think you’ll find very little in common. So when you buy insurance on lemonade you download the app or you go to the website, you’ll be insured in a matter of seconds. Literally if you spent more than 90 seconds buying Insurance, you’re probably doing something wrong. So it’s a seamless experience. We are talking to a chatbot. It’s delightful. It’s instantaneous and more remarkable than that. Is that when you make a claim, it’s the same thing zero paperwork instant everything a third of our claims are paid by Our AI in 3 seconds you press submit and the money is back on your debit card within 3 seconds and the third part is not only does AI allows to transform the experience but it allows us to lower costs. So for first-time Insurance buyers younger consumers, the savings can be very dramatic. You’re talking about 70-80 percent savings more often than not.
You guys are spending been spending a lot on advertising and I’m curious how some of these costs.
Timestamp: 2655 sec to 2714 sec
Have Paid off in growth, you know, how are the cost stacking up relative to the progress that you’re making
We still a young company? We launched 18 months ago. So these are early days but we are seeing growth well ahead of our expectations in the six quarters that we’ve been in business. We’ve grown a hundred percent quarter-on-quarter. So certainly we’re seeing growth that has been way ahead of what would initially planned and what that really means is that about amongst first-time buyers of insurance. We’ve become the number one brand so I marketshare amongst early adopters of Technology, but Millennials and young consumers in general has risen to the top so that we are now the First Choice amongst renters who are buying insurance for the first time. So the growth has been surprising and fabulous for us.
Hey, we got through it. Well done Hugh really interesting. I think case study their good to get a bit of sort of Flesh on the bone really into for those who have heard.
Timestamp: 2714 sec to 2773 sec
Name that innate but not not understood it too much. So Hugh very briefly in a nutshell. What’s the best part of you know the AI usage for you in this lemonade model?
I think the business model has been started from digital first and I think it’s the use of chatbots to engage with customers for the fulfillment and point of claim that then provides the data for the AI to use. So this business scale model data to learn and then deploy and get better over time. So that starting point chat getting the data and of course that chat interface by the time they move into life as well as but to me that is the interesting news.
Yeah, okay. I mean, of course that business relatively fortunate in that being a green filter able to sort of not have to worry about much of the Legacy that many of the people on the call are going to be working within the constraints of but some great we’re going to move on here with back to a bit later. So now we’re going to move back to Asia.
Timestamp: 2773 sec to 2832 sec
Business very much close to home for those that are in Hong Kong orbits. We’ve got people around the world and in a moment. We’re going to hear from Nora physically live as Innovation, actually for AIA here in Hong Kong and about their product Fusion which uses AI to improve underwriting now, actually we ran our Global Insurance Innovation Awards last year in November coincidentally AIA With this Innovation won that award. So what we’re going to do to start with this play a little bit of a recording of the pitch. They made that won that award and then we’ll come in to live with Nora too soon to have a bit of a chat about it. So if we can just run the video first, please
Hi everyone. I’m Laura work at AIA and I’m from The Innovation team and this year. We have worked on a AI project for underwriting. So this is a homegrown AI underwriting engine.
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I’m going to share with you the problem that we are solving the solution that we have in the business impact that our project brought the table. So basically insurance has been catching up with the e-commerce industry where like we are not expecting customer to wait for so long for their applications to being passing through and the fact that actually these applications go through a machine and their applications that go through a machine that decides okay to accept this application or refer to the underwriter, right? But this process would be slow down if the machine themselves are not maintained well and if these machines themselves are out of date, so it looking at the increase in demand in Asia that we are expecting 30 percent year-on-year increase in number of applications that we have to process. So for the customer they basically if we don’t do anything about it, our customers are going to get angry because of like
Timestamp: 2891 sec to 2950 sec
Slower processing time too many applications are going through the same machine for Underwriters is a lot of stress because they have to stay longer and more complex cases are as diseases get more complicated and also AIA it’s going to risk our reputational risk because we’re not serving our customers to well as well as like not being up to date with what we can provide to our customers. Right? So what we do is that we looked into how we can do a breakthrough in terms of the commercial rule base engines We created this AI underwriting engine that uses a combination of AI machine learning models as well as rules to create what we call fusion today. And this is basically a homegrown underwriting engine or the expertise is within the team as well as our local markets expertise and underwriting processes itself. So I’m going to play a video that explains
Timestamp: 2950 sec to 3009 sec
The tool itself how we’re putting this AI engine into operational practices, but also give users a particular people who don’t have much technical skills to be able to operate and a machine where they have transparency into the machine understanding that the positions that the underwriting engine makes that there is intelligence understanding how the machine can process through.
text will be called what people type into them message boxes within application as well as some lightweight ruin what we called as like control for for for users of fusion that they will be able to manipulate the rules and self in the engine itself. So I’m going to play a video here before that. Let me explain to you. So how does technology works actually so it’s gonna
In applications, we have structured data and unstructured data. So these two things
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That used to pass through rule base engine, the rule base engine will look at the yes/no questions and underwriting application form and it’s like a clean case then it would go to a straight path right will be automatically accept. But if there is a free text within the application itself, then it has to go through an underwriter because the rule base engine doesn’t understand what the customer wrote in there. Like it could be something important about their health. So what we do is that we use an AI on the underwriting engine to process both structured data and unstructured data so that we can push up the auto underwriting percentage which means the straight through rate. So this is going to help Underwriters process on decisioning that they don’t have to otherwise. So now play this video
Timestamp: 3068 sec to 3127 sec
We found we had a really unefficient underwriting system, then we could not really optimize the opportunity that we had. So we wanted to look at an alternative to LeapFrog a whole generation, which has the AI or machine learning. Fusion underwriting employs ai machine learning and rule-based engines to enable faster and more efficient ways to process traditional and non-traditional data for risk management. Fusion has analyzed over 100 Years of customer data finding actions in the answers to inform fair and objective underwriting decisions. Once Fusion is launched we expect our auto underwriting to further improve from 70% to 90% of the easier cases are being approved by the artificial intelligence and the underwriters. There should be able to hone her skills to be able to judge more complex cases in fusion AI fuses with our Underwriters expertise and human and machine learining
Timestamp: 3127 sec to 3186 sec
from each other for example fusions pretext classifier and process both structured and unstructured text and will decide if a human needs to review the data for a decision to be made
Fusion can then learn from these interactions with the underwriter. Our Underwriters will help shape half-eaten advances. Also presumably the app will provide us the reasons why an application is not approved and they will be able to review study and then it will be able to suggest to us which was to improve on. Fusions lightweight rules engine allows the technical team to make simple updates in the AI rules and models saving both time and cost. With the launch of fusion by 2020 this will support our business to triple…..
Timestamp: 3186 sec to 3245 sec
So Nora congratulations again for winning and that excellently back in, back in November. I appreciate that may have been a little bit lag for some people we’re still as a little as a as a world getting to grips with sort of bandwidth and things at the moment particularly, but Nora well done, but that was quite a few months ago. So I guess my first question is just so how it’s been going since since your last saw the picture and winning.
Has been going great. So for Philippines is our first market for launching fusion, and it’s right now a few months after we have fully launched AI underwriting engine and has worked really well. We received great feedback from the users as well as from IT where operationally engines are going very smoothly and it was actually
Timestamp: 3245 sec to 3304 sec
Out of expectation. We thought that there might be more nuances coming after we’ve launched it but actually actually went a lot smoother than we we thought it would be because it’s never go perfect for this year. We are moving on finishing development for other countries. So we have great experience in doing it for one market and we are doing similar things for other markets, but we actually also want to put in extra capability given that we already have experience on Philippines. We thought that maybe there are other valuable features that we might be able to introduce the fusion for other countries where the regulatory requirements might be different. There. Are they operational demands might be different. So for for Market, there’s a different use case and our AI team is very kind of well versed
Timestamp: 3304 sec to 3363 sec
with underwriting now and we’re very much in touch with the subject matter experts and underwriting working together as to what would make the underwriters happy using AI. So this is where we are today. And now we are looking forward to doing more good work.
Yeah, we’ll look. Congratulations again. It’s great to hear. It’s going well in the spirit of us all working together which aligns to HKFI mandate of you know, working with the whole industry as well as TDI Can you just share one little thing with everybody on the call and you know one little bit of the secret that you’ve you know, you’ve lesson you’ve learned that everyone else could benefit from some to implementing AI
yeah, I think the biggest learning that I have is always start small. We’ll start with people who really understand the subject and people who would actually sponsor the project. So if you start small proving that basically a proof of concept
Timestamp: 3363 sec to 3422 sec
proving that it actually works would give the sponsor confidence to been more extra resources than commitment into making a bigger scale project. And once you have signs and models built and you proved it to the subject matter experts that actually works and it works label Leaf month after month and you can turn it into a project where you can launch and by doing that you actually need to its up people’s think it’s a, It’s change management is transformation. Right? So you really have to get in touch with people who are going to use the tool and ask them so that through user sign Centric mode where you understand how people use how people look at things. What would be more convenient to them is really about looking at things that the users perspective per se and the sign of it. And so that ensure that the
Timestamp: 3422 sec to 3481 sec
transformation will go well and people love to use it. It’s not going to be like a project where you built something and you will forget about after a few months.
Yeah. Yeah. Okay, and I just saw a question just come in just from somebody’s asking. How big is your AI team is that an easy question to answer if it is, please answer it. If not, then we’ll move on
it’s more we have more than 10 people
Okay, very good. Now I want to thank you again. I want to bring Andrew in just on this discussion around the implementation. Maybe you can share some slightly broader perspectives, you know outside that individual in Insurer on the kind of I don’t know maturity model, how are things sort of stages of development in this space for insurers? What does it look like? Maybe next slide, please?
Yeah, well Gardner has a 5 stage model that they’re the using this this model here. They’ve got the five levels. So obviously it’s starts off with some sort of awareness and they they categorize that as having probably
Timestamp: 3481 sec to 3540 sec
Too High expectations initially maybe overhyped and getting but that’s sometimes necessary to get the board interested in doing something. I guess the second level is whether active and they actually start to do something and mainly do some little little types of experiments level three is where they operationalize it bring it into their day-to-day use and then 4 is where it becomes pervasive across the business where it’s actively being used and then level 5 is what they call transformational and that’s where it’s so ingrained into the organization. That’s part of the DNA. Everybody thinks in terms of AI. So this is what what Gartner how they’ve lined it out and I would I would say most insurers are properly it level level.
Timestamp: 3540 sec to 3599 sec
One two three, I would guess Nora I don’t know what what you would categorize based on where you’re at, but you’re definitely level 3 in your at least I would say, I don’t know. How what have what would you say based on this scale?
Yeah, I think level 3 is a pretty good fit according to the description that I see on the chart.
Yeah, I have to say I was just thinking of that same question for you Nora and that’s kind of where I had you tagged as well. But what I’d like to do we got another call from the audience. Let’s see where people are and they’re different companies. It doesn’t fully aligned to that maturity model but is a quick question that’s going to be coming up. I guess how well Advance do you think your companies and use of AI and the options are awareness active operational systemic transformation. Also, I think that does align with the going to thing maybe so maybe we can pull that.
That question up now in pole so that people can can answer that.
Timestamp: 3599 sec to 3658 sec
And maybe while we’re doing that was there. Was there any other slides Nora that we hadn’t shared of yours that you wanted to just cover on this sort of question of implementation?
I think that’s it for now.
You’ll feel good. Are you okay? So hopefully the polls coming up.
Then you read it. Yeah, Nora I had a question for you. One of the ??.
Yeah, in terms of one of the things traceability I think is a really key factor and know that MIS in Singapore has been really pushing that in the ethics of using AI. So how conscious of where you in moving in that way initially.
I think there’s something that’s very what we call
Timestamp: 3658 sec to 3717 sec
I guess like we have pretty good risk management awareness and practices at my company. So this is something very basic. Like if something went wrong, we want to know how it went wrong. Right and if something went well, we want to know how much of that how many of those cases actually went. Well, so it’s basically a monitoring process that we are going through and according to what you said with with Singaporean regulations around AI we’re very well aware of that but it wasn’t really based on the Mas requirements. It’s more more of a business user is Centric design itself, but somehow it also perfectly aligned with the ethical concerns that people have around AI being transparent and that people’s data are respect.
Timestamp: 3717 sec to 3776 sec
Maybe we can just bring the results up on that pole then briefly. Please just see where we are. So okay interesting spread here why we got 10 or 11% in the transformational space. So maybe they’ll be potential participants on our next discussion on this topic but 40% saying in the early stages awareness, so I guess this would have AIA as a little bit more of a sort of front-runner, which is maybe why you won the award at the end of last year Nora.
Andrew any Reflections on this
Yeah, I’d be interested to see maybe we’ve got some insuretech on in the audience. I guess they would be wanting to transform the industry. So that sort of makes sense. But no it’s good to see people looking at it actively need to have think about it and how it can be used in a really applaud AIA in their in their considered use in the way.
Timestamp: 3776 sec to 3835 sec
It actually implemented. So I think it’s excellent model for everyone to follow.
Yeah, very good. So, thanks again, Nora and Andrew for your thoughts as well. Let’s um, let’s let’s move on now. There’s a question that’s just come through this stirring up a little bit of a discussion. So I thought I’d just call it X is quite fun. I think from some. Here we go. How thick data is most important in AI and ML. Will thick data replace big data. So Andrew, I’m going to bring you in as our resident Tech.Expert here my understanding of thick data. Is it in relation to behavioral data? So it goes beyond transactional information and kind of looks at behavioral patterns and put almost gets into Predictive Analytics based on that sort of information around how people behave so is this the next evolution of AI the next level up using thick data
or absolutely we need to be using a larger data set. We’re dealing with behavioral elements and we’ve got we’ve got
Timestamp: 3835 sec to 3894 sec
Fantastic capability to do that with not only people but with machine so you think about telematics we’ve got in the industry 4.0. You’ve got a lot of iot data means that we can actually reduce risk. And I think that’s a good thing. We start of sitting back some fat and happy we can paying out when clients come we can actually partner with our clients and really help them excel in their business and this sort of data if it’s provided to the insurer the industry, we’ve got the risk management capability and the ability to really model and and give value back to our clients. So I think it’s a start of a golden era for the insurance industry. We really tackle it the right way.
Yeah. Absolutely. I mean, I think the key with this is I think you know, we just can’t do everything ourselves internally. So we just got to get better at leveraging
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External Relationships and partners to get more of this done right this and I’m going to move us on this re good questions coming in from people around the world. So, please keep that interaction going on. The panelists will keep answering as best they can, but I do want to make sure we’ve got we get our five minutes with Celine from HKFI we heard from Selena earlier on some of the broader sort of progressive stuff that the HKFI up to in Hong Kong Celine. Just please bring us up to speed a little bit more on how you’re looking at Tech Using different things to help move the industry on here.
Hey quite frankly happy about that previous poll question and proud to say that we do actually have something that is actually operational as well. Not just the AIA change going on there. So happy thank you for the introduction as an industry body Hong Kong FI has always been quite interested in countering insurance fraud and because we never had a very good
Timestamp: 3953 sec to 4012 sec
solution to fix that problem and we don’t have a centralized database. So back in the days. We were using really really out of date Solutions such as passing around papers and asking calling other insurers and see if they had similar cases but we knew there were Technologies going around and so we started sourcing people experts in the field to give us a solution. So
If we move on to the next slide, please.
In 2015. We began talking to a lot of experts in the field. We started in 2016. We had one of the big fours and one of the top legal firms in Hong Kong to help us build a solution as well as find fun ways so that we can actually build a business case so we can
Timestamp: 4012 sec to 4071 sec
engage stakeholders such as Government bodies or our members the insurers it was going to be a one for all and all for one solution a centralized database which would be managed by the Hong Kong FI so would be the impartial person. It would be powered by a tech company called shift technology. I think some of you guys may have heard of it. They specialize in detecting insurance fraud using AI so But then the obstacles came, of course, it’s a lot of money. It’s very difficult to convince. A lot of the big companies the multinational companies about privacy obviously and not everyone is tech-savvy especially the CEOs no offense to any of the CEOs, but it’s very difficult. So we began cracking on it wasn’t about just funds it was about getting everybody on board.
Timestamp: 4071 sec to 4130 sec
If we move on to the next slide
These are all the government and public bodies that we had to jump through hoops and hurdles and explain to them how our solution would benefit the Hong Kong the entire industry and all the big things that would come along with just a centralized database. We had the most fun speaking with different insurers legal and compliance teams, the IT teams and ensuring them that privacy is no not a problem. The cybersecurity is dealt way implementation to operational workflows. That was actually the initial bit if we go onto the next slide, please.
In 2018. We launched our first wave which included motor medical and personal accident and in 2019
Timestamp: 4130 sec to 4189 sec
we started our travel line of business in hindsight. We think we should have started with travel but because travel is quite complex as well. It actually covers everything in the 2018 wave all the motor medical personal accident and some travel delays lost luggage but travel insurance has always been a pain point for the industry, especially because we had a really outrageous case. Where a Single person took out 24 policies for a single trip and filed a claim against every single insurer. Basically, he bought 24 travel policies and mind you. We only have 26 insures in Hong Kong that offers travel policies.
So that was how bad the situation was back in the days and that’s not very long time ago. If we move on to the next slides, so we partnered with
Timestamp: 4189 sec to 4248 sec
Shift Technology and obviously they specialize in fraud detection the AI would be the platform would provide us with fraud alerts multi-dimensional that data analysis. So they were be able to use the data and reconstruct the social network of a the claimant. We are hoping in the later stages. We would be able to some of the Syndicate crime. So a third-party driver claiming to be a driver in another accident or something similar to that but that takes a lot of time obviously and we need to gather a lot of data. We are expecting Trend reports for the industry maybe in the next quarter or so just because we’re still building the solution and perfecting it with data. Obviously. We actually receiving motor suspicious alerts already since
Timestamp: 4248 sec to 4307 sec
January ish this year. We’re actually quite proud of that. It took us a very long time to get to our stage right now for the full circle. Of course, we actually established a anti-fraud committee. This is basically the part where the AI does the learning and our claim specialist from the entire industry all of the participating insurers that have joined our database. So these claimants experts would come in every quarter and sit with the data scientist and actually discuss about how we can perfect the the data and the detection of the algorithm quite interesting and you actually learn a lot of things and it’s not just about AI taking over claims specialist jobs. The claim Specialists are actually teaching the AI. So we move onto my last and next slide, please we always
Timestamp: 4307 sec to 4366 sec
This is for the kids of Hong Kong. We’re trying to keep the insurance premiums at Bay and obviously trying to protect the put honest policyholders because we do see quite a bit of insurance fraud in I’ll come take my five minutes is up, right?
Thank you so much. And I have to say you must be some sort of adrenaline. Junkie because you just described it being great fun to get so many parts of the industry. to work together in a line on something. I think most people on this call will know how unfunny it is. Just getting their own organization to do something. So to get tens and tens of insurers to align and other bodies of the government Etc and private Enterprises must have been some feet for you in the team. So yeah, I hate to think what something scary would look like for you but you know congrats again to all of you for what you’ve achieved and it’s great to see such a progressive agenda in Hong Kong now.
Timestamp: 4366 sec to 4425 sec
Got a quick poll. We just want to take from everybody on the call just in respect of where and on the basis of everything you’ve heard and what you brought into the says today’s discussion really where you see most important use cases for AI and insurance you can see the choices their recommendations and advice using AI algorithms AI enable chatbots better CS lead quality scoring for underwriting or for claims and maybe while you’re just thinking about that and before the results come up, I just want to update on a couple of Of developments at the digital insurer. So if we can just click on next slide, please.
We should have now you’re sort of questions coming up. We always like to just acknowledge. Thanks to our corporate members of which AIA is one of the support they give the TDI platform our purposes working together to accelerate digital transformation of insurance this kind of events very much part of that. So thank you to all of our corporate members around the world.
Timestamp: 4425 sec to 4484 sec
Like please and really we just wanted to just sign post the fact that I think one of the things we’re seeing is in is a need to accelerate the awareness of an enthusiasm for digital in to be a you to get digital from the few specialists in too many in the organizations. And as part of that. We’ve launched TDI Academy earlier this year and we’ve got different levels. I guess of a sort of virtual Learning and Development programs that we’ve we’ve launched we started With ADI a little mini MBA on digital Insurance in January, and that’s getting some great reviews, and we’ve got an executive level program just about a launch and also a certificated program as well. So different levels of opportunity actually quite pioneering pioneering around the world really to deploy this really sort of relevant content and digital Insurance in a nice easy to consume format.
So next slide, please just punch.
Timestamp: 4484 sec to 4543 sec
Through this the ADI program. There’s a bit of detail here that you can look at in the in the deck afterwards which will be shared with you but really interactive takes a while six months or so and really get you in and out of pretty much every area of an insurance company and how technology may be able to improve it as well as looking at new ways of doing insurance going forward really exciting in the format. We’ve got some great feedback, which I’ll share in a second that next slide. Please just sort of brings to life. I guess their dad.
Depth of what we’re looking at. So if we just took one of the courses like Tech enablers we run through all this sort of buzzwords spend an hour on each of them. Give a 101 on the technology some of the use cases how it could be deployed in insurance. So I think the people that are going through our first cohort really enjoying the diversity of this program and you can see on the next slide, I guess some of the kind of feedback we’re getting so this is very much by us developed by the industry with us for the industry.
Timestamp: 4543 sec to 4602 sec
Now corporate members and looking forward to getting more of you industry engaged and I think the key differentiators here. You can see on the right. It’s it’s digital first but not digital-only. So we do have some people at the end of a phone and online that can interact with people that are coming through. These is very relevant to our insurance markets. That’s all it’s focused on it looks out into the wider world for through consumer lens and it’s very Dynamic the content right? So really exciting development for us next slide, please.
Well actually just go back one. So I better just call up the results the last poll before we go into the next one. So Brooke are we able to just call up the results there? Yeah of this question of where’s the most exciting area? So quite mixed right other than lead quality scoring. I think people are seeing opportunities all over the place, which if we had a bit more time I kick around with the panel, but we don’t so thank you for that. And let’s just move into the last question because we do think this kind of Learning and Development and
Timestamp: 4602 sec to 4661 sec
Instilling more awareness of an enthusiasm for discipline in organizations is important. So we wanted to sort of move to a close with this question for each of you. How important do you think accelerating remote learning on digital insurance is for you and your company so important for my company important for me personally important for both not really important at the moment so you can quickly quickly sort of give us a results on that that’ll be interesting for us and then just to round out a Couple of other final sort of updates really next slide, please.
Yeah, just really to say clearly the coronavirus on all of our minds at the moment. As I said, I think this is an opportunity for the insurance industry to really step up at the same time. It is creating some short-term pressures as well as medium term opportunities. So we’re going to reflect on all of that in a webinar. Kindly support supported by Swiss re coming up next month Thursday the 23rd of April so mark your diaries for that. I’m sure it will be
Timestamp: 4661 sec to 4720 sec
Well attended and look forward to getting getting many of you involved in that that debate. How are those results looking brooke on the last question?
We able to pull those up yet.
If not, maybe just flick over to the last slide, please.
Yeah, so one thing we always like to do on these webinars is get a bit of feedback. This is the first time we’ve done something with HKFI so I’m sure they’ll be interested as well. So, please take the opportunity to quickly. Give us a bit of feedback on the survey when you get the recording link and come back to it to us as well either individually or collectively. I think the next slide and in the pack that you’ll get a link to is some contact details as well. So email addresses etc for a few of us been on the panel today. So how are we looking on those results?
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We have a view so important both for me and my company. Well, that’s good to hear unsurprising but really good to get that sort of endorsement really from so many people around the world that actually particularly at the moment upskilling in digital is kind of really important and we wholeheartedly agree. So hope we can help you with that both personally and across your organization’s so we’re going to move to a close just because I’m conscious of people’s time and time is money all around the world and equally we’ve got many other point on things to be focused on as well nice, so I just like to finish by saying firstly thank you to all our panelists for their time and their different insights today appreciate all your effort. So thank you Celine Nora Andrew Hugh and of course Celina, also, I’d like to again reinforce our house. Thanks and appreciation to HKFI for their kind support for making this happen on behalf of everybody on the call and last
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No means least a really big thanks to everybody around the world for getting involved in this in this discussion time is money really conscious of that particular in Hong Kong. So we hope you found it useful and please let us know in the feedback. If you’d like to get involved in some more and what sort of topics you’d like us to cover. So on that note we’re going to end here copies of this recording will be available for you and any other colleagues who would like to view it in a day or two and the materials will be added as part of that.
That as well, so thank you very much everybody and stay safe. Look after your colleagues your friends and your loved ones this difficult time. Thank you. Thank you.