Azure for Executives

The Emerging Technologies of Insurance with Rob Galbraith

Episode Summary

Insurance has some problems. It’s too complex, too expensive, and it doesn’t cover everyone. Our guest today, Rob Galbraith, the most interesting man in insurance and author of the book The End of Insurance as We Know It, says that tech can help though, but it must be relevant to the consumer’s needs. To support this hypothesis, he has coined the acronym S.C.A.L.E.D. to focus on the technologies he believes are transforming the insurance industry. He tells us what it means and explains each part in detail.

Episode Notes

Insurance has some problems. It’s too complex, too expensive, and it doesn’t cover everyone. 

Our guest today, Rob Galbraith, the most interesting man in insurance and author of the book The End of Insurance as We Know It, says that tech can help though, but it must be relevant to the consumer’s needs. To support this hypothesis, he has coined the acronym S.C.A.L.E.D. to focus on the technologies he believes are transforming the insurance industry. He tells us what it means and explains each part in detail.

Additionally, usual host Paul Maher takes on a guest role this week as a former CTO at Milliman and talks about what some of Microsoft’s big investments in insurance are and how Microsoft AI technologies are impacting insurers and financial services as a whole.

Episode Links:

Episode Transcript
The End Of Insurance As We Know It (Rob’s book)
Azure for Financial Services
Azure for Insurance

Guest:

Rob Galbraith is the most interesting man in insurance. He is a keynote speaker, media contributor, and bestselling author of The End of Insurance as We Know ItHe is the Insuretech Business Series man of the year for 2020.

Follow him on LinkedIn and Twitter.

Special Guest:

Paul Maher is General Manager of the Industry Experiences Team at Microsoft. He was formerly CTO at Milliman.

Follow him on LinkedIn and Twitter.

Host:

David Starr is a Principal Azure Solutions Architect in the Marketplace Onboarding, Enablement, and Growth team at Microsoft. 

Follow him on LinkedIn and Twitter.

Episode Transcription

DAVID: Welcome to the Azure for Executives podcast, the show for technology leaders. This podcast covers trends and technologies in industries and how Microsoft Azure is enabling them. Here, you'll hear from thought leaders in various industries and technologies on topics important to you. You'll also learn how to partner with Microsoft to enable your organization and your customers with Microsoft Azure.  

DAVID: Hello, listeners. Welcome to another episode of the Azure for Executives podcast. This is going to be a great discussion with Rob Galbraith, who is the most interesting man in insurance. He's a keynote speaker, media contributor, and best-selling author of The End of Insurance As We Know It. Also, he's the InsurTech Business Series Man Of the Year for 2020. Rob, welcome to the show.  

ROB: Thanks, David. It's great to be here.  

DAVID: We're really excited for this conversation. And this one's going to be a bit unique because our co-host, my co-host, the person who's always asking the questions on the show, Paul, happens to be a former CTO in the insurance space at Milliman. And we are going to play this a little bit different today. We're going to welcome him to the show as a guest. So he's going to represent Microsoft's view on the insurance space. And so with that, Paul, I get to welcome you to the show.

PAUL: Hey. Thanks a lot, David. It's nice to be able to wear a different hat today. So I’m super excited to talk about insurance.

DAVID: Right on. So let's start with Rob. Rob, you and I have had some previous conversation. And in that conversation, you told me a few things, like the fact that insurance has a few problems and that it's too complex, too expensive, and not everyone has the coverage that they would like or need, but that technology can help. Even so, it needs to be relevant to consumer needs and to support this, you've coined the term S.C.A.L.E.D, S-C-A-L-E-D as a framework to focus on the technologies you believe are transforming insurance today. And so, Rob, I wonder if you could tell us about your framework S.C.A.L.E.D, how it helps guide firms in the insurance industry.

ROB: Yeah, sure thing. So I get the question a lot in terms of what are some of the trends? Why are we seeing this explosion of technology? How's it going to impact insurance? And I was always trying to come up with a framework or a way to think about this. And so, what popped into my mind originally was the whole concept of agile methodology or the scaled agile framework that obviously a lot of developers and folks in the IT community are familiar with, and that distinction from the traditional Waterfall methodology of being able to just run in sprints to deliver value throughout the process, a very iterative approach rather than you gather all the requirements, and then you go off and a year or two later you hope you got it right. And meanwhile, lots of things have changed in the ecosystem.  

So building on that, my acronym, S.C.A.L.E.D, I always say companies need to be S.C.A.L.E.D, using the acronym, to be agile. And so, what does the acronym S.C.A.L.E.D stand for? So, the S is sensors. I know we'll talk a little bit more about this. But just the miniaturization of there's a computer chip in practically anything today, certainly going from telematics to smart home and IoT-enabled devices to things like wearables, which we'll talk about and many of the things. And quite frankly, I think about the distinction between maps and GPS. And you might've had a paper map, and you're guesstimating on drive times and things like that. Well now, with GPS, you can read the information from your mobile phone as well as thousands of others on the road. And it can be transmitted over cellular networks to cloud computing, which is the C in S.C.A.L.E.D. So having all of this streaming data, this plethora of data, this explosion of data needs to be stored somewhere. And in the past, storage was at a premium. I know way back, going back to my programming days, I would care about whether things were an integer, or a floating decimal, or one single character or a string. And now, a lot of those distinctions just don't matter because storage is not the limiting factor that it was for decades because of cloud computing.  And then artificial intelligence, of course, now that I have all of this data and I'm able to store it, how do I make sense of it? I can't just put it in an Excel spreadsheet and run a PivotTable on it. The amount of data we're talking about is too big for that. And so you need more advanced techniques, artificial intelligence, machine learning, and many other ways to come up with advanced algorithms to make sense of the data and to find patterns in it.

The L is localized knowledge. So again, thinking about the GPS example, it's not just knowing approximately where something is but really pinpoint down to a particular latitude and longitude, not just a ZIP code or a territory but really understanding at a very granular level. For parallels such as hail, for instance,  you can live on the same street, and one house gets three inches of hail, and another house three doors down doesn't get hail at all.  And it was difficult to distinguish between those two things in the past, and now we have much more granular ways to be able to detect that.  

The E is efficiencies in the back office, and there's a ton of technologies coming out. There are a lot of manual touches in insurance, and I think the pandemic has actually highlighted some of those gaps that we had in our processes. And we could benefit from automation; things like optical character recognition, robotic process automation, natural language processing, and the like are unlocking a ton of value that really frankly didn't benefit insurance customers very much. And so anyway that you can squeeze out expenses from the product that doesn't impact the customer service part those things are really valuable. Digitalization of solutions, video conferencing, and the ability for companies to very quickly overnight go to a remote work environment and using software like Microsoft Teams that we're recording this on it was pretty remarkable actually how seamless the transition was. And I know it was a struggle for a lot of companies behind the scenes. But from a customer’s standpoint, I think insurers did a remarkable job of pivoting during the Covid outbreak this time last year.

And then finally, digital is the D in S.C.A.L.E.D, and really it allows a business to conduct business without having to meet face-to-face. I know a lot of underwriters and claims professionals and loss control folks talk about the windshield time, driving from one agency to another or from one policyholder to another. And again, they had to pivot and find new ways of doing that, capturing video remotely, being able to analyze it, being able to do their jobs without being face-to-face. And I don't think face-to-face is entirely going away from insurance once things return back to normal. But certainly, we're going to be a lot more intentional about those face-to-face interactions in the future. And when it doesn't need to be face-to-face, or there isn't a lot of value to the face-to-face, if it can be done digitally, it will be.

DAVID: That's great. Thanks for the trip through the framework. And that really sets a stage for us because I think, Paul, maybe you could describe some of Microsoft's investments that might even fit within the framework that we just discussed. There are several technologies there, and I wonder if you could take us through some of Microsoft's big bets on insurance.

PAUL: Yeah, you bet, David. And Rob, that's fantastic. I was just hearing you walk through S.C.A.L.E.D. I think you touched on the plethora of scenarios and capabilities needed across insurance and different insurance types. We have something a little similar that we call our industry priority scenarios. And so you can think of that as we take a step back and think strategically, how are we thinking about the industry? And then, in this particular case, how are we thinking about insurance? And so S.C.A.L.E.D maps really well to that as you've thought about the different capabilities across insurance and whether we're thinking about life insurance, whether we’re thinking about health insurance to property and casualty to employee benefits, et cetera.  

And so certainly from a Microsoft point of view, I'll share a couple of points, David, to your question in terms of how we're thinking about how we can help. And at the core, of course, and Rob mentioned this: cloud has been transformative and cloud services. And so, really, with the advent of cloud accessibility, what we're getting is the opportunity to get near-infinite scale when we think about computing power in a pay-as-you-use model. And so that's something that hasn't been there before. Previously, large investments have to be made around, say, HPC infrastructure, et cetera, that are very costly. Now it's all of this being able to get the scale and the computing power that you need on-demand and not pay for what you use model. And Rob mentioned the data explosion. I think we talked about this notion of before; being able to consume that data going back over time was costly, but now data is just a commodity, that accessibility to data. And then, on top of that, is artificial intelligence. So it's not only being able to gather that data, but it's also using artificial intelligence to be able to drive meaningful insights on that. And so across all of that cloud computing power, that accessibility, that near-infinite scale, paying for what you use, the reduction of cost to use these capabilities, and advancements in artificial intelligence have been huge.  

And then when I double-click on that, when I think about it from Microsoft’s point of view of how we're thinking about some of the key areas that we can help, things like risk modeling, of course, is a key area where we've been focusing a lot of energy. It lends itself to cloud and that need for computational power during complex calculation processing. And, of course, it's important to do that in a timely and secure way. So risk modeling is one area that I would surface as a key area. And again, Rob touched on this in the S.C.A.L.E.D acronym, modernizing of core systems. Core systems are a plethora of things; it could be the back end, the RP systems. It could be the key financial modeling solutions. It could be the reporting systems. It could be the back-end systems. So it covers a broad gamut. But we were looking at that and as Rob said, what's interesting is if we look at pre or current times with the pandemic, the pace of innovation, if you will, around those core systems -- And keep in mind, those core systems have been built up over man-years. And so they're complex, they're embedded, maybe some institutional knowledge isn't there. So they’re certainly challenging to modernize or replace. But I think what we've seen is a change in mindset or a change in pace of innovation, given the pandemic in terms of just being able to deal with just simple things like people not being in the office and on the requirement for remote working, and the accessibility to IT infrastructure that previously were on-premise investments that now need to be accessible to remote workers, et cetera. So I think we're seeing a change in mindset or an increase in the urgency to drive modernizing these core systems, which is good. And of course, we're excited from Microsoft’s point of view in terms of the capabilities we have across our broad spectrum of our portfolio being able to help that.  

And then, interestingly, it's really delivering things like differentiated experiences in a way that organizations can really interact with their customers. I think I had the other week that there are more millennials now of any generation than ever before. And so again, that's really a changing of the guard and a changing of mindset. And so thinking about who the customer now is, what their needs are and what their preferences are, are very different than previous generations. It's much more about agility. It's much more about mobile users. It's less about going in and talking to physical people about policies. It's much more about point in time. I want to be able to discover on my own. I want to ideally not have to speak to folks. And I want to quickly be able to obtain information on what I need when I think about insurance and then be able to procure that as need be.  So there are a lot of things there, David, of course, but what I'm excited about is the synergies that we have as we think about these industry priority scenarios and helping the insurance industry. Rob has the S.C.A.L.E.D analogy. And we have good synergies as we think about that. And super excited about what Microsoft has to bring across our portfolio of technologies. But more importantly, as well, the partnerships that we have with insurance customers but also the partnerships we have with our partners as well because, at the end of the day, our goal at Microsoft is really building excellent technologies and platforms. We look to our customers and our partner ecosystems to really drive the innovation on our platforms.  

DAVID: Thanks, Paul. And I appreciate hearkening back to the S.C.A.L.E.D  framework and sharing Microsoft's description of what we're doing to invest. And so with that, let's revisit S.C.A.L.E.D a bit and look specifically at the sensor piece or IoT.

PAUL: So, hey Rob, we're going to talk a little bit about IoT and its impact on insurance. And, of course, we could think broadly across the different insurance disciplines. But talk to us why IoT has been so disruptive and delivered such an opportunity within the insurance industry. Some of my assertions are the price point for IoT devices and solutions has come down. Of course, some people say that insurance is dying a slow death because people aren't necessarily buying new insurance and a lot of that is challenges around things like life insurance. But what are your thoughts? And, of course, you're going to talk to us about the IoT opportunity. But why is IoT being so prevalent and opportunist, if you will, in the insurance industry? What's your perspective, Rob?  

ROB: Great stuff from Paul. And on the IoT front, we're very much early in the game, and there's this concept that's been described as discounts for data where a lot of carriers have been out there and saying, “Hey, we'll give you a 5% researched discount for data.” In the past, maybe you had to put a dongle in your OBD port on your vehicle. Now, increasingly, you can do that through an app on a smartphone and have the vehicle talk to the phone and capture all manner of things: your speed and your hard braking, things like that. And I think again, during the pandemic, this whole idea of pay-as-you-go insurance or pay by the mile insurance in the past was seen as maybe more of a novelty type solution that might appeal to urban millennial that maybe they have a car, but they either walk or bike to work most of the time. And they only get in the car to go out to visit family on the weekends or things like that. And overnight, folks like myself that were regular commuters, now, I've been working from home. I don't know that I even drove 4,000 miles last year after regularly driving probably between 12,000 and 15,000 miles very consistently over the past two decades.

So if you think about the traditional way of writing something like auto insurance where you're asking somebody's age, somebody's gender, somebody's marital status, and now I don't have to say, “Well, 35-year-old married females are better drivers on average than 18-year-old single males.” I can directly observe the driving behavior through telematics. Why would I care what their age or gender, or marital status is when I can directly observe their driving? I mean, that's ultimately what you're trying to get at. And being able to directly observe behavior rather than try to use proxies for risk really translates into all manner of things. And so it's not just on the telematics front but certainly a lot of the smart home technologies. We know water losses, for example, are a big part of losses to a home; probably between 30% to 40% of the losses involved are water loss of some type. And there are technologies out there that can actually not just measure your water flow, and some, even if they sense an unusual flow, they can shut the water off for you to prevent further leaks. But they capture a water signature of your home. And so they know hey, during a regular day, there's a lot of activity in the morning as people shower, and they get ready, and kids go to school and people going to the office in the past. And on the weekends, the patterns are different. People are sleeping in, and they're waking up later, and there's more regular water usage throughout the day. And so, over time, it can build these profiles and then be able to sense when there's unusual activity that is indicative that there may be a leak. There are a lot of things. I know we're going to get into wearables a little bit later, but on the life and health side.  

So agriculture insurance is actually another one, too.  IoT is often used to manage the modern farm. And so why would you not leverage the same technologies that you're using to manage operations to also manage your risk? And so we're starting to see some innovations there. So I could go on and on. But really, I think the sky's the limit, and it really is very much about re-imagining the way that we rate, underwrite, handle claims in terms of risks, but it is a complete paradigm shift. And so it's not always obvious how you go from your traditional rating or underwriting plan to this new world. So you definitely have to start somewhere, and you have to capture the data. But I think through things like artificial intelligence and others -- And the partner network that Paul mentioned, I think is another one where if you're capturing that data within your core system or maybe you've got an extension to a partner that has an app, for instance, for your phone to be able to capture that, then you can bring it back in or make sense of it. These are conversations that you should be absolutely having now and going beyond. “I think there was a sense of capture at first, and then we'll figure out what to do with it later.” Smart companies are figuring out what to do with it now and actually benefiting from that. And so I think if you're not at that stage yet, you need to quickly move on because it could be a lasting competitive advantage for those that really do not just capture it but figure out how to leverage it for their benefit.

DAVID: Thanks for that trip through some of the leading edge scenarios that you can see in the IoT space. Paul, I wonder if you could talk about some of the more forward-looking technologies that you see that will potentially have a disruptive impact on insurance.  

PAUL: Yeah, absolutely, David. I think I'll think about it in a few ways. It's really the cusp of innovation and blue-sky because there's lots going on. And Rob, I'm going to look back over your S.C.A.L.E.D acronym because I think that's a good guiding talk track as we think about what's happening. And so certainly, if I think about blue-sky, I'll throw it out there. Of course, I think everyone's super excited about things like quantum computing. And so I think that just takes things to the next level. I'll just leave it at that. There are lots of great reference articles to go read out there. But of course, quantum just takes things to the next level. We've already talked about how disruptive in a good way cloud computing has been. I think quantum just takes things to the next level. But when I think about the cusp of innovation, so things like computers, computer chips, et cetera, the innovation that we're seeing there across the various industry leaders continue to push the bar in terms of whether it be low-power chips to high-end driving, the capabilities to do things like GPUs on personal computers, all that stuff I think is super exciting when you think about the need to crunch data and drive calculations. Cloud, of course, the continued innovation in cloud continues to grow leaps and bounds, so you're going to see further innovation there.  

But things that excite me in the core is things like with the next generation of data centers, the innovation that’s happening there around getting further and further to being carbon neutral and the innovations that are happening there as an example, I think are super, super exciting and that continued innovation in the cloud space and then the expansion of data centers in other regions. But also, again, there's lots of reference material out there. Microsoft, for example, recently also explored different ways of how we think about data centers. So we did our underwater data center, and we did some prototyping around that, which is a great success. So I think the innovation that we'll see around how we provide those cloud capabilities is going to be really, really fascinating.  With AI, and Rob mentioned it earlier on as well, which is there's the partnership between data and meaningful insights, and so data in the world of cloud has become more of a commodity and much more accessible. Artificial Intelligence is not new. You can go read the textbooks from the ‘60s and the ‘70s. What is new is the breakthroughs in the calculations and the innovation combined with the computing power. So I'm excited to see how artificial continues to evolve and help things like RPA, things like being able to do things like anomaly detection and helping focus the skilled worker on skill jobs and using things artificial intelligence to further evolve whether it be capabilities insights or take away some of these skilled functions.  

Localized knowledge, as Rob was saying so the advancements on --we'll talk about wearables in a moment. But the continued ability for tracking insights and analytics, I think, is super interesting. So I think all of these things excite me, and so just some practical things as well is just the here and now and the cusp of the innovation. And just over the last week or two, for example, we furthered our HPC capability. So we released the HBv3 skew for those of you who are working with HPC, et cetera, so just lots of stuff in there, David, in terms of the here and now, and then obviously that blue-sky. But excited on a number of levels in terms of I would say cloud computing, form factors, innovation, getting to carbon neutral to innovation on cloud and services and how that's going to help us drive further insights further enable the workforce. And just even looking at the fundamentals of the chipsets, et cetera, are going to allow us to do high-scale computing to low-power devices. So lots of stuff in there, but hopefully, that was useful.

DAVID: Yeah, that was great, Paul. And I appreciate the trip through some of the more innovative things that are happening that are driving or tech that's driving innovation. So that's great. And one of those that was mentioned earlier is wearables. And I'm curious about wearables from the standpoint of is this a today reality of making a difference in the insurance space, particularly in health, or is wearable an up-and-coming technology? And Rob, I wonder if you could speak a little bit about that.  

ROB: Sure thing. I very much see it as an up-and-coming technology because, again, I think we're just at the tip of the iceberg in terms of what can be done. There have been several iterations on wearables. And I will say early on they were good in concept and good in theory, but the execution perhaps wasn't there. And I think we're also learning best practices. So, for instance, early wearables often provided some type of haptic feedback, whether that be a buzzing or an audible noise or things like that. I know I've, for instance, had wearables on my belt that you wear like an old school pager, for those of us that are all old enough to remember those and how popular they were in the 1990s where if you bend over to lift something up if you bend at the waist, it gives you a little buzz to remind you that no, you should be bending at your knees and keeping your back straight and things like that, a great idea. But if you imagine being a worker in a factory and you're having to do that eight hours a day, all that constant buzzing might get annoying or might get irritating. And so just trying to find the right balance between providing meaningful feedback but at the same time capturing the data in the most unobtrusive way so that the wearable doesn't feel like you're wearing a computer or devices. I know, for instance, of early exoskeletons, again, trying to give people added strength and less wear and tear on muscles and things like that. But they could be motorized, very heavy, you could be really sweating and just be very uncomfortable to wear. And so again, through iterations, we're really seeing just a slimming, more lightweight, more unobtrusive, and being able to capture a whole range of information.  

Interestingly enough, I will say that a lot of early hardware that I saw in the wearables devices have now been essentially replaced by your phone. Your phone can capture a lot of things. And all of us carry our smartphone around with us all the time. And so that is actually an amazing, wearable technology among the many other things that it does. Having said that, there are limitations; of course, your phone only has so many sensors and devices on it to capture things. And so noise level, light levels, air quality, things like that are the types of things that a phone isn't necessarily going to pick up. And so you are going to need some type of specialty hardware. But this is exciting because you can capture both external environmental conditions as well as biometric information in terms of how is that person reacting to that external stimuli? So when you're running, is your heart rate too high? Are you sweating too profusely? Maybe you should take a rest or a break. Or maybe you’re getting dehydrated or things like that.  

And you mentioned health. I know, particularly in many Asian countries, they really pushed the envelope in terms of life and health insurance in applications and being able to tie healthier behaviors and healthier outcomes to reductions in premiums, both on the health insurance side and on the life insurance side. No one is gamifying it. We see in the U.S. and other places in terms of if you drive safer, you see that now in your monthly premium, and you're able to directly tie your behavior to your premium on the property and casualty side. And we're starting to see that in other countries in the life and health space. Obviously, a lot of privacy concerns go with that. And so those are the things that I think here in the U.S. and other countries -- again, each country has different, privacy standards but we know in the U.S., in particular, it's a major concern. So I don't think we've seen as much advancement in those two continents. But it's really less of a technology barrier today as it is more the legal framework, the insurance framework really catching up to what technologies are able to do. In fact, I've even seen technologies where it's constantly monitoring your blood alcohol level. So think about long-haul drivers or things like that that you would want to just constantly monitor and make sure that they weren't ever above a certain level and things like that.  

So I do think over time, we are going to have a lot more wearables either that we're wearing all the time or things that we use periodically. I know in sports medicine, there are some technologies today that can see how prone you are to having a severe knee injury. And you can actually do some rehab ahead of that. They're saying, “You're about to blow out your knee. So we're actually going to have you sit out rest and do some physical therapy before that occurs,” knowing that being reactionary can cost millions of dollars in terms of being sidelined for that athlete. And those things are going to be coming to all of us. Very, very exciting, and again, we're just at the forefront of what we're going to see in the next 10 to 20 years.  

DAVID: Thanks for that. And I find it really interesting in what you described that most of the hesitancy or even, I'll use the word barrier, comes from industry rather than the technology itself of being able to capture some of this stuff. And along with that, I'll mention that in an earlier conversation that we had, someone mentioned EKGs. And all of a sudden, we all looked at our smartwatches. And that underscores the idea that that capability of running an EKG, even though it's very much unsupported and there are all sorts of disclaimers around it on our watches, but it's there. And insurance companies are being moved into the position of being the angel on your shoulder to keep you healthy, if you will and in the health space. And it's interesting that they have this relationship with their customers that now they are in this position of helping you stay healthy and it's in everybody's interest. So that's just a compelling scenario for me looking in on the industry. And with that, Paul, I wonder if you have a take on wearables you could share.  

PAUL: Yeah. Thanks, David. I guess I would start with what comes to mind. I got to spend quite a lot of time in my previous life and in my current life really working in this space and working with partners and vendors who are working around wearable solutions hardware, et cetera. So a few things I'd throw out there that come to mind that I think are fundamentals that need to be in place, and Rob mentioned it before, security and privacy concerns that's number one, which leads to acceptance. And so there's work to be done there and a good reason that we have policies and legislation in place, et cetera. So I think that's at the high level. There are different levels of acceptance, and that varies by country, et cetera. And so there just needs to be some standards and governing bodies, et cetera, and consortiums coming together to really, I think, standardized things. Otherwise, as we've seen with the pace of innovation of mobile devices and smart applications on smart devices, they should have been delivered much, much sooner. But because you didn't have that coming together across the different providers, we just had a slower pace of innovation. So that's number one is the coming together of the industry across some of the key elements versus working in isolation. Coming together, working together, working as a unified team with a common set of goals, I think, is going to benefit everyone depending on what these wearables are going to be used for.  

But things that go through my mind for wearables is what's the form factor? How many times is this proliferation of devices out there? And so some look better than others, some are easier to use, and wire and others are more clunky. So I think form factor is important, and I think bringing together standardization around that. And then there are practicalities which is what does the battery life look like? Is it really useful? It's only useful if you've got the right form factor if you've got the right battery life and the innards within the devices, the right power in those devices, the right capabilities with chipsets, same on things like connectivity. Is it seamless connectivity, or is there work to be done there? And then what is the cost of these devices? Because, of course, this goes back to the coming together, the standardization. What we tend to see with a lot of these wearables is it could be anything from mainstream well-established companies who are working on these solutions to startups, and economy of scale and reduction price point come together. So if you've got startups who would just have the great idea that they're having to make investments in both software and hardware, then they're going to find it hard to provide a good price point versus maybe a more established company that's working with an established solution hardware provider. So cost is super important.  

And then ultimately, the solutions that are on these devices, again, are they well-thought through? Are they actually delivering to the user's needs? That's key. Are they immature or rudimentary solutions that just let the experience down? I think you're seeing the convergence with some of the players. I mean, of course, watches, I think, have become a common form factor, and there are obviously some leading players there. And what's been interesting is whereas before perhaps there would have been multiple wearable devices doing different things, I think you've seen some interesting innovation on watches to be able to do a plethora of things and some super interesting innovation there anything from tracking your heart rate to doing estimates of have you fallen over? using the geometry of the device. So I think there are really some interesting things going on. And so I would underscore, which is saying I think wearables are super interesting. I think it's important that the rightful process goes in around what are really the problems that we're trying to solve versus finding problems to solve, so like all the really-real world first-party problems that are needed with these wearables versus it being a fad or a gimmick. And I would encourage the folks that are building these wearables, the more we can bring people together so people can benefit from each of these [inaudible 36:28] We can open source perhaps code where we can start to standardize on the hardware and bring price point down, get some consortiums together to think about these problems and how we can really help I think is key. So wearables are super interesting. I think we've seen some interesting applications, but I think we have some way to go, David, as we still figure out the space.

DAVID: Thanks for that holistic view, Paul. And one thing I'll just throw on the stack here is the self-interesting story, really, that you both have mentioned wearables and the regulation per country. So one of the things that is really compelling about that or interesting to me is that it's regulation per country and per industry that is prohibiting some of this movement. And I'll give you an example, the watch I wear, which I won't mention what it is, but the smartwatch that I wear is able to take blood pressure readings in real-time with a firmware upgrade. But that firmware upgrade has only been made available in Asian markets, so just another interesting component of this wearable story. And with that, let's go back to the S.C.A.L.E.D acronym. And in particular, let's examine the A part of that framework. And so, Rob, what are some impactful uses that insurers are finding for artificial intelligence? Is that really making a big difference for us already?

ROB: Absolutely. It is huge, and it really needs to be central to companies’ strategies in this space. One of the things that I think makes insurance somewhat unique is that it's a very old industry as we know. It's been around literally for centuries, and obviously, it covers a very basic need, that protection from loss, that risk management function. Risk is not going away. Exposure to loss is not going away. So there will be a need for insurance going forward; having said that, we don't have global supply chains. We don't need big capital investments in terms of major factories, things like that. I know we're recording this at a time when they just unstuck that huge ship in the Suez Canal that was blocking all the other ships for the past week. And we were hearing about all the impacts that it was going to have on all of us. For the insurance industry, we don't have to worry about events like that. I suppose there's perhaps an insurance payout tied to that, but it's really about data and algorithms. And so it's actually a perfect industry for our digital age. And insurers compete, quite frankly, on algorithms and to have the best algorithms. You need to have the best data and the cleanest data, et cetera. So within that context, I think of AI -- there are many different tentacles to it, of course, but I think of it primarily in terms of an 80-20 rule in that we're capturing a lot of information, or we could capture a lot of information that would be relevant to evaluating risk and exposure and be meaningful all throughout the insurance value chain. Yet most of the data that we're actually using is structured data that's captured on an application form or things like that, things that we can store in a traditional relational database. And we're really ignoring a lot of the unstructured data. And that could be images; it could be videos, that could be handwritten notes or hand-typed notes from a claims adjuster or a medical provider or things like that.  And so to me, AI, in a nutshell, is really unlocking that 80% of data that is important and could be highly relevant and really reshape or rethink the way that we think about risk but was really just too difficult to access before. And so it's going to lead to enhanced risk management.

And I mentioned OCR and NLP before, but think about, for instance, the term surgery. It's great that I can read the term surgery in a doctor's hand-written note, but I need the context. I need to know if that surgery is needed immediately; if physical therapy doesn't improve this condition, surgery may be required down the line, or surgery could be ruled out. This will heal without intervention. So just because I can read that term surgery, I still need to understand the context in which that was said. And that's going to make a big difference from a claims perspective and possibly even from a risk modeling standpoint and being able to, again, use that in rating and underwriting. So I could go on and on here, but I think it's really about unlocking that 80% of information that's available to us but that we weren't able to see. And oh, by the way, it also helps make our processes a lot more efficient and enables new products, new revenue streams. We're really bringing the expense floor down. And so we're making new products able to reach new market segments that, quite frankly, we weren't able to serve before because of the expense ratio. It just was too expensive to provide that new product or service. So it's definitely helping both on the top line and bottom line side.

DAVID: That's really compelling. And one of the more interesting, at least to me, things that you just mentioned is that insurers compete on algorithms. I've not heard that before, and it really dovetails well into the use of AI. So I'll take that as something to look into, actually, the idea that insurers compete on algorithms. That's a very insightful observation. And Paul, I wonder if you could talk a little bit about Microsoft artificial intelligence technologies and their impact on maybe insurers and perhaps financial services as a whole.  

PAUL: Sure, happy to, David. I'm just carrying on from your point about AI. So in the world of insurance, we have obviously this person called an actuary. So AI is the actuary's best friend. And as you said, the algorithms are king. It's what really differentiates, especially when you think about financial modeling and doing financial projections. And so a lot of that when you think about calculations as you were talking about is really on the shoulders of these actuaries. And so certainly things like artificial intelligence are great because that's where you can use artificial intelligence to support what they're giving as they’re thinking about their calculations, their assertions, and ultimately thinking about the financial projection. So at a super high level, when I think across the insurance disciplines, whether it be life insurance, to health, to property and casualty, to employee benefits, et cetera, I think the key areas I think I would call out is number one, artificial intelligence. We’ve talked about the data explosion. And also, what I will say in the data explosion is being able to bring data together from across departments. Now, of course, there’s advocacy and privacy there; the data being brought together there perhaps wasn't intended to. But with that in mind, you've got this growth in data. And so of course, I'll start with one of the applications of artificial intelligence is being able to drive meaningful insights, leveraging that data for different purposes, whether it be looking at insights around the customers, whether that be insights around thinking about the calculations that are being run on assertions.  

And that leads me to another big one when I think about insurance and the opportunity around artificial intelligence is things like anomaly detection. So if you get poor data in, you'll get poor results out, so looking at that, looking for anomalies detection, especially as you think about insurers working with huge, huge datasets and then obviously helping with decision-making because there's a lot of pressure in the world of insurance when you're doing things like financial calculations, rightly so. There are things like the peer review around the calculations being used to signing off the results that have been delivered because this is all about the solvency of the policies and the lines of business. And so that anomaly detection and decision-making is a big area. We've talked about how better to allow insurers to engage with the customers and learn about their customers and help make recommendations to the customers. So personalization is another key area where artificial intelligence can help using that information to be much more empowering and drive a much more compelling and engaging conversation with customers.  

And then I will also just throw out the -- we'll link it in the show notes. We've just released the Azure for Financial Services cloud to combine analytics and AI to identify new revenue streams for our customers. So go take a look at that. And I think that's lots of great collateral, great innovation that we’ve driven with the Microsoft Azure cloud tailoring it around insurance. And then finally, of course, fraud. Fraud is an important thing to mention, and so fighting fraud using AI, real-time remediation. And so we did, David, a previous show with Jamshed Patel about real-time data-driven decisions. And so I'd encourage the listeners here today to go there and listen a little bit more about looking at the data, driving decisions from the data, and that’s super interesting as you think about fraud, which is obviously point in mind for everyone.  

DAVID: Thanks, Paul. I appreciate that trip around various aspects of the industry and its applicability to AI. Rob, I want to ask you something that we ask a lot of the guests on the show: as a forward-looking person in your role out there in the industry, the most famous man in insurance, or that sort of take on the industry, what is a given technology that you think will make the biggest difference in the industry in the next 10 years?

ROB: That's a great question. So I'll give a boring answer, and then I'll give maybe a more intriguing answer for 10 to 20 years out. So in the next 10 years, it's actually cloud for all the reasons that Paul was just articulating. And I think there's a misperception out there that the insurance industry is really slow to adopt a technology where in fact, they were one of the early adopters of technology when it came to mainframe computers and some of the running things in batch processes. And so, during the 1970s and 1980s, they adopted these big mainframe systems. And that was a big revolution that again has been, I guess, forgotten or taken for granted. But the challenge with insurance is it's a financial instrument and a legal contract all rolled into one, and so upgrading systems is a big challenge. It's not just a rip the Band-Aid; it's not a move fast and break things type of approach. And so those, of course, became an albatross in certain ways that you have these large on-prem systems that are expensive to maintain that don't talk to other systems or if they do talk, you've got to be very intentional about that. And it's very expensive, and they tend to be very siloed. And so, how do you get to this future that we're talking about: the platform, the ecosystem approach, the partner network? There's probably a startup that has yet to exist that will be founded two years from now that will be a critical partner of yours in five years. And so when you work in that environment where we certainly didn't know the pandemic was going occur one year ago, and we don't know what lies ahead, agility and flexibility are just key traits that your organization has to have. And so, being able to move to the cloud and unlock all the benefits that doing so enables, I think, is really critical for companies. And so that's why my answer is cloud over the next 10 years. It unlocks so much of what we've talked about throughout the whole podcast.

For the 10 to 20 years, I'm really interested in blockchain and Distributed Ledger Technology, and obviously, non-fungible tokens are all the rage right now at this moment. And I won't pretend to really understand it, but as an avid baseball collector, card collector back when I was a child to now see a similar craze, but on the NFT side, I do think this idea of digitizing trust is critical. There are so many components to insurance that involve a lot of third parties that are not a party to the original contract. So it's an agent or broker, a carrier, and the policyholder, the insured that really forms the contract, those three parties. Yet, again, there are medical providers, there are body shops. There are all sorts of other people that get involved in the insurance transaction and knowing which information to share which not to share things like that. There are a lot of manual touchpoints, quite frankly today, that have to take place to verify and to be part of this. And so finding a way to get rid of all those manual touchpoints and digitize trust and leverage some type of DLT, I think, is quite interesting. And again, I think it's so early that the technology needs to mature some, but I think that's going to be the 10 to 20-year technology that's very interesting to me.  

DAVID: Thanks for that. And the case you make for agility and flexibility via the cloud as an immediate return and short-term future returns is really good news for us, of course. And we encourage people to take a look at Azure as an alternative there. With that, we're getting down to the end of our episode. And as always, I'll mention some of the things that we're going to put in show notes so that listeners can come back and engage more. And we'll have Rob's social info so you can follow him and learn more. And also, we'll link up to sites about your book, Rob. And we'll have links to Microsoft technologies that were mentioned throughout the show. And finally, as always, we'll have Paul's media there, social media, so that you guys can follow via the show notes. So with that, Paul, I appreciate your involvement in the show with a very different role that you played today. That was great. And to Rob, I just want to say thank you so much for being on the show. I really appreciated your perspective, and it's been a great conversation.  

ROB: David, Paul, it's been a pleasure. I really appreciate you having me on.  

PAUL: Thanks, David and Rob. Yeah, it was really fun. It was nice to wear a different hat today. Thank you, David.  

DAVID: Thank you for joining us for this episode of the Azure for Executives podcast. We love hearing from you. And if you have suggestions for topics, questions about issues discussed on the show, or other feedback, contact the show host, David Starr or Paul Maher, through the social media links included in the show notes for each episode. We look forward to hearing from you.