The Evolution of Insurtech Leadership in the AI and Cloud Era

hey Dave thank you so much for joining us uh Nelson good to see you thank you yeah um well today I love to get your thoughts and insights um you know about the modernization of the insurance Tech stack in the life and annuities industry first first of all um you know for those in the audience who may not be super familiar with your past roles I think uh it would be super helpful so give us a quick intro of your background U which I think is super powerful and impressive well I appreciate that um I have uh had many interesting business career functions along the way and also two startups and I really think that sort of defines my experience because when you've worked in very small companies as you know uh growing a business is super interesting it's challenging uh but you uh you developed some really really good skills and if you could take sort of that Innovation and bring that into a large company environment which I did later in my career um that tends to give you deeper insights and a little bit more in the way of skills I think to help navigate and move a little bit faster uh I ran a couple of businesses for my former Company New York Life in the day and in my last eight years in the company I ran technology uh for the entire Enterprise and coming from the business side Nelson having this entrepreneurial background I was able to uh I think do a reasonably good job connecting the business problems to technology and Technology to the business problems I always felt like there wasn't the strong enough association between the two groups to make real meaningful impact and to have that come together at a New York Life was really a nice way to cap off my career at least in the corporate side and then as you know I joined Brewer Lane Ventures as an operating partner two and a half years ago and uh have really really enjoyed getting back to the entrepreneurial side learning about businesses and helping them grow and develop yeah that's such an impressive career Dave that I think entrepreneurs and you know corporate Zs are are are lucky to work with you so in your Journey running you know kind of both Tech and the connection between Tech and business that you mentioned is so important what have you seen as some of the biggest challenges or obstacles you've seen in trying to modernize the technology stack as we quickly go into the clab and into the age of AI yeah so I mean again that starts with connecting to the business because why are you modernizing uh what are the business outcomes you think you should get once you've gone through the modernization Journey exactly what does modernization mean is it a full stack modernization are you modernizing the front end and you're going to live with some of the you know the more Legacy environments in the back end are you going to do full stack and what are the reasons behind that and then what is the sequencing to actually do that because you're talking about a multi-year journey here to accomplish that in an effective fashion and again making sure that all parts of the business are connected to that discussion those decisions and that Journey becomes critically important uh because it's difficult now I would say about modernization in general um it's going to be expensive it's going to be time consuming it but one of the things that really most or organizations are facing is retirement risk you have people who built these systems 30 35 40 years ago you don't really have the documentation that you would have today in you know your development cycles that you're going through Nelson and so understanding how am I actually going to take this monolith down that's a tricky proposition are there any conceptions that you have ever run across when it comes to like you said how to take this down and move to the next gen of tech technology well the misconceptions could be let's start on the business side the business side might might conclude uh something like well how difficult is this really just get it done you know don't don't tell me about all the details just make it happen and to again to take people through not the not the NS detail of every sort of thing you need to do in modernization but deep enough to get the business to appreciate the complexity uh the timeline that's going to take the care that's required you know as I always said if you start pulling wires you might not get the right outcome in the end and so some sensitizing the business to actually what's going to happen here is is critically important equally important on the tech side is to make sure that there are very very good Keen listening techniques going on so that we understand exactly what the business requirements are you know for for decades Nelson you heard this story the tech people would say uh the business has not given me good requirements the business would say Tech really doesn't move fast enough they're not really yeah they're not into my needs they don't really understand what I'm trying to achieve that communication gap is job number one you have to fill that so on that note you know job number one skill set seems like great communication with the bridge between engineering or Tech in general in business right do you feel like the skill set and prior prioritization of skill sets for a tech leader at an insurance carers today is fundamentally different from say 20 or 30 years ago are the skill sets similar totally different in between oh I think they're a lot different Nelson uh I'll start with the fact that 20 years ago just about every action within a tech uh ecosystem was a um we're going to do it ourselves we're going to build it we're going to own it we're going to operate I mean you may buy software of course but you're going to highly configure that soft software and you're going to own everything from compute to development and maintenance okay that was the old model and Cloud wasn't well I just going to say that there was no AWS there was no Azure there was no Google so compute was something you would own and operate and I kind of um the example I would use this is not different than how Public Utilities that provide power sources to businesses came about in the 30s and the 40s and the 50s which was every Factory in the US had its own power generation facility you can see it all through New England these mil towns built on rivers with their own power generation ah and you know everything was decentralized and then all of a sudden the public utility came along and said why are you creating power it's a commodity we can do it faster cheaper and distribute it much more efficiently that's an amazing perspective I think so many of us forgot and take for granted that Public Utilities is just a given today I think many of us forgot that wasn't always a thing and and then factories like you said were able to realize maybe we're not in the business of generating electricity we're in the business of making other things Factory well so AWS and Azure Microsoft's Azure those are the new Public Utilities for compute uh I suspect AI is going to have a public utility aspect of it as well it's not to say that vertical AI won't be a thing it will but you're going to be tapping into large sources of compute and you're going to be tapping into lots of data and those will be the next Generation Public Utilities beyond what we what we see today do you think SAS applications who themselves are also on cloud compute will be also a trend of the future in that less companies insurance companies will build and host their own code and instead in certain cases use a third party SAS service yeah here's the trick um many organizations and I I think this is certainly true in insurance they have come to believe that what they do is extremely unique when it's not um I give you an example that underwriting is a commodity risk analysis is unique to the business what do I mean by that underwriting is just a system to take in various information factors and come up with a score low risk to high risk the insurance company gets to decide from there what level of risk they're comfortable with some organizations are more comfortable with more risk others less data is the data and I think that actually lends itself to a public utility model the engine behind underwriting is a public utility model right the data the data and the use of the data is a private utility model that's something I'm going to hang on to and and slowly but importantly it's happening organizations are beginning to realize it's costly to maintain everything myself um every time there's a change it cost me more money to to you know work through the maintenance aspects of this sort of thing and it's table stakes and so I need to understand what my true IP is my true identity and my true destiny data and I need to hang very tightly onto that and I've got to release everything else it's it almost sounds like you know the golden path to building a good startup even right although we're talking about very large insurance companies but you know how in Tech startups they say build your unique differentiator and try to Outsource everything else I mean obviously we don't take that to an extreme in an Enterprise but sounds like that's what we're kind of saying when it comes to deciding what to potentially take outside and treat as a commodity and what to actually build as proprietary right and not everything is proprietary is what I'm hearing exactly exactly you know I I give you another really easy example paying paying a claim is a commodity I agree yeah I mean and but it's expensive you have call centers associated with it you have multiple platforms but here's the trick this is no different in than banking but insurance companies uh over the last 40 years they have built built their systems on products not clients so every system had a product associated with it and they were product Centric organizations to create a different customer experience and to say no I wanted more customer Centric model those multiple systems have to come together as one because those systems don't talk easily to each other and we've threaded that together or tried to do that with middleware and so on and so forth but what have we done we've just occurred another software cost it's not as elegant as it needs to be it's certainly not fast and so as you modernize what people are beginning to do is to say I got to rethink the architecture again this is what I was talking about earlier what is the aim well the aim is I want a better customer experience I want to easily pay a claim and and not frustrate the policy holder or the deceased the beneficiary in this case I want to be able to cross sell more product into my client base well guess what that means you have to have client Centric systems not product Centric systems so this points back to your original question modernization is really super important and it sounds like the skill set to a to be success successful at that today really is not about tying everything that is product specific but tying all the different product systems into a universal layer of experience so that the stakeholders like agents and consumers many times most of them are non-engineers can benefit from a more client Centric experience right yeah exactly now we're at a very interesting place we started to talk a little bit about generative AI uh I think the most immediate use case for generative AI is is in coding as a co-pilot I agree helping helping Engineers like yourself code faster standardized documentation and in my experience documentation is hit or miss some people are good at it some are some are not so good at it so a consistent standard around documentation and then the ability to go in and reverse engineer so we started talking about mainframes that were you know platforms that were de developed 40 45 years ago with no documentation the ability for those algorithms to go in and understand how those systems are operating to then create the code documentation that enables you to decommission to modernize I think that is a huge relief that has come our way I love hearing these super practical use cases in the Enterprise that people can actually benefit from because I hold um a belief that some of the most important use cases of generative AI may not be recognizable or or even brought to the level of awareness for consumers right something you just said that that is like a GameChanger but most consumers won't Rec won't realize that's actually happening right it won't be as apparent as say someone um you know creating an image from scratch or text prompts yeah exactly and I and a I I don't know if it was Microsoft but I think it was them I love the phrase co-pilot uh because really what you have is a very powerful set of tools as an engineer to apply to either difficult tasks or tasks that require an awful lot of time and attention they can be mundane tasks uh let's take cyber security as an example for a moment here wouldn't it be be nice to have an engine sitting on top watching all nefarious activity in addition to people you're less likely to miss some some bad behavior some infiltration attempted infiltration you can certainly do it 24 hours a day seven days a week the comput compute doesn't get tired human beings do but as human beings we're just not only we get tired but we get inundated with information we're going to miss things along the way and by the way the people who are the frauders are also getting more sophisticated off the use of these tools and so that arms race we have to keep up with as a business to sort of stay above it as well so there's I think there's some very very good practical use cases for AI um that are front and center of what we need to be doing today I totally agree with you um and speaking of AI you you both as a former Tech leader and also now as a venture capital investor I think another topic on AI um that's on everyone's mind is though generative AI I think there's consensus that it can be a game changer there's also a ton of noise right yeah yeah there's a ton of noise and many companies of all sorts and flavors claim to be generative AI companies what do you think is the best way for a large company to tell what is noise and what is act useful you're right about this um I think everybody and anybody who had a business plan two years ago who didn't include AI as a prominent feature has now made it front and center so it's it's become a lot of noise a lot of uh marketing nonsense and that's clouding the picture in some ways in terms of real AI but here's what I'd say about a business uh first and foremost businesses need to develop a culture of AI and AI usage in other words you need every single person in the company playing with AI on Small Things uh is there a way to write this email better uh I want to write a white paper and I want to put all my inputs in and I want that white paper to be 10 pages long and I want to turn that into a PowerPoint presentation those are all practical and what I'll call nonthreatening uses of AI I'm not putting personally identifiable information in there I'm not putting the corporate secrets in there I'm not putting the corporate strategy in there give people though the opportunity of learning and developing and seeing the power of these various co-pilots that's that's sort of job number one job number two is a business what are you trying to solve for what's your mission how's that mission going to change what's your vision for where you want to go as a business and then and only then say where might AI play a role in helping us achieve this um you not have access to all the information in the world combine that with your data how might I use that for you know position of power decision-making Point number three what is okay in the public domain data what is my destiny data my real IP that I need to preserve and how am I going to use those models and how am I going to govern it and so corporate governance around AI has to take a very very strong form over this important data and then job number four is to begin the implementation process what's happening in the market Nelson is everybody's getting into the implement ation they're getting into the art of the possible all very well and good but they they ignore the first three steps I talked about which are three critical steps especially when everyone is claiming to be an a company but not everyone has a true Ai and an engineering Centric culture right exactly and you you asked the question how do companies identify what is real and what's not so real what is what is myth in sort of Market versus you know in fluff versus something sub you know substantive well if you have a culture of AI you've allowed your management group and others to to begin to play with it you've identified your problems and you've got your governance you are a well-formed organization knowledgeable organization around AI that you'll be able to see very clearly what's real and what's not that is a great Point um the culture of AI kind of needs to develop on both sides right that's right and you know you you when we talk about culture and being so Ai and AI in my mind is is a very engineering heavy Endeavor right um there is a ton of hype and marketing around it which is all in good we want we want more awareness it's very engineering heavy um a lot of times you know obviously I'm I'm super biased because I'm a technology startup founder a lot of times it seems to me that it is just structurally easier and faster for you know new Challenger Brands um to instill this AI culture if they are born and built in the age of AI and Cloud native technology um but we sometimes see you know uh the industry fall into the cycle of they want AI they want clown native they want a bunch of new technology you know containerized microservices but the companies who sometimes do these things the best or at least very well are not the established companies from 40 50 years ago so you have this dilemma where I want to go to the big and safe choice but that may not necessarily aligned with what I'm seeing that's best in the market so my last question for you is how do large ORS deal with that they see an amazing group of startups with this amazing product set I want but my familiar you know set of companies give me kind of that sense of security you uh you asked this question on the front end it's a really really good one you're really getting to the heart of how to actually how these organizations innovate and then you asked the question earlier about what's the role of the CIO how's it changed in the last 20 years I believe very strongly that cios and business leaders will pick a few of the emerging companies that are actually really good at providing fast moving technology gamechanging technology and more strongly partner with those firms here's my example of that uh I see a day not too distant future here where employees of early stage companies will be embedded into to these larger entities is part of their Innovation group strong form partnership where you've got multiple benefits you're going to get the intelligence and the new technology of these startups and you're also going to bring that into the Legacy organization and you're going to cross-pollinate the Engineering Group Within These established organizations they're going to learn more they're going to develop quicker you're going to actually have a seat at the table with these large entities to help teach them and develop the sort of things that you take for granted uh I see a lot more co-investing that will occur where large entities will co-invest in early stage companies take an equity stake that's a hard form of partnership that you know is different than the loose form partnership but if you're um if you're a business leader and you're CIO you've got to be able to look at these uh smaller entities and say which ones do I believe in which teams can I get behind which ones have enough traction for me to get comfortable with and you're going to have to have a different business analysis lens going on there to make those decisions in an effective fashion as well but again that's not something you had to think about 20 years ago as a CIO or a business leader I was just going to say that RS to that earlier question the same Tech leader in the 80s 990s probably not only didn't have to it probably wasn't in the realm of like priorities they have to even be brought to awareness right yeah yeah exactly um I know I promise you that was my last question but you brought up such a good point I'm gonna have a real last question for you Dave all right I'd apologize for doing this um but I can't miss this you mentioned there are things that a new technology company take for granted but that could be potentially actually very valuable for a larger Enterprise in Insurance what is something you think new tech companies take for granted that is valuable to Enterprise um I think it's very difficult I mean take take you as an example every day you're on the Forefront of developing new products and new skills that these companies can tap into and you're going super fast you're hiring really great Engineers who have a lot of interesting experience and your work ethic your drive and your Leading Edge thinking about what's next uh it's just what you do and so really appreciating that is hard to do when you're in the middle of and I'm telling you that every large organization could benefit greatly by having some exposure drinking some of that water that you drink as you know your normal sustenance every day as part of their system it um it's really hard to separate yourself from that until you've actually worked in a large entity and then worked in a small entity to really sort of appreciate the differences yeah um I'm obviously super bias being you know a Channel or brand technology company but um you're right sometimes we're just in the middle of it every day and we don't necessarily think of our day you know in that fashion but um you know it's always good for I think folks on the tech startup side of the world to understand you know what are what are the tangent benefits that that their customers May value um Dave I know we're on the top of the hour it's such a pleasure to have you I think I feel like we've we've got so many good nuggets um by picking your brain today um I might just have to invite you back for another episode or two in the future well it would be my pleasure I really appreciate you inviting me to do this I had a lot of fun today thank you so much stve

2024-03-02 03:53

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