Deus ex machina with Niki Kouri-Maglaras from Prudential Financial

James BenhamOn this episode of the InsurTech Geek podcast, Deus Ex Machina with Niki Kouri-Maglaras from Prudential Financial. The InsurTech Geek podcast is all about technology that's transforming and disrupting the insurance world. We'll be interviewing guests and doing deep dives into specific tech we see changing the industry. We're taking you on a journey through insurance tech, so enjoy the ride and geek out. This episode of the Insurtech Geek Podcast is brought to you by Terra. Visit terra.insure to discover how Terra is changing insurance claims and policy management.

And we are back with another great episode. How's it going, Nikki? Great. How are you, James? Outstanding. It's a beautiful day. It's a warm day in Texas, but it's a sun is shining. The birds are flying there. Birds are chirping. The, you know, the breeze is blowing. Even though it's a 98 degree breeze, it's it's still blowing. I'm I'm actually gonna be in in New York City next week. I'm so excited. I'm gonna I I I got actually already got my tickets for my daughter and I to go see Great Gatsby.

I'm very excited. Very nice. Very New York. Yeah, very New York. So we, you know, we went back in March and saw a bunch of a bunch of shows and we're doing a quick a quick visit to see some more. So I'm super excited to be in your neck of the woods and and see some Broadway shows. How how have you been since our last episode?

Niki Kouri-MaglarasOh, my God. The world has changed, right?

James BenhamAlways does. Well,

Niki Kouri-Maglarasaccording to Moore's Law, every eighteen months, things are doubling. They're doubling in AI, and we'll talk about that. But definitely they have been exponentially growing. I've done some great travel. I've been in a few conferences. I think I bumped into you in one of those. But maybe the most exciting trip was the one I took two weeks ago. I went to China and we can talk about it in days, four cities, including Shenzhen, which is the Silicon Valley of China. And in the course of this session, I think we're going to talk a lot about my impressions.

I'm going to

James Benhamfeed that in our conversation. Excellent. Well, I'm so happy to hear that. So just for the listeners out there, if you want to hear our first interview with Nikki, go back to episode number one zero seven from 04/06/2023. It's been about a year and three months since, we had her on the show. So go back to that. That's episode one zero seven. You can hear about revamping the insurance value chain with data science. And we we did a whole background, and we talk about where she's from and what led her into this space.

We're not gonna cover that again. So I just want you if you to know, if wanna go listen to it, you can definitely go check it out on our website. That's insurtechgeek.com. In the meantime, let's do a quick reminder of everybody of what you do. You're chief digital officer of international business at Prudential Financial. And before that, you you're you're Greek, so you got a bachelor of science, in University of Athens, and then you got a master of science at Stanford University in management science and engineering.

Your bachelor's was in in science as well, a bachelor of science in electrical and computer engineering. And you got a master of science there too. So you're you're you're very technical, which I, as you know, really super appreciate. We can geek out at a very similar level, and I really appreciate that. And then, you know, for all the folks who are gonna listen to the show, I'll give a ten second background, or to Deloitte, then at Citi Private Bank, then at Citi Wealth Management, Citi Cards, Citi Cards, then then, you know, since 2018 now for the last six years, chief digital officer of international business at Prudential Financial.

So that's that's Nikki's background. Nikki, let's jump straight into the conversation. Our our listeners like to to get to business. When we spoke in April 2023, you predicted a major wave of innovation in the insurance industry over the next five years. If you look back on the last year and three months or so since we spoke to you, which innovations have exceeded your expectations

Niki Kouri-Maglarasand which areas still have some untapped potential? Yeah, let me take some time on this. It's a brilliant question. So AI, AI and AI, right? I would say the advancement in AI has exceeded my expectations and will continue to do so. First, there is a tidal wave of money going into this space. Second, our ability to compute has grown by 1,000,000,000 times in the last thirty years. We are a billion times more efficient. Our cars that we drive have not even become 10 times more efficient in the same time span.

Similar story on the size of the brains we train, we have exponentially larger brains. In 2018, the model size was 100,000,000 parameters, And now we handle 1,000,000,000,000 parameters. And we have exponentially more data. So we have a brain that is getting exponentially larger, which we can train with exponentially more data in exponentially faster computers. So things are happening, and they're happening fast. And the growth is real. I want to quote Bill Gates. Week, he said, Bloomberg, said, AI is not pets.com. I mean, no offense on pets.com, but Tech companies are putting tens of billions of dollars in re engineering their applications, and we're seeing a fundamental advance as important as any in the history of digital technologies.

So, what has pleasantly surprised me is how big companies like Morgan Stanley, Swiss Re, Vanguard, just to single out a few, have embraced AI. And in some cases they have slain some sacred couch, like giving their advisors guidance on their conversations with clients or creating chatbots that interact 100% with all customer requests, or using machine learning to manage active stock funds. Two Vanguard funds as an example, using machine learning in 2023 beat peer funds and exceeded benchmarks. And these are what I consider gutsy implementations. Now, what we're seeing in the insurance space is a lot of investments in talent, fixing the data in a way it can be consumed by AIs, and a full range of implementations from upgrading existing conversational AI chatbots to Gen AI all the way to underwriting innovation.

But I do think there's incredible untapped opportunity in individualizing the way we serve our customers. The product, the price, the service, the ongoing engagement, and the technology is here. I also think there's untapped opportunity to connecting the physical world with the digital. For example, and I'll talk about a startup that we saw in China, in Wanzhou. There's a startup there, and Elon Musk is talking about that as well, monitoring a person's sleep and compiling and sending valuable information from these brain waves to fulfillment, right? So connecting the digital with the physical.

So when these brain waves suggest that the person is like the heart rate is not normal or they're about to get into a seizure or not have a good night's sleep, there is aroma that is being infused in the room. The lights or the shades may go up and down. So that is lacking and it's a major area. And two more areas, robotics, I think is another area of untapped opportunity, where an analysis of a situation prompts a physical action. Autonomous cars, right, becoming mainstream, for example, that will take, I think, ten to twenty years.

And writing code, another untapped opportunity. So I told you I was going to talk about China. So we visited Tencent, which Tencent is one of the biggest companies in the world. It's a meta, a Google and a Netflix in one. We may know them here from the WeChat app. So Tencent, one of their co founders told us, is relying on AI for 25% of its code generation. So compare and contrast with how insurance companies are really very hesitant to dip their toe in such critical functions.

So think insurance, so all these things surprise me. What's going on in China? What I see in financial services? Definitely getting our talent and data in shape in insurance. I think we have a lot of velocity there. But I don't think what we've historically been doing as an industry, sit it out, see other people playing around with these things, then when it's all safe and secure, we'll go in. I don't think in this algorithmic economy where core functions like risk assessment, which is something we do very well, are being completely appended by AI, think I we need to be a little bit more gutsy.

That's a strong call.

James BenhamThat's a strong call to be more gutsy. Right? Like, there's a there's a lot of risk in being more gutsy. In in particular, when there are certain folks that can't fully explain how some of these things work. Right? And I so for me for me, the the risk in being gutsy is the black box fear. Now in writing code, I'll say this. I mean, coders are writing a lot less code right now, and they're doing a lot more engineering assembly. I still think and maybe this is, because I am legacy wise a coder.

I'm legacy wise a coder. You know, I started writing code when I was, like, 11 in school and, took a lot of computer science. We already before now mind you, AI is decades old. Right? Decades old. Absolutely. Yeah. This version of AI, LLMs, are mainstream now, but AI has been around for decades. I still think we'll have software engineers, but we'll largely be doing assembly work and direction more like a conductor of an orchestra than the individual violin player. Okay. And if you look at backlogs, development backlogs of every major insurance company in the planet, they're huge.

Like, the the the feature backlog and improvement backlog is massive. So there's, like, infinity demand on applications to respond to to needs. And so I think it's this is, again, not a replacement. It's Right. It's a it's a staff augmentation that allows us to hopefully get our backlogs under control on on requests. You know, it's a it's a really interesting, really interesting time. And I'll and I'll agree with your assessment that that AI and and LLMs far exceeded my expectations because what because I use Copilot and I use ChatGPT four o.

I installed the desktop app, the mobile app. I use it all the time. Like, I I use it constantly. I just went to Europe with my daughter. And when we had free time, I walked around every town I was in, and I I made ChatGPT my tour guide. And I said, I'm on this street in this town. Tell me about the street. Tell me about the town. Tell me what I'm looking at. And it knew it knew the history of the street and the buildings and the town.

And then when I would ask it questions and then, you know, now, thankfully, it cites references and gives me links. It does some really nice things where I can know it's not just, you know, hallucinating. I I don't I don't know. I mean, Rob, what do you think on this area? Like, as far as things that have exceeded your expectations on on on, technology this year, and what do you think still has untapped potential?

Rob GalbraithYeah. I I think, you know, just echoing what you guys are saying on AI and how it's been a a game changer, and I think everyone's still figuring out, right, the best way to kinda deploy it. I I've I think I mentioned this on the podcast before, but one of the things that I think is just a remarkable, moment that we're at is usually you have to make a trade off between better customer service and lower rates, right, lower expenses. You can have the Southwest Airlines model, right, or you can kinda have the the the super upscale airline.

And here, you could do both, right, in this moment, you know, by intelligently deploying AI and other technological solutions. It's like you can improve your customer service while at the same time reducing costs. And so I always encourage companies to really look for those moments. I think, as an industry that already struggles to pivot, and we've been talking about this for many years, just the pace of technological change is challenging us, right? Like we were already having a hard time keeping up or already trying to have a hard time getting out of the legacy world.

And so I think to the point where, you know, people have been able to integrate kinda some piecemeal solutions here, you've been able to kinda maybe, you know, have that kind of, you know, duct tape system that maybe looks okay from a front end perspective, but the back end, right, is really challenging to manage. I think the company has done a good job in terms of rolling out some features like chat functionality, some in terms of distribution models to take advantage of you know an offline online kind of, rather than truly going through, just agents or just a phone channel.

But, I think that back end guts, right, particularly claims is where I see it the most. I think it's been the biggest challenge and the profitability, right, that's been the main theme for the past two or three years. Hey, if it's not tied to a new product innovation or new distribution channel, innovation or sales channel, it's been difficult for a lot of companies to incorporate a lot of the new technology and it's just evolving faster than our ability to leverage it for its best use cases.

Niki Kouri-MaglarasYeah. And yet Insurtechs, right? Insurtechs and Fintechs are which historically and by design have been faster to implement some of these. The use cases in claims are astounding, right? How you can process in P and C definitely has a leg up versus life insurance. But when you can actually, with GenAI upload the pictures, right? And you can process straight through, you can process the entire claim based on that. I mean, are use cases. I don't know how mainstream they are, but definitely in SureTex. And the size of the price is definitely for us in these areas because this is our bread and butter, right?

The moment of truth is at claims, right? Especially for life, that's the moment of truth. And the underwriting is our core competency. So I think the question here is, we don't have to boil the ocean, we don't have to go for the shiny object. Leveraging, and I think that's another question, how do you prioritize, right? Like what do you do first? So there's so many vendors, there's so many use cases. So how do you prioritize? So I think you look at your strategic objectives, and it could be all of them.

It could be customer experience improvement and cost reduction and revenue growth, or it could be one of whatever it is, right? Line up those use cases to this, so that actually they follow your opportunities and your vision or your pain points, And it's not just experiment with everything. And then look at your core competencies and leverage those and make them shine and make them differentiated. Because if you're just following what everybody's doing, then you're not differentiated, right? So then it almost doesn't matter. I mean, you have to do it for hygiene, but how do you competitively differentiate?

So take your core competencies, whatever that is. And I do think in our industry, is about assessing risk. It is about processing claims. Everything else could and will maybe be disintermediated, right? With all these 10 companies and the affinity partnerships. So how do we, and the size of the price there is substantial for us. So how do you make improvements in risk assessment? How do you improve the moments of truth that you have with the customer? I think that's where I would put my money first.

Well,

James Benhamlet's let's jump into the phrase Deus Ex Machina, out of the machine god. Right? Or god out of the god out of the machine. Yeah. And, you know, you've spoken about AI as a modern deus ex machina Yes. And its role in serving human needs. Right? The at the end of the day, that is what we want AI to do is serve human needs. That's certainly and that's why I I went all in on using it so heavily personally as fast as I could. Yeah. You know?

And I I I have a car that has self driving capabilities, and so I use it as much as possible. Now there's definitely some failings, definitely some shortcomings, you definitely have to pay attention. Same with same with, all the LLMs and AI models that I use. Definitely some failings, I pay attention to them. But I think it's really important that you that you use it personally so you can understand what it is, you can use it, professionally. How do you think AI can be ethically and effectively integrated into insurance?

Right. Like, because it has got a benefit. It's got a benefit to the premium holders and the shareholders. Right? Like, it's got the premium, the policyholders. I mean, it's got a benefit. The policyholders and the shareholders both have to receive benefit. And and you also have to do this ethically so we don't end up in another situation, where you you have some really baked in bias like there was with credit scores. You know, like, there's some really big issues around credit scoring for for for rating policies around the area of bias.

And so ethics really do matter. How we get there matters. So how do you think AI can be ethically and effectively integrated?

Niki Kouri-MaglarasYeah. So let me just first say that there's ex machina, which is exactly right, God via the machine is an aspiration, dates 3,000 years ago. Another phrase that you know, conveys a similar message is tech for good. So we opened Pandora's box and now we have to use it in a way that I want to manage it. I think an easy use case of how that will happen is in medicine. I think undoubtedly they're democratizing medical advice for the poorer and also for the richer because it will combine multiple diagnosis and vital signs and procure the best possible medical plan.

I had the amazing opportunity to meet Eric Jinkx, the CEO of Ant Group. Ant Group is the officer of Alibaba and Alipay when I was in Wanzhou in China last month. And his vision is that of your own private doctor. Now this is the company that have already experimented early days with a mutual risk sharing hospital indemnity insurance. Basically, critical illness insurance to 100,000,000 customers. So it's a mutual risk sharing app where they basically, it's Exante versus Expos pricing. So they do not collect premiums Exante from its members, instead they equally allocate the aggregate indemnity payouts.

It's an interesting model, but they also apply artificial intelligence to process claims, standardized claims procedure, applied textual and graphic analysis in evaluating claim materials. So definitely there is innovation. And then in medicine, I just brought it closer to insurance and of course in medicine, I think in all aspects of medicine, this will be revolutionized. So there is a way to make it undoubtedly good for humanity. In the insurance industry, the people that most need insurance are the ones that can at least afford it. I mean, that's my provocative statement.

I believe AI will help individualize the risk pool and assign pricing that's fit for purpose without sacrificing profitability to your point, yet allowing poor people to participate. For example, and this is a research done by the Columbia Business School, in a down market, wealthier people can afford and will pay for higher premiums, while poorer people will be able to participate with lower premiums. In other words, price optimization at scale will benefit both the company and the policy holders. Now, to your point, there's a lot of talk about biases being propagated via AI, and that is possible.

An AI based system is going to be successful only to the extent that there are no better implementations around. And to your earlier point, will it take over, there will not be programmers. Just because you do an AI implementation doesn't mean you're done, right? Is yours as good as the next ones? Is it more fair, right? Is it better? So there will be the people and the talent needed to make sure. Standard quantitative processes use statistical techniques to identify correlations. But you still need to go in and think carefully about where these correlations come from, and examine all the data in a deeper way, and use all the data you can in the best possible way.

So having the data science talent that can do that is extremely critical. The other thing about eliminating bias, if you will, or at least trying to make it more manageable is regulation. And already it's playing an important part. Because consumer data is needed, a lot of consumer data is needed to produce AI modeling, regulators have already started taking notice. Last October, US CFPB, the US Consumer Financial Protection Bureau, proposed the Personal Financial Data Rights Rule. This will shift financial service providers to open banking. You probably have heard of open banking.

Open banking will grant new protections to consumers. These protections will forbid financial institutions from hoarding a person's data and require companies to other customers request shared data without companies offering better products. So, a combination of data science, human in the loop, removing those biases that are inherent to the data because we produce the data, so it's full of our biases. Data science talent, I think is critical and human in the loop review of all these models. And I think regulators, I think regulators will be happy to hear me say that the business sometimes doesn't take their side, but I do think regulation and especially big tech companies is needed and will play a critical role.

James BenhamWell, regulators can never truly keep pace with the pace of innovation. I can tell you as a former city councilman, a former planning and zoning commissioner, and a current state official in Texas, I can tell you it is very difficult, in the seat of government to keep pace with with change because the democratic process, the way the Greeks invented it. I'll just give you I'll give you I'll give you the credit, and I love that. I love it. I love that a Greek brings up Pandora as well.

So I'm just gonna say it. Democrats. Right? Anyway, sorry. So it's from demos. Sorry. Okay. It it it's

Niki Kouri-Maglarasthink you've watched my big fat Greek wedding.

James BenhamPut some put some Windex on it. This is from the Greek word demos and gratin, meaning Greek. Sorry. Okay. You know, it's an it's it's naturally designed to be slow. It's naturally designed to an an efficient effect an efficient government's very frightening because efficient governments don't don't weigh in on on all the needs of all people. And so I'll say I'm okay with policy and regulations lagging behind innovation. And we've had I've had some conversations with regulators that were at some of my speeches and asked me what they should do around AI.

And I said, Observe. And let let your let your let your your let your rule making follow the innovation, not lead it. It can be very, very dangerous to try and get ahead of technology and and rule making. So democracy is naturally slow, and it's okay for it to be slow because it weighs in all the feedback of everybody involved. And so I'll say that first. Mhmm. That that's that's really that's really important that we we not get too aggressive with wanting rulemaking. Although I do believe that capital markets, and I'm a hardcore capitalist, operate most efficiently when there is a healthy minimal framework around them to operate in.

It shouldn't free for alls rarely go well.

Niki Kouri-MaglarasTech companies, you're right. So it's regulation and companies, right? In a capitalist environment and where the innovation is right now happening, right? There needs to be ethics in the way our tech companies, which pretty much right now possess a lot of the power towards creating those AIs and they're making billions of dollar investments, things we've seen in the past only governments being able to do, right? They were the only ones able in the past to fund innovation in this country, especially after the war or just before the war and after the second world war.

So now it's the companies that are making these huge investments. And I do think that we're entering an era where maybe with minimal framework, maybe a little bit tighter. There's a big responsibility for this company. I think there's a big responsibility for academic institutions as well that are bringing up the next wave of leaders, our Gen Zers and our Gen Alphas. And I think our education this very changing world also needs to be something ingrained in our collective psyche. Absolutely.

Rob GalbraithYeah. No. I I I'm actually fully with you, James and Nikki, in terms of you could be stifling, right, positive change, positive growth. And Nikki, you just talked about, you know, being able to offer insurance products to the most vulnerable in our society, you know, whether it's in our country or or worldwide. And so, you if you try to get very restrictive and kind of how you can leverage technologies like AI and others before you even are able to say, well, does that bring down the price floor or remove some barriers that have presently been in there that makes it difficult to offer insurance.

One of the reasons, you know, micro insurance has been a success story but yet it hasn't really scaled in the way that we'd love to see it worldwide because there are so many challenges with offering low cost products to so many people, right? You need technologies, you need efficiencies and able to to to to do so. And, you know, we've kinda hit a a a barrier there as I understand it. And so now with the leverage of new technologies, there may be ways to overcome that.

You know, the the role climate change, we're talking about tropical storms coming up, right, and the cat five in June now. And so, you know, the Florida market and part of that was regulatory. Right? And so there's been some cleanup there, but there's a lot of challenges we're seeing in terms of availability and affordability. Well, maybe new technologies. You know, Nikki, you talked about better risk assessment tools that are out there, you can Mhmm. Can change that. So, absolutely, I I think, you know, you would want not wanna, have anything be stillborn, right, as a regulator.

And, yes, there's gonna be some negative outcomes. You mentioned, James, you know, with autopilot and Tesla. Right? It doesn't always work exactly the way that people thought it was and probably all the stuff that the folks at Tesla never even dreamed about. Right? People falling asleep in their car, letting it drive by themselves, stuff like that. So Who who

James Benhamwould ever do that?

Rob GalbraithSo I I and I totally agree too. You can't have a free for all. You have to have that minimum framework. Like, you can't have a vacuum. Right? There needs to be some boundaries, some rules in place so that people kind of know, right, where this basin can innovate within that. And there's been a lot of talk among regulators the last five or ten years about a regulatory sandbox. Right? Well, let's go try this area, try it out, test it out. And so I definitely think kind of public private partnerships and having that space, to allow innovation, and figuring out, you know, the minimum amount of rules that allow people to go forward with these significant investments that they're making, right, without, stifling growth but at the same time evolving over time and regulators will never be at the leading edge of innovation.

They just can't. There's too much to tackle. We've spoken to regulators in the past on this podcast so Nor should they understand those challenges. Yeah. I just don't who they should. Yeah. They don't wanna be. They don't wanna be for the most part anyway. So So so, Nikki, let's wrap up with this question.

James BenhamYeah. In a recent LinkedIn post, you mentioned there is so much information about new technologies that it's sometimes hard to prioritize our next move. This is something I hear a lot is that it's almost like paralysis by analysis. People are paralyzed by by how much information, the tidal wave of info, the tidal wave of change. So how can insurance companies effectively prioritize tech advancements so that they can stay ahead, but also so they can pick the right thing to work on at the right time?

Niki Kouri-MaglarasYeah, yeah. Think decking the technology against a real business problem, I think I mentioned that briefly earlier. Companies need to be very clear on which advancements will give them competitive advantage and leverage those core competencies they already have. You cannot be everything to all of these peep to to all people and you cannot experiment with every possible use case out there. So in a cost efficiency

James BenhamYou can try to. I mean, Microsoft's doing it right now with AI. They're baking Copilot. Their strategy is put it in everything and see what sticks. But none of us can afford the processor time to do that. Exactly.

Niki Kouri-MaglarasExactly. I mean, we're not talking about the Googles and the Microsofts right now. We're talking about how we'll be consuming these technologies. And of course, they're making bets and the way they're making bets is let's do something of value, and then the profits will come, so to speak, And they're throwing billions of dollars. So we cannot afford to do that. So if cost efficiency is a priority, then contact centers and overall service, right, is low hanging fruit. We mentioned that in terms of automation and Gen AI.

Now, if revenue growth is the primary target, definitely turbo charging the agents reach through personable social media campaigns, product recommendations, personable AI generated upselling are things to look at. And even something, you know, the one thing to start from, it's all these knowledge bots. But I wouldn't just put a knowledge bot there and say, hey, use it. I mean, personal productivity, as you mentioned James, in your daily life is amazing, But where we're going to get the biggest bang for the buck is if they're integrated within our desktop.

Right? If they're integrated in your workflow. If it's like you're listening to the call, let's say, we have a hybrid digital agency desktop in Latin America, right? And our next thing is, okay, so now you have this remote selling going on. The sentiment analysis, right? And these are easy implementations, but they are disproportionately effective because they are already integrated in the workflow. So when it comes to core strengths of license assurance, and this is very near and dear to my heart, is the abandoned history of what passes or fails under writing.

Nobody has that data. So let's talk about a unique core competency of insurance carriers is we have a unique mix of historical data, health indicators, medical histories like blood tests, like who has that? And from financial services company, right? And we know what constitutes a favorable insurance customer. So the trick here, and I think there is where I would spend and make an investment in a bet as an insurance carrier is getting all this data in tip top shape to produce AIs. Producing AIs and Jensen Wang said that the CEO of Nvidia is basically we're producing intelligence.

I mean, a cool thing, right? Your product is intelligence. So commercial, put it in the abstract level of all this intelligence to either sell something or service something, And commercialize this intelligence to further our customer reach. And I think that should be at the top of my list.

Rob GalbraithNow, Nikki, I love what you're saying about the core competencies because I think about some of the Insurtechs that felt like, hey, we're gonna do insurance better than insurance companies because we, you know, have superior technology. Well, where did they fail? You know, distribution was a challenge a lot, started to go direct and then realized, no, we need to pivot to independent agents. And a lot of the ones I talked to, 90% or more of their business was actually coming through the agent channel rather than direct because you've got to spend so much marketing, you've got to outspend the Geikos and the Progressives and the Safe Farms of the world, right, to just kind of get that customer acquisition cost was just so high.

The underwriting part, right, that was super critical. So we saw these challenges with profitability. They didn't know what the proper risk selection was looking like and they were constantly having to change their guidelines, change their pricing. And then finally claims, right? And the difficulty of claims, the negative customer experience that may go along with denying a claim or investigating a claim, right? That everyone's got to do. There's obviously a lot of legal and regulatory requirements along that. So all those are core insurance competencies. And so I think what we've kind of ultimately found is that insurance companies are still best at doing insurance.

What they need to do is improve the customer experience and efficiencies through the leveraging technology and there's a lot of partners obviously out there to be able to do that. I do still think it's good to have a kind of competitive threat always from the outside to make us motivated, re examine the way that we're doing things but ultimately I think what we've seen is that insurance companies are still highly relevant And so it touches back to your emphasis on core competencies. How do you take what you do well and make it better?

Yeah,

Niki Kouri-Maglarasabsolutely. Absolutely.

James BenhamYeah. I think the the mainline insurance companies, I said they're usually good at making a profit and providing insurance. When when the when the entire industry has a over 100 combined loss ratio in certain segments like property, you go, man, maybe we all miscalculated. But, know, it's certainly it's an art and a science to make money, not getting put out of business. So it's sure.

Niki Kouri-MaglarasSomething I heard from somebody about insurance, I had never heard of that. I can't remember exactly who it was, but it stuck with me. We said, well, the insurance business, if you think about the customers, this is motivated by love. Like our customers are buying insurance out of love, right? For life insurance. So basically they want to protect their family. And I thought this is, I mean, and I've worked in every and you said that in the beginning, I've worked in every possible retail financial services product, started with the private bank, there was in brokerage, then I was in the consumer bank, then I was in cards.

I mean, the only thing I had not sold to an individual was insurance. And then I joined Prudential, and I've done that too. So I can tell you from all the lines of business in consumer banking and lending and investments and insurance, this is an industry that, and maybe I'll sound Pollyanna, but means well, right? It's trying to do the right thing. It's not trying to make money from the people that cannot afford it, right? And lending, you know, that's some lenders, I'm not saying all lenders, right?

It's not like harassing you with fees every time you use another ATM. I mean, it actually is trying to pull people in risk pools that make sense so that we also not lose our shirts over it, but really is willing, is promising to cover your loss when you need it, right? So I want to say it's an honorable vision servicing the insurance. I feel honored to service the insurance industry as opposed to other financial services. And as I said, our customers come out of an act of love to buy this product.

So I would say making money is one thing, doing the right thing for the customer is what will lead you to that regardless. So one of the CEOs, and I wanna call with that because, I mean, China may and the Chinese CEOs made a big impression. Geopolitical differences notwithstanding, this guy, Eric Jing, who is the Ant Group CEO, he made a statement, I wrote it down, I'm trying to find it, about how to lead. And he said, I'm striving to deliver something of value, and then the profits usually come.

So I do think with AI, we can take what is fundamentally something of value that we strive to do in insurance every single day and turbocharge it.

James BenhamI like that. Take it and turbocharge it. That's how that's certainly how I feel. And it's it's really what it's turned into for me. It's a giant turbocharger for my productivity and for for my people too. Rob, any any closing comments? No. I I think this has been a a fantastic conversation, and it's

Rob Galbraithit's challenging. Right? Obviously, the world keeps going faster and faster. There's so many different dynamics. You mentioned geopolitical, Nikki, and the technology, the business side, the economic side, healthcare side, etcetera. So it's always going to be a challenge. It's never going to be perfect. But on the other hand, that is kind of what I think let leaders like Nikki thrive right in this world of trying to shape her organization and other leaders out there, right? Towards positioning you for long term success in this, nobody's got all the answers and so it is through networking, through conversations like that, listening.

Hopefully our listeners out there get the value out of our podcast by staying on top of what these trends are, listening for the experience of others and giving a lot of meaningful thought strategically and that's the key part I'm taking away from our conversation, Nikki. You don't have the time or the resources to chase everything and so you really have to kind of fall back on what are our core competencies, what are our strategic objectives and think about leveraging technology in those terms.

Niki Kouri-MaglarasPrecisely.

James BenhamAwesome. Well, thank you for the conversation as always. It's been great. Enjoyed it thoroughly and thank you out there, all our listeners out in listener land. Nikki, can't wait to see you soon. Yep. See you. And Thank you, guys. Rob, always great to have you on the show.

Rob GalbraithYep. Always fantastic, James. Thanks for the conversation. Thanks, Nikki, for being a guest on our show again. And thank you for tuning in today to geek out our interview with Nikki Curry Magalaras

James Benhamfrom Prudential Financial. Thanks. See you next time. The Insurtech Geek podcast is all about technology that's transforming and disrupting the insurance world. I've been your host, James Benham. That's jamesbenham.com with co host Rob Galbraith at endofinsurance.com. We're taking you on a journey through insurance tech, so enjoy the ride and geek out.