Think Slow, Execute Fast: The New Playbook for Vertical AI Transformation in Insurance | Kristoffer Lundberg

When Allianz does their annual risk survey and they measure what are the risks facing businesses, AI went from number 10 on the list to 2, so second highest, just behind Cyber, the biggest jump. And he is foreseeing that this is something which the industry needs to lean into more. Hello, my name is Juan de Castro and you're listening to Making Risk Flow. Every episode I sit down with my industry leading guests to demystify digital risk flows, share practical knowledge and help you use them to unlock scalability in commercial insurance. Welcome to a special live episode of Making Risk Flow. It's a very special one because we are recording this one from InsurTech Insights in New York and we are just wrapping up this conference, which has been a phenomenal conference, and I thought it was a really good opportunity to discuss reflections on the conference, what we've learned and what are we looking forward to. So, first of all, join me in welcoming Chris Landberg, CEO of Insured Fake Insights. Thank you for having me here, but also welcome to you for coming to the conference. We're very pleased to have you here and happy that you decided to host the podcast here. Hope you've had a lot of good conversations. So, no, it's been a really good show over the past two days. We've been a bit overwhelmed by the industry this year, I would say, given the AI craze that's going on. And having OpenAI and anthropic speaking on stage is just. I think we have about 20% more registrants this year, so it's good. And we are excited for this conversation as well. In terms of learning more about what you're also doing with Zytora. Well, going for sure. Congratulations. Yes, yes, I said it's a fantastic event to really bring together the insurers, brokers, the startups, the technology providers, the capital providers and bringing them all together into the room. So I think that works extremely well. You've been running this for, I think you said, seven years now. Yeah. So let's start with just like a brief reflection of how has it changed from back in 2018, 2018, when we did the first one and we didn't start Insurance Insights with the ambition for it to be what it is today. It was back in 2018, you had like this wave of intro tech coming to the scene where a lot of people came in and said, you know, technology can help the insurance industry in so many different ways. And we just thought, well, we need a forum to get everyone together. We want to hear from the incumbents about what are the problems that they're facing? So it was very much also just a conference to learn and, like, get the feedback back to the tech people, but then also a platform for the technology companies to come and use that platform to say, well, what can they do? And I think over the years, we've seen obviously, like a lot of iterations of intratech evolving, but this year is the year that I found most exciting. I think it's moving now at a pace that's so different. The conversations that I'm having on the stages with the carriers and insurers are just much more progressive than they were back then. And I mean, I remember we had the likes of, you know, I think Hippo was at our first conference in 2018, just when they were starting off. So, like, you had all the challenger insurers in the first couple of years. And then I feel in the past couple of years you've really seen the bigger, like, New York life is here. Like, just speaking with MassMutual John Hancock, like, more the bigger incumbents who have Century Legacy, they're now coming to the conference. They're now asking, like, what do we need to do? I think they're waking up. They're realizing that, wait, there's something brewing right now that we need to work with Will. And so it's been a big evolution since we started. If I reflect back in 2018, I'm sure we'll talk about AI in just a second. But the single thing that I think has felt very different, especially DC, I mean, in the last few years compared to 2018, is 2018 was all about disruption. It's like new entrants wanting to displace the incumbents. I think that conversation is probably almost gone to really much more between all of us. How do we create a partnership ecosystem. Right. To really help each other. Right. I think it's right that you say that. Yeah, it was like back then you had lemonade coming to the team Hippo, and it was like this, oh, let's see, the challenge for an incumbents. And then there was a wave of saying, you know what? That's not going to work. And a lot of those challengers went actually and started building technology to sell to the incumbent and it became more of a partnership. So that definitely happened. But although I will say I feel now we're kind of going full circle because I'm also seeing now more new companies coming out saying, well, with this new, more mature technology, we can actually start to challenge the industry. So a good example is corgi out of Y Combinator, where it's incredible how the money that they're raising right now, I think they hit over a 2 billion valuation recently. They're speaking on stage here as well later. And that's where they're going and saying we want to provide, I think they say, as insurance at the speed of computer, speed of lighting. So I think we will see more challenger insurers come back. And we had Daniel Schreiber from Lemonade at our conference last year in Europe and still in his mind it's like, well, we are just set up differently from a data perspective and more like foundational perspective to be able to harness this technology that the incumbents just can't. So I think that discussion is still there. But similarly, insurance is also just an industry that is inherently selling a product that is about trust and it's dealing with risk. And so in some way, like the legacy carriers, they are leaning into that more now. And the panel I had with the CIOs from Don Hancock, MassMutual, so on, they were like, well, that's fine, we have all these new incumbents, but at the end of the day, people buy insurance because they want a trusted partner, somebody who's been around for a long time, has the financial stability. So it's an interesting debate and which one, which I'm sure will continue to dab over the next couple of years here at the conference as well. That's fascinating. So you almost are seeing like a new cycle, but because I think you're right that you still see like the corrugates of the world, but it is still feels like the exception to the rule. But I think it's going to be interesting the next few years. And one of the things that are really interesting about this, like a corrugate proposition is they are approaching the angle of disruption from a different perspective. They are not saying going to be cheaper, they're going to be. Now everybody talks about we're going to be faster. Yeah. Which is fascinating. But it's something that probably 10 years ago was we were not discussing it up. And it's something which is completely front of mind to insurers, which is like, how do we provide the best service to our brokers or insured? And now the disruptors are taking a similar approach. Yeah, yeah. So faster. But I think also what I'm looking for now as well is who is thinking about not doing what they did yesterday faster, but building the insurance of tomorrow. Because I think, and this is a completely separate thing we can dive into if you want is like how the risk landscape is changing as well with AI because with this new technology comes new risks. And so what new types of insurance products, especially on the commercial side, do we need to build to? How do we underwrite AI risk? We had the group CTO of Allianz, Christian on stage with Anthropic, where that was one of the key things. And he mentioned that when Allianz does their annual risk survey and they measure what are the risks facing businesses, AI went from number 10 on the list to 2, so second highest, just behind cyber, the biggest jump. And he's foreseeing that this is something which the industry needs to lean into more. Also it's like how do we build new products for the future as well? So it's not just about using the technology to work faster, but also how do we build better products as well, both underwriting and also customer experience. And probably that is something. It's a muscle that the industry is probably not very. Doesn't exercise frequently creating new products. Probably the last major one was cyber and that's probably whatever 25 years ago. Right. So it's really interesting, right, how the product innovation follows the AI threads. Yeah. So for us, as intriotic insights, what we are looking to do now is trying to think how can we help insurers build these new products by helping create bridges between industries, meaning get companies from other industries who has data on risks that the insurance industry doesn't have and create those bridges so that we can create those new products. Fascinating. So I'm sure like when you were planning this conference, you were thinking, okay, what are the questions you want to answer other than facilitating that collaboration between all the players in the ecosystem? What was in your mind when you were planning this? So this year when we're planning this is. So if we go back to our Europe conference. So for those who don't know, in short against us, we do three big shows. London, New York, Hong Kong. So we have a really global perspective on what's going on in the industry. And back in March, when we did our London conference, when I went through the survey, almost or big majority of all of our customers or attendees said we want to see real case studies, we want to see real use cases of how AI is being the deployed at scale. And that's something which internally in my team going into the US show now here in June, I said we need to look for and find examples of where this technology is not just in pilot mode, but where it's Actually in production. So that's been probably the main question looking at. So that's one question. Then the other question for me, and this is more me thinking about how our conference evolves, is what impact will OpenAI and Anthropic and likes of this have on the existing tech industry and insurance? Meaning the existing players that are providing, like will they be able to replace. Will it be a partnership with it? Like, how will that dynamic be when you start having these frontier models come into the industry? And how much will that, you know, you had the term SaaS apocalypse, right. Come out and everyone's talking about the stock of ServiceNow Salesforce being down. Like how much is that also impacting the tech vendors in the insurance space? Those are probably the two things. So that was the data hyping on the first one on the real case studies of how AI is actually driving value. Yeah. Have you been able to answer this question? What have you heard in the last couple of days around what are the ingredients of actually driving value at pace? What's the right way of approaching an AI transformation? Yeah, so I think the most interesting one that I saw was the one that was announced yesterday with travelers and OpenAI right now they have been able to take 90% of all of their first notification of loss calls done for auto claims and use an AI voice agent developed in partnership with OpenAI. And they picked auto claims specifically because it's high volume. Travelers deal with 1.5 million claims a year. And so there's a lot of data and volume to go out there. So that was the reason why they picked that. And then they've worked very much integrated with the business, getting the business leaders involved in this process. And that is a case study where I thought that was interesting to see how they. They've been able to at scale now and they started out in eight states and then they've now after just a couple of months of testing, they was able to roll it out nationwide. And some of the interesting things that I took from it was how they actually used AI to control the rollout. Meaning have a bit of like a control center where they could see, they could test, trial it and very, very quickly see when was conversations with these voice agents not working and adapt and create. So that was an interesting example. So what would you say, would you say the takeaway from that one is what was the secret sauce in that one? Was it that collaboration between the technology teams at Travelers, the business teams and a provider like OpenAI? I think the secret sauce from there I would say is how much they were leaning into working with the business. The business part, which also was something that came up in my conversation on the CIO panel was with this, to get the technology to move forward faster and implementation, we need to work with the business leaders much more. I think in their case, as they said, we've all had bad experiences with the poor chatbots and so getting everyone in the room saying what is the level of quality of conversation we need here? And so it's not just an IT project, but it's really a business project. And I think said for them it was building a completely new operating layer. So it was just not a new technology, but it was a completely new way that they were thinking about how to manage trust, notification of loss on auto claims. So and ultimately all these initiatives require change management. Right. Require the clarison gestures, the claims teams to feel comfortable with the recommendations from those AI driven decisioning. And so I guess the involvement of the business is not just to best define the operating model, but also like to feel comfortable with how it's working. Right? Yeah. And then I think there's the two other things which came up when one of my conversations with another tech company on stage here was a the notion and the person I was speaking with had a background from Facebook and as she started off saying, well, Facebook was very famous for, you know, move fast and break things. And many people don't know this actually, but they actually changed that statement to move fast on stable infrastructure or so, but not breaking things anymore. And the sexy thing in the industry is just let's, let's go quickly, let's move fast. But when you look at the big projects that gets done, it's actually a bit the opposite. It is you spend more time upfront thinking about, okay, what is it that we need to get done here? Who are the people we need to have in the room? What is the data we need? So you're actually thinking slowly and then you have a much more rapid execution because you've just gone through and mitigated for all of the things that you really don't want to come up once you're sitting and deploying and then that's really then holding you back. So I think that's what the case there were travelers that they did really well is that they invested that time up front to really get everyone in the business involved really making sure that they knew before they started in executing. So it was a good example of thinking slowly and then acting, executing very fast. And then the other thing which Also from another conversation I had on stage was thinking about the human in the loop. So they didn't go in and try to automate 100% of the claims. There's still a certain level of claims that are complex, that needs to have a human in the loop. And I think leaning into that and saying, well, what is our human in the loop strategy? Or to what extent is technology deserving of doing this for us? And then to what extent are we still relying on human to come in and do that thinking and then do that even better? So those two things, the point you made about the think slow, move fast or execute fast. The real reason I said I get. Well, anytime anybody asks me, like, what's the single differentiator of clients we work with that move fast or actually capture value fast versus not. It is exactly what you said is. And when you say things slow, it's really have real clarity of what's the end state you want to get to. Yeah. And then, then make really fast executions to get there. I think the flip side of that is I've seen also that argument being used to justify just moving slow. Yeah. To justify the will it take 18 months to figure out the target state? And I think the trick, which is obviously what's difficult is what's that balance of like having real clarity of what your target state you want to achieve and defining that, but at the same time not waiting 912 months to execute. Right. Because in reality the market is moving quite fast. Right. So if you're in your plan on delivering value in 2027, it starts being too late. Yeah, there's definitely a balance. I think it's not black and white. Right. So you can't spend all of your time just sitting and planning. At some point you need to step out and you need to try something and. Because that's how you learn. But I think the problem occurs when you take the leap about now we're going to do this amazing. You put out the press release and we're now putting this huge investment into this. And you haven't done the upfront thought process in terms of, well, what are the risks here? What are the associated with, like, do we even have the right data for this? Is this even a profitable investment? Right. So I think there's a phase of quick iteration. And let's take an example from us. Even here at this conference, we have a couple of products that we haven't rolled out to everyone. It's not public, people can't see it, but we've handpicked a couple of attendees where we are running essentially a pilot. Very, very iterative example of like, how was a new experience to go to a conference. We're testing that, we're getting feedback, but we haven't gone out and made a huge public statement about like, we're now going to do this and change this way. So we're right now still in, you could say, like stealth mode. Just thinking about how do we get the details right here? What are the risks when we scale this, what's going to be the consequences when everyone in the conference is going to start using this product, how will it change? So we want to do that upfront thinking as much as possible. And then once we feel it's ready, then we then launch it and hopefully then launch it much, much quicker instead of getting through a slow clog of execution because we maybe hadn't thought through the scaling process. So we're looking forward to hearing more about what whenever it goes out of stealth mode. So that's the thing is like, I'm not going to reveal too much about it, but obviously in the same way that AI is impacting insurance, it's impacting us as well. Like, there is very different way people are going to go to conferences and they're still going to be around, the same way insurance can be around, conference is going to be around. But I just think the way you're going to go to conference is going to be different. And so that's what we're experimenting with. And we're excited to also show the industry what we can do on that front. So, yeah, we'll touch on that in a minute because you showed me a good example earlier about how is AI impacting you guys. And I would like to touch on. I'll just say before doing that, you mentioned me the other take, one of the takeaways was about the importance of a human in the loop. Right? It's like, how do you create value by also like really identifying what's the role of automation and what's the role of the human judgment in any given process. And I think we've got quite a strong point of view on that, which is we always advise our clients is think about an operating model, a technical architecture that is designed for automation first. So design it as if everything was automated. Because what is clear is that that is a direction. I'm not saying full automation. The direction is increasing levels of automation. And then I think given that we will never get there in one go and even in five goes, it's like how do you then really apply judgment on what are these steps in those workflows where you really want the human judgment and do it in a very deliberate way. Right. I think, I mean, it might sound like a nuance. It's a very different approach than the historical one, which is like we assumed humans would be involved in every step of every process and then we just designed technology around it to make it more efficient. Right. And I think that is a significant change in mentality. Yeah, that's a change of where. And this is, I think, where people get a bit scared about thinking, okay, when you're taking the human out of the loop, is that going to remove the jobs? But I think that's where I always want to challenge people and say, well, this is where we need to be more deliberate about where the humans are. And then we need to double down on that. So for me, it's very exciting that we can now say, well, a lot of the things that could be automated and would take that away, but what are the things that both humans is still the very, very best to do? The relationships, higher, complex decision making, how do we double down on that and actually do even more of that, become more productive as well with that? So, yeah, and you actually, you were sharing earlier today with me a anecdote of how you're using AI internally and the impact on the talent on the world. So, like, what are your thoughts on that? So a couple of things. So one, listen to a podcast with Marc Andreessen where he talks about this notion of AI vampires where you have these people right now that are so sucked into the capabilities of this technology that you end up just not sleeping because you can all of a sudden do so much. And so that's addictive. And there's definitely a bit of that going on in my office at home. I've definitely had a couple of very, very late nighters just producing so much work because all of a sudden I'm enabled to do so. And I can see that as well in the team. So this notion about, oh, well, you know, AI is just going to make us work less. Well, actually, I don't think so. I think when people see that they can do more, they get addicted to that and they want to do more. Now practically, how it's impacted us is so in our business, we need to have a lot of calls throughout the year. We need to put on the right agenda, we need to have the right people in the room. And so the most valuable work that my team does is speaking with people it's speaking with insurance execs to technologists like yourself, learning what's going on. That's the valuable work that needs to be done. Now, historically, we could maybe have three to four calls a day because even though we had time for more calls, you need more time to the admin coordinate, write notes. When we have a prep call for a speaker session, we need to do a debrief, write it down, write the notes, send it to panelists and really prepare all of the content. Now, with our internal systems, the way it's set up right now is the moment the person, and let's take myself in the example, the moment I finish my call with an executive, the debrief email is already done. It's written in my inbox. I don't even have to do anything. It's listening to the conversation and it's already taking that. And what's even more is that if other people in the company should be informed about the conversation that I just had with a certain executive, it's already prompted that email as well. And the same thing goes for our sales teams admin on long proposals. It's just that doesn't happen anymore because we have the data right there. We used to have people ask us how many of X, Y, Z attendees are coming. We can just now quickly search it up. We have it right there. So we can now spend a lot more hours just on calls, talking with clients and doing the high level work and then they are sitting in the back end and doing a lot of the processing that normally we would have to sit and spend hours doing. So we're by no means cutting any jobs. Like for me, I'm having my whole team work so much more productively and to be fair, coming up with new products as well. What are new ways we can make the conference better? By having them more engaged in building instead of doing the backend engineering. I mean, that applies to your point to any industry, right? So we do the same for insurance companies and brokers. And what are you doing internally? Right? And it's all about how do you remove that busy work that really doesn't drive any value and really enable your teams to be much more productive? Have you seen? I think one of the things that I think everybody's still learning is it does create much more mental pressure right at the end. It's like you're switched on because when you are doing admin to some extent, you are procrastinating. You're procrastinating, but you're also relaxing. You don't need to be focused. Right. So we see that even internally at Siteora with our engineering team, sales teams, you are switched on all day long. Yeah. Are you seeing that internally or no? I don't see that. I find it more relaxing that I don't have to monitor and report so many things. To give you a very simple example, I've not had to check my email over the past two days because I have an AI agent set up to every two hours it checks my inbox and if there's anything critical, it sends me a WhatsApp message saying, hey. And so it's just for me, I've set up my systems and we are trying to do that across the whole team in a way where it should probably almost alleviate some of the stress of always like constantly checking your inbox, constantly being over things, doing admin things. I think the admin in some way is Ordranian, but I feel it's very liberating to be able to be more focused on building. At least that's for me. Maybe it's different for other people. So no, I haven't seen that. But yeah, people will have to think a lot more in the future. I just wanted to get your thoughts. To be honest. That is exactly what we see is there's sometimes an initial reaction to, oh, like now I'm going to be like whatever number of hours you work, focused on doing actual work. The reality is people love activities that are mentally stimulating that are really elevating the job. And I always think about it as many people challenge this concept of okay, if you're removing the basic activities, what is the development trajectory for junior professionals? And really what we're doing is we're just like elevating the stack. Right. So you will start, instead of starting doing all the really boring work, you'll start halfway through the progression and develop further, right? Yeah. And I think there's a skill that I am also trying to be better at which is knowing when to think and when to use the technology. Because it's very easy to fall into this trap where just any problem you just put it into clause and you see what's going to be. And what I've tried now I've realized, hey, I need to sometimes take a step back and be like, you know what? I actually this is something I have a lot more context for myself I need to solve. And I remind my teams as well. Sometimes I do get emails when I'm like, is that you or is it a quick prompt in Claude? And where I Have to kind of call out saying, you need to still review the work. Like sometimes I've seen some work published where I'm like, that probably was missing the human in the loop there, where there was some mistake that we should have caught. So I think really understanding and being intentional about what do I use this technology for and how do I use it is going to be key. And I think actually the people coming out of uni is going to be more equipped to do this than us because they've used this technology and they're much more used to using this. And that's also what I'm seeing in my organization. Like, the people are coming out of uni and being fresh. It's more natural. It's more natural. It's a bit like using Microsoft Excel for the. Like, there's the people who used it and the people who didn't use it. And so I think there's a really the same way that there's a skill to use Excel, there's going to be a skill to use AI in the same way. So. Yeah. Okay, so the final question to wrap before we wrap it up, like, if you had to predict what's going to be different in the 2027 edition, not so much from an organization perspective on the conference, but more like in what sense is going to feel different than this? Yes, we'll start to see, I think, a lot more use cases deployed at scale. We will see more of these case studies like the one I mentioned with travelers. There will be more interesting examples of where insurance have moved forward to use this, but it's hard to say. And I almost like, don't want to make predictions on it because I feel things are changing all the time. So we'll see. What are you. From your point of view, I was just thinking, because what you just said ties back really very much with what you were saying at the beginning of the conversation around people coming to the conference to see like real, tangible case studies. Right. Yeah. I know in the conference you've got like different stages which, like the technology one, it might make sense to create one which is only at scale use cases. And I think all of us would benefit from separating the what's real today in production from what is about building the future. Right. I think, I think interesting. I think actually having a stage which is like showcase stage, not from a technology point of view, but actually a case study showcase. One thing which we want to do a lot more is dive into the case studies that has worked really well and trying to bring out as many of the learnings because I think that's what people are craving for. I think we're past the notion of panel debates where people are just having a bit high level chat and people want to see real insights about what worked, what did not work. So those are. But I would love to hear again the two questions which I had going into this conference. I'd love to just get your take on those two. First one obviously being how you see AI being deployed at scale. You obviously you work with a lot of Azure, you just had the partnership with Zurich. How have you found working with them right now? What are the ingredients audience to deploy your technology at scale? I think it goes back very much to your think slow, execute fast. As I said, we work with many insurers both in the us, in Europe, in apac and the single differentiator between those that really move fast and capture business value and those that take longer is that clarity of what is a target state. What do we want these operations to look like? So that's both from a technology perspective, but also like what is the single KPI or single North Star that is driving this transformation? Right. So in the example of Zurich and many other clients, it's very clear, it's we want to be the fastest to respond to our broker request. I know there are secondary benefits or secondary notes stuff, but that is probably the main one. So then it's very clear like everything we do with them is focused on that. No start the second one, which actually is what I was going to say when you asked me. You were going to ask me back about like what do I think is going to be different next year? In the last 12 months we are working in a very different way with our clients and the way we were working with them three, four years ago. So three, four years ago or even two years ago, it was very much we provided the platform and our clients usp, we configure deployed, right? Those plans that are moving faster and capturing real value. We've got a partnership that goes beyond providing just technology. It is really a thought leadership partnership where we get together, we think about how can we benefit each other and it feels like a proper partnership. It's not a vendor provider type of relationship. Right. And I mean obviously as many others in the industry, we even have started to create different teams internally to really change our relationship with our clients. Right. So we've got new roles internally. So we've got four deployed engineers, we've got four deployed product managers, but are really the ones that really bring the thought leadership of what can be done with Siteora to really brainstorm with our clients on how should they be evolving. And it's much more collaborative than currently it was a few years ago. So probably those of the two is the things load secured fast with the KIO node star and a proper partnership where we kind of brainstorming together how to drive impact. Yeah, it is exactly following on those points. And then the final thing if I can ask that is obviously now we have OpenAI and anthropic coming into the show. How do you see yourself being competitive going forward in terms of they're obviously coming in making bold statements in industry and I'm keen to hear your response to that and how you think actually leaning more into your competitive edge then when it comes from a technology point of view. I mean all the foundational models like OpenAI, Anthropic, Google, Gemini, they are doing incredible progress and we are all benefiting from that. Even some of the demos we've seen in here at the end, they are a horizontal provider. Right. So they, I mean even though they've got vertical teams, they are providing features, technical capabilities that are applicable to any industry. Insurance and financial services is a very specific industry. It's very regulated, it's got plenty of HK Certified cannot be just accommodated just by using directly a foundational model. Right. So when we have this conversation with clients or like we talk about this a lot with our clients, like buy versus build, what should you buy, what should you build? None of our organizations can just stay philanthropic and just deploy it live. Right. So you need first of all a number of rail guards around it to like make sure that you're compliant with regulation, that you have all the auditability required for the compliance organizations globally, that the product is scalable. It's really easy to do like a one demo for a simple use case. It's a different story when you have to deploy this type of technology across a number of different countries and a number of different lines of business. You have a real product that adapts to the insurance workflows. Right. So even though we've seen demos where it could feel like they are competing with people like us, I still see them as their role is providing the foundational capabilities. They're bringing to light those capabilities and some of these demos, but they will always be a role for the insurance specific platforms or providers like cytora. Yeah, and that's also been my takeaway from the conference coming into this is having seen it's like it's easy to get dragged into the headlines of. Yeah, of course anthropic and organization is going to come in and do this. And you see those edge cases, as you said, you realize that, okay, like the data that the likes of you have, the knowledge in terms of working with an insurer, it's just that is that competitive edge to lean more into. And I think it's ultimately going to be a partnership. It's going to benefit everyone. I think in the earlier stages in any way in the industry, it always feels this goes back this a perfect analogy. Like when we talk in 2018, it felt like InsurTech was here to disrupt the industry and then it evolved to be a partnership. I think the same is happening with some of these examples. Like a frobish, it might feel like a threat or a disruption. Ultimately it's going to be a partnership with companies like ourselves. Right. All right. But yeah, Chris, it's been a pleasure. Thank you so much for joining with me. Thank you. Appreciate it. Thank you. Thank you. Making RiskFlow is brought to you by Cytora. If you enjoy this podcast, consider subscribing to Making Risk Flow in Apple Podcasts, Spotify or wherever you get your podcast, so you never miss an episode. To find out more about Saitora, visit saitora. Com. Thanks for joining me. See you next time.