Progressive Corporation (The)

And pardon me, everyone, I'll go ahead and count us down to start the conference. I'll start the conference in 5, 4, 3, 2, 1.

Good morning and thank you for joining us today for Progressive's fourth quarter investor event. I'm Doug Constantine, Director of Investor Relations, and I will be moderator for today's event. The company will not make detailed comments related to its results in addition to those provided in its annual report on Form 10-K and the letter to shareholders, which have been posted to the company's website. This quarter includes a presentation on a specific portion of our business, followed by a question and answer session with members of our leadership team. The introductory comments and the presentation were previously recorded. Upon completion of the previously recorded remarks, we will use the balance of the 90 minutes scheduled for this event for live questions and answers with the leaders featured in our recorded remarks as well as other members of our management team. As always, discussions in this event may include forward-looking statements. These statements are based on management's current expectations and are subject to many risks and uncertainties that could cause actual events and results to differ materially from those discussed during today's event. Additional information concerning those risks and uncertainties is available in our annual report on Form 10-K for the year ended December 31st, 2024, where you will find discussions of the risk factors affecting our businesses, safe harbor statements related to forward-looking statements, and other discussions of the challenges we face. These documents can be found via the investor relations section of our website at investors.progressive.com. To begin today, I am pleased to introduce our CEO, Tricia Griffith, who will kick us off with some introductory comments. Tricia?

Good morning and thank you for joining us today. As we usually do for our calls after even-numbered quarters, today we will have a presentation that dives into a certain aspect of our business. Today we'll speak to two of our strategic pillars, people and culture, where everything starts for us, and competitive prices with a focus on technology investments in our claims process. To present these topics today, we've enlisted two experts from within Progressive. First, we have John Murphy, claims president. John assumed the role of claims president in December 2021 after spending nearly seven years as Progressive's customer relationship management president. In this role, he's responsible for all aspects of claims strategy and resolution across all product lines. John joined Progressive as a claims representative in 1992. During his initial tenure in claims, he held various strategy, process, and operations roles across the country, including regional claims manager, national implementation leader, claims business leader, and physical damage process business leader. After John, we have Matt White joining us today. Matt has been our claims business leader for data and analytics since May of 2022, after spending six years in personal lines managing our technology and innovation team in direct acquisition. In this role, he's responsible for our claims data science, business intelligence, and data strategy teams that build solutions for all aspects of claims handling. Matt joined Progressive in 2014 as an IT manager after serving in the Coast Guard. His military career took him from various leadership positions on ships patrolling in the Caribbean and Eastern Pacific to Washington, D.C., where he worked on Capitol Hill in budget and program management. He was the director of operations in Key West, Florida, and ultimately to Cleveland, where he oversaw several business lines across the Great Lakes region. Again, thank you for joining us this morning, and I will now pass it on to John. John?

Thank you, Tricia. Good morning, and thank you for joining us today. Over the next 40 minutes, you're going to hear a quick recap of 2024, which was a tremendous year for Progressive. We'll dive into two of our strategic pillars. First, people and culture, which is where our long history of success starts, and then competitive pricing, where we'll focus on the critical role that claims plays in creating a competitive advantage that helps fuel business growth. And finally, we'll share just one of the many examples where the effective use of data and technology at Progressive enhances our claims team's accuracy and efficiency. Now, before I get to the topics at hand, I wanted to acknowledge the devastating wildfires that ravaged the Los Angeles area in January. Our thoughts and prayers remain with those affected by this event. In that vein, we know our customers want and expect action to support their recovery. Our Catastrophe Services team responded quickly with empathy and respect to meet their needs. And while the majority of the claims we received are now resolved, our team continues to assist our customers however they can. I also wanted to acknowledge our human resources and local leadership teams who responded quickly to support our employees who were impacted by these fires. As a senior leader in this organization, the urgency, empathy, and care that our collective team has shown here is an excellent example of our core values in action and fills me with incredible pride. Quickly recapping 2024, in short, this was arguably the greatest year in the 87-year history of Progressive. Net premiums written grew approximately 21% year over year, finishing the year at $74.4 billion. In absolute dollars, premium grew by nearly $13 billion in this single calendar year. Now let me try and put that in perspective. That nearly $13 billion net written premium increase in 24 is equivalent to adding the premium of the eighth largest auto insurer in the calendar year of 2023. For those who have been following us for a while, the premium growth in 24 is about a billion more than we wrote for the entire calendar year of 2003. Average written premium increases provided a little bit of a tailwind here, but the majority of this premium growth comes from customer growth, which is our preferred measure, and 2024 was a record year here as well. We increased active policies by more than 5 million this year, which is more than twice the previous highest annual rate of policy growth in our history. Growth is one important objective for us, and profitability is the other. You're well aware of our stated calendar year goal of a 96 combined ratio or below, and in 2024, we produced a CR of 88.8, well below the 96 and also about six points lower than 2023. We often say that growing or generating a profit individually is fairly straightforward. To do both simultaneously and at the performance levels that we did in 2024 is significantly more challenging. In true progressive fashion, more than 65,000 of us work diligently together to deliver what may very well be the best combination of growth and profitability in the industry. While we celebrate these successes, our excellence core value challenges us to continually improve for our teammates, our customers, partners, and investors. I believe strategic investments in our people, data, processes, and technology position us to perhaps have an even better 2025. The four cornerstones is a construct that we've shared in the past. It's how we think about competitive advantage and defines how we win and win in the right way. We start with our core values or who we are. These are unifying statements that provide the very foundation of our company culture since the late 1980s. Next is our purpose or why we're here. We evolved this statement in 2022 to build on the legacy of our core values and our history of challenging the status quo to accelerate progress. Then we have our vision or where we're headed. This company-wide objective highlights the constituents that we feel so fortunate to serve and our never-ending pursuit of becoming the number one destination. Finally is our strategy or how we'll get there. These are the four important pillars of this strategy and two of them will be the focus of today's discussion. people and culture, which are collectively our most powerful source of competitive advantage, and competitive pricing, which is driven by industry-leading segmentation, claims accuracy, and operational efficiency. Progressive people and culture are collectively our most powerful source of competitive advantage. A very well-known and respected brand, a routinely recognized top work environment, and sustained business success makes us an attractive option for folks in market looking for jobs. While our growth rate in staff over the past 10 years lags PIF growth and premium growth, it has been substantial. Our outstanding talent acquisition group generates robust candidate pools for our roles, from which we then choose top talent with personal values that align with our core values. Due to the very significant number of people interested in working at Progressive, we're able to be highly selective. In fact, we hire less than 3% of people who apply for jobs at Progressive. This scale advantage allows us to bring additive skills and experiences to our team, ensuring that we're always growing and always evolving. Our culture is built on the foundation of our core values, and it has evolved beautifully with our people growth over several years. A transparent, inclusive, and forward-thinking environment ensures our people feel empowered, welcomed, valued, and respected. A development focus allows our people to build careers and become talented business leaders who can drive enduring success for decades to come. Gallup is a multinational analytics and advisory company well known for its public opinion polls and surveys conducted worldwide. In an article published on January 14th of 2025, Gallup reported that US employee engagement sank to a 10-year low. That is not the case at Progressive. At Progressive, 2024 marked a significant year of achievement, where engagement has surpassed previous records. Progressive ranks in the 98th percentile of engagement and the 99th percentile in overall satisfaction. These results have us in the top 10 and top 5, respectively, for U.S. companies in Gallup's client database. As we look a level deeper into our 2024 survey results, we see year-over-year increases in every single question and in every tenure bucket. As we explore the tens of thousands of comments from our team, responses to the question, the one thing I like most, generates themes of a positive work environment, care for customers and colleagues, strong leadership and support, career growth and development, flexibility and values. You can see just a few of the comments here on this slide. Once again, consistent with our excellence core value and our desire to consistently improve, we also ask about things that should change. The data that we collect from that question, really all others, are rich and guide our efforts to further nurture our special culture. We believe firmly that the investments we've made in our people and culture have fueled our growth and success for several years now. We'll continue to care for both to position us to be even better in the future. In prior presentations, we've discussed our ability to rapidly deploy risk selection and new product models, our segmentation excellence, as well as efficient media and agency compensation, each of which has had a positive impact on rate competitiveness. Claims plays a very important role here as well. The combination of loss costs and loss adjustment expenses typically represents between 70% and 75% of our total company expenditures. So we focus heavily on producing accurate claim outcomes while optimizing efficiency, customer experiences, and employee engagement. We refer to these as our four guiding principles, and they have helped inform our daily efforts, investments, and priorities in claims for more than two decades. On the left and right, you see the two key constituencies that we are privileged to serve. In the middle are the two items that have the most linear connection to our combined ratio and ultimately the rates that we then have in market. If we don't deliver here, we simply can't compete at the level we've become accustomed to and continue to aspire to. This chart is our theoretical cost curve and gives insight into how we approach our work. The x-axis represents loss adjustment expenses, or LAE, essentially what we spend to operate the claims organization. The y-axis represents loss costs, claims payments and reserves, plus LAE. Much like my commentary earlier about growth and profitability, being accurate or being efficient individually are straightforward. Doing both at the same time is a far greater challenge, and we believe we do it better than anyone in the industry. Now, there are downsides to focusing too much on either side of this curve. If the sole objective was to be the lowest cost, we couldn't make the investments in people, data, and technology that enable us to pay the right amount. Quality would suffer, cycle time would increase, rentals would extend, and ultimately, loss costs would rise. Likewise, if accuracy was the sole objective, you would need to overspend to eliminate the potential for errors, likely spend on non-value added activities, and end up with a cost structure that would be uncompetitive. We leverage operational excellence to drive us down this curve. This is where having the best people in the industry who are willing to get into the details, investigate tirelessly and effectively, and make the right decisions around coverage, liability, and damages really pays dividends and moves us down the left side of this curve. Empowering them with the right data, processes, and tools increases their efficiency and throughput, moving us down the right side of this curve. This view of driving down total cost is more about the journey and the incremental gains that come with it than any theoretical destination, because no matter how good we get, we will always seek to be better. Within the claims organization, we constantly measure accuracy and efficiency, so we always know how we're doing. Objective assessments of the work provide valuable insights into how and where we can be even better. And while we're always trying to find the optimal spot on this curve, we also strategically target efforts to shift the curve to a better position for us and for our customers. You'll hear from Matt White shortly about how we invest in new technology, data, and processes to shift this curve. And this is what driving down and shifting the curve looks like in practical application, using perhaps the best measure of success for claims, which is total cost. While claims supports all manufactured products across auto, special lines, commercial lines, and home, I use private passenger auto data here because it offers the cleanest comparison relative to industry. This graph is a visual representation of the competitive advantage our claims organization, in conjunction with all other business areas, brings to Progressive and shows why we're able to grow faster and with better margins than the industry as a whole. Total cost is a combination of loss costs, which tie directly to accuracy, and LAE, which is our primary efficiency metric. This slide compares progressive, reflected by the blue line, to the industry ex-progressive, which is in orange, and shows that we've maintained an advantage for more than a decade. More recently, though, you can see the gap widening. And while we don't have complete 2024 statutory data for the industry yet, we have loss ratio data through the first three quarters of 24, and we maintain a seven-point advantage in loss ratio alone. As we compare our own results for 2024 to 2023 for total indemnity, we see a near nine-point improvement and finish the most recent year sub-70%. Back to our full set of guiding principles, I'm proud to say that in 2024, our claims organization had the highest engagement in our history. the lowest LAE ratio in our history, improved accuracy, and generated the best customer satisfaction and retention that we have in several years. These results don't just happen, and they don't happen overnight. This culture of execution excellence has been developed over years and isn't easily replicable, but we believe it can be improved upon. And now Matt White, our acclaimed business leader of data and analytics, is going to share with you how we use data and technology to enable and enhance our human capital. While the efficiency and cost wins you'll hear about are very significant, it's our intentionality around also increasing accuracy that makes these efforts really valuable. Matt?

Thanks very much, John. Empowering our employees is indeed at the heart of our approach and claims. As emphasized by John and as Tricia states often, along with our culture, our people are our greatest competitive advantage. We focus on enhancing, not replacing, their roles through technology. Similarly, we want to enable our customers with user-friendly digital options so they can interact with us when, where, and how they choose. We'll share some of those concepts and how our progressive DNA around digital experiences, segmentation, and data translate to claims. And we'll dive deeper into a specific use case around photoestimating, highlighting the progress made and our commitment to achieve the optimal balance of accuracy and efficiency. John showed how we stack up from a total loss and LAE perspective. Here is an alternative view of efficiency, an indexed comparison of auto policy growth and the number of staff aligned to auto claims handling. We continue to grow and hire, but our scale and strategic investments have allowed us to grow staff at a slower rate than policies, shown in the gray shaded area indicating the growing gap. And while we acknowledge that frequency declines in this period are a tailwind, we're very pleased with the efficiency improvements we've been able to achieve. Market conditions may have us make specific calendar year staffing decisions to ensure we're positioned for the future. But over the long term, we believe we can continue to become more efficient and selective with the human capital required to service our customers while maintaining the competitive advantage we believe our culture provides. In prior college, you've heard us talk about our large and growing media spend and how critical it is for us to manage it efficiently. Efficiency is also top of mind with our claims technology spend. The vertical axis shows the indexed gap between auto policies and claims staff, the same gray area I highlighted in the previous slide. In general, we want to be higher on the vertical axis, indicating more efficiency in our staffing. The horizontal axis is our claim's IT spend, a subcomponent of LAE. In this case, both indexed to 2007. You'll note that while we made some progress in growing that policy-to-staff gap from 2008 to 2016, when our technology spend was flat to down slightly, it grew notably faster with some strategic investment decisions after that point. The policy-to-staff gap grew by 50% from the index values of 1 to nearly 1.5 in the nine-year period from 2007 to 2016. But we've been able to grow it by 130 percent from 1.5 to 3.4 in the seven years since 2017. Our investments in technology to improve the claims process have shown through in clear efficiency gains. And not unlike our media spend, we're willing to invest here as long as we can do so efficiently. You've heard us talk before about our digital capabilities in acquisition and policy servicing, and the obvious value we believe advanced product segmentation provides for our company results. That progressive DNA and experience applies just as well to claims. In fact, when it comes to first notice of loss or the moment of truth when a customer contacts us to report a claim, we think about it similarly to our acquisition funnels. That said, it is a bit more nuanced, as it's a funnel that then feeds our claim's handling funnel from the point of assignment to resolution. And that path can be nonlinear, depending on the circumstances of the claim or what facts might emerge after initial assignment. Nonetheless, there are similar tradeoffs at first notice of loss as in our acquisition funnels. Asking a lot of questions might aid initial triage and segmentation, but it might also frustrate customers, drive digital abandonment, and increase call times and expense. So it's very important we gather as much accurate information as we can as efficiently as we can, but limit it to only what we truly need. As John alluded to previously, it's straightforward to do one. It's much more complicated to do both at the same time. To be clear, segmentation in this context is about the facts of the claim and not customer segments. We are not talking about Robinsons or Sams here. But not every claim or accident is the same. Knowing the number of vehicles and parties involved, whether vehicles are likely total losses, and whether there are injuries and how severe are just a few of the many important facts that allow us to segment incoming claims and make assignment decisions to get the claim in the right hands faster. Getting it wrong can negatively impact cycle time, which can increase expenses such as rental and storage fees if we must spend time retriage in claims and or vehicles. It also can result in a suboptimal customer experience and even hurt retention. We believe there remains additional upside on the digital side of our first notice of loss funnel and have been investing accordingly. Industry data from Bain suggests that digital adoption in the auto claim submission process averages about 25%. While we are meaningfully above that industry data point, we think there remains additional opportunity given the long-term trends we've seen in acquisition and policy servicing. Many customers prefer interacting digitally, and we'll continue investing to ensure we have those options available. That said, an accident is certainly a very different kind of life event than purchasing or modifying a policy, and we will always be available for human-to-human contact with customers that prefer or need that channel. One of the reasons we continue to invest in digital experiences for our customers and our employees is it further accelerates a virtuous data cycle we've referenced in a variety of contexts over the years. As we work to resolve claims, our customers and employees generate a variety of interactions with each other and other involved parties. Historically, across the industry, these have been predominantly analog in their nature, with lots of phone calls, manual claim notes, and relatively unstructured data. At Progressive, we've invested significantly in modern digital experiences. Those enable us to turn many of those unstructured processes and associated data into more structured information. Additionally, the very nature of digital interactions creates even more data that's not exclusive to a finite set of events or outcomes. They also provide experiential insights to how our customers and employees are using those systems. This data helps us identify areas for additional claims process and technology investment, connecting back to John's description of how claims contributes to competitive pricing. Our operational efficiency improvements help lower LAE, which enables lower rates, powering additional business growth and scale, generating even more data, and enabling additional targeted investments. One example of these cycles in action has been photoestimating. Photo estimating is a digital experience whose adoption has grown significantly. It can be a convenient one for customers and claimants when they're uncertain as to the repair costs relative to any deductible, or they're not sure when or where they'll get the vehicle repaired. From the comfort of their own home or workplace, they can submit photos via a guided digital experience and get a repair estimate back quickly, often within a day, if not faster. If you recall the conceptual curves John discussed, photoestimating is a good example of a shift in the curve. And as we'll walk through, even when we do achieve such a shift, we continue to optimize so we can operate at the bottom of the curve. The chart on the left shows annual photo estimates since 2016, over which time we've enjoyed an 82% growth rate. While we're not showing actual numbers on the primary vertical axis, know that in total, this represents millions of photo-based estimates written over the last eight years. And with it, of course, tens of millions of customer-submitted photos. On the secondary vertical axis is an indexed view of our estimate quality index, plotted on the orange line. These objective assessments of the work that John mentioned earlier are a core benchmark for quality and accuracy, and an invaluable source of ground truth. Despite the growing volume, there's been no material degradation in accuracy. So while we're pleased with the growth of photoestimating as a viable and efficient vehicle inspection channel, we are consistently measuring accuracy alongside the growth in volume to ensure the experience we're offering and outcomes we're generating aren't compromising the claims guiding principles John described earlier. The chart on the right indexes daily estimates completed compared to traditional in-person estimate completion. In total, we've seen we can complete two and a half times the number of estimates each day, making it our most efficient vehicle inspection channel. Once we achieved viable scale, refined our processes, organizational and data structures, we began to apply additional technology so that we could potentially drive further down the cost curve. In this case, we're using machine vision models alongside a variety of other technologies to help us automate parts of the photo estimating process. These photos illustrate the process without disclosing actual customer images. At a high level, we're using deep learning models, or neural networks, alongside more traditional machine learning techniques to look at customer submitted photos, like the example on the left, identify the correct parts through segmentation masks, and then identify the location and type of damage by part. Generating an accurate estimate requires several discrete predictions. For example, we need to know not just the location of the damage by specific part, but also the type of damage. Is it a dent, scratch, et cetera? From there, we need to decide whether we should repair or replace the part. And in the case of repair, how many labor hours do we believe it'll take? These models use transformer architectures you may have heard about, quite literally the second T in ChatGPT, but they are trained very differently than some of the models making headlines more recently. These are supervised models that we train on our photos and our own curated data to ensure accuracy consistent with Progressive's estimating standards. Such models all benefit from very large, clean, and diverse data sets. We're fortunate to have all three in-house without feeling a need to look externally. And again, that ground truth data from objective assessments and our own people's disciplined quality assurance processes and willingness to do the hard work to get it right give us the benefit of a very clean, trustworthy, and we believe differentiating historical data set. It's my experience that it's really the combination of technology and progressive talented people that make the difference. On this solution, our data science team works daily with our physical damage process team that combined brings over 400 years of experience. Most of them have worked at every level of our claims organization. They have written estimates themselves, worked in and alongside shops, and have a deep understanding of all facets of vehicle repair. It's that difficult to replicate expertise alongside more advanced technology that really helps us deliver competitive advantage. As one quick example of why the details and subject matter expertise matters, let's consider a bumper. It's not enough to be able to identify a bumper and the existence of damage on it. You need to be able to distinguish between such things as upper and lower bumper covers, depending on the year, make, and model, and in this case, the presence of bumper sensors. At left is a rendering of an example with some of the things our solution does behind the scenes in relative real time. In this case, cropping the bumper from the original image and then making a prediction as to whether it sees the small circular outlines that indicate the presence of sensors in the bumper of a particular car. These can be very hard for even a human eye to detect from a photo. But we must get such things right to ensure we get the accurate part in the estimate in the first place and account for the incremental labor required as shown in the estimate example on the right. Of course, while machine vision is a very interesting technology, we are not in the business of winning data science competitions. We are in the business of insurance, so it's important we prove the value. The orange line here represents the index value of traditional in-person estimates completed per day, the same value as before. You can see the light blue line as we introduced and then scaled photoestimating, getting to that original 2.5x increase in productivity that I mentioned previously. We began this journey in 2019, well before the current hype cycle, as an R&D effort with a small group of our photo estimating representatives. We continued to iterate and refine our models and approach until such time that we were convinced, one, of the efficiency gains, and two, that we were able to generate equal or better accuracy results. Now the darker blue line shows our estimates per day when enhanced by machine vision. In 2022, we began expanding these capabilities throughout our photo estimating organization and fully rolled them out in 2023, having achieved an incremental 2X increase in productivity. To put that in some context, without these advances, we would have needed around 200 additional staff in 2024. While it has been a multi-year journey, the combination of data science and other automation techniques have now doubled the productivity of what, as I mentioned, was already our most efficient means of vehicle inspection and estimating. 100% of our photo estimates are now initially drafted by these solutions and then validated and or corrected by our estimating professionals. To be clear, this is not full automation or straight-through processing that you may see referenced across the industry. We have people involved. We do think full automation is possible at some point, but we won't do that until we're sure we can do it consistent with our guiding principles and, of course, applicable regulations. For now, we're quite happy to continue empowering our people to be even more and more productive, and we continue to see gains with nothing suggesting to us we've even hit a ceiling yet. I'll cover just two examples on how we're continuing to further refine our solution that we think will generate incremental gains in accuracy and efficiency beyond even what we've already achieved. Beyond our people's efficiency, we also work to make our model training more efficient. At our scale, we must keep up with a very diverse set of vehicles and an OEM market that is always moving. One of the ways we do that is with a semi-supervised training approach called pseudo-labeling. This is the practice of training a model on a small set of labeled data to label the rest of the data. Traditional machine vision use cases rely on a very large set of manually labeled photos, as I mentioned. But as we've scaled our solution, we've sought to improve the speed at which we can deliver value across a broader and ever-evolving list of car parts. For context, and while it certainly varies by manufacturer, there are an average around 125 distinct external parts on most common vehicle types. Our process starts with our original segmentation model capable of identifying major parts, such as doors and quarter panels. From this base model trained on subject matter experts' labels, pseudo-labels are generated on a much larger dataset to create an initial base model that's even better at those major parts. This improved base model is then fine-tuned with even more detailed part labels from a diverse set of vehicles. This allows us to get more details about very specific parts in the vehicle, like portions of the grille and emblems, that can all vary in shape, location, or even existence depending on the specific vehicle type. This new part segmentation model is a general template model that works reasonably well on all vehicles. But to ensure the most accurate outcome, we customize the model further for specific vehicle makes and models. With only around 100 detailed label examples, we can apply these vehicle-specific pseudo-labels to hundreds of thousands more examples of that vehicle using a bootstrap technique to randomly sample additional internal data. For computational efficiency, we then fine-tune the model with a technique called low-rank adaptation, or LoRa. LoRa allows us to efficiently adapt large models to specific tasks, enhancing precision without needing as much training data or training time. The point of all this is shown in the images on the right. While you might look at the top right image and suggest the damage is probably on the bumper or maybe the right front fender, the accurate view is the damage extends across three parts, the bumper, front fender, and wheel molding, the details of which we achieve by much more fine-grained part segmentation capability. Our approach ensures both broad applicability and precise customization across vehicle types, reducing the need for extensive labeled data sets. It has enabled us to achieve a 10x speed improvement in training while providing more accurate identification of all relevant external parts. It's important to recognize that such techniques are not possible without very trustworthy and accurate labels and a large data set upon which to extend them. Our subject matter experts and tens of millions of available photos give us both. This is obviously a very fast-moving space we continue to keep our eyes on. This animation illustrates a newer approach called 3D Gaussian Splatting. It allows us to transform two-dimensional images into dynamic three-dimensional models. Doing this well requires a lot of photos, but back to those trade-offs of accuracy, efficiency, and customer experience, we can't reasonably ask customers to take hundreds of photos. But we do ask them to take a video in addition to around eight to 12 photos on average. A one minute video at 30 frames per second of the car yields us around 1800 frames. And it's that data we are increasingly leveraging as part of our solution. Some research scientists have suggested that what large language models are to text, Gaussian splatting is to graphics and reconstruction. The latter is what's interesting to us. Being able to reconstruct a vehicle as if we were in person to understand the full extent of damage. 3D Gaussian splatting builds on previous work in the field of reconstruction, such as neural radiance fields. But it's much more computationally efficient and is a solution that meets our operational needs. Remember, we must be efficient and accurate. While we won't walk through the math here, there are four primary steps to this technique. First, we use the underlying data, again thousands of frames, to understand the position of the camera and construct a three-dimensional coordinate grid to understand the relative position of every pixel in the frame. In parallel with understanding camera position, algorithmic techniques such as structure for motion create a point cloud, or mesh, of the vehicle. This essentially gives us the center point, or mean, upon which to locate the Gaussian splats. On those points, we overlay Gaussian functions onto each pixel to simulate the physical characteristics of the vehicle's surface. It can capture intricate details, providing a more comprehensive reconstruction of the vehicle's surface and geometry. Those three-dimensional splats, or blobs, help us render the point cloud, representing every point as a Gaussian or normal distribution in three-dimensional space. From there, we optimize using traditional graphic rasterization techniques and adjusting the density of the Gaussians until we get results representative of the original training data. What's ultimately produced is a fully interactive 3D model of the vehicle. This is important because it allows you to view the vehicle and damaged regions from novel angles and views that may not have been fully captured in the original data. It can also provide for more accurate scale and distance measurement enabled by fully understanding the relative camera angles. Such approaches can enable more accurate labor hour predictions where the surface area and depth are very relevant to how long it'll take to repair a part. Longer term, we think it could enable virtual inspections of additional damage types, vehicle conditioning in the case of total loss, and perhaps enable leap decisions by anticipating damage to interior parts that aren't visible from external pictures alone because we have a more detailed understanding of damage depth. Lastly, I do want to reiterate that at Progressive, this isn't about cool science or Gaussian math for its own sake. It's about our excellence core value, striving for continuous improvement and better business outcomes for our customers, employees, and investors. And as John mentioned previously, we are willing to dig deep and work hard to achieve those outcomes consistent with our core values. Before wrapping up, I wanted to share our general approach when we consider build and buy decisions. First, we think those are complementary and not competitive sides of the same coin. For example, our machine vision solution for photo estimating is powered by things we have built, but also relies on very tight integrations with our Estimatics platform partner to turn those predictions into the correct part numbers and actual estimates. When building or buying, we prefer to keep things decoupled. Rather than monolithic solutions good for one purpose but perhaps difficult to change or modify for other purposes, we prefer to build or buy systems that are open or can be decoupled so that some of the pieces and parts can be reassembled into something entirely new. This gives us the potential to earn outsized returns on the initial technology investment and provides flexibility when new technology solutions inevitably arise. We can use those decoupled pieces to derive near-term value, but it also allows us to be agile in adopting new solutions like pseudo-labeling, Gaussian splatting, and whatever may be next. We can also start to apply parts of the original solution to build something entirely new that we may not have even considered at the time. On the right is an example of that potential emerging. When we began a firm commitment to our claims machine vision journey with photo estimating back in 2019, we were focused on photos that were submitted after first notice of loss from customers that had selected photo estimating as their vehicle inspection option. But as we've iterated on that experience or funnel, we're now receiving hundreds of thousands of photos per year at first notice of loss and at an accelerating rate as we optimize. This is before a customer may have decided to opt in for photoestimating. We can and do use those for photoestimating, but we can also apply our existing machine vision capabilities in that initial triage and segmentation decision, and not just photoestimating. It could allow us to make even more fine-grained triage decisions based on a much more accurate damage estimate. We can also use those photos to enable more sophisticated review processes of estimates that weren't written through the photo estimating channel. We hope a few themes came through today as we conclude. First, I'll remind again that the 2024 company-wide results John shared and our efforts and claims to help enable competitive pricing starts with our people and culture. They and it are what makes such things possible. Secondly, we remain tirelessly committed and energized to chase that ever-elusive perfect cost curve balance while simultaneously investing strategically to shift it further downward. And we see further opportunities ahead to continue doing just that. And as shared in the photo estimating example, we continue to exploit advanced technology by putting it in the hands of our people because we know they will generate outcomes fully aligned with our progressive core values and claims guiding principles and keep those virtuous cycles turning. On behalf of John and I and 65,000 plus progressive teammates, thank you for your attention.

This concludes the previously recorded portion of today's event. We now have members of our management team available live to answer questions, including presenters John Murphy and Matt White, who can answer questions about the presentation. The Q&A session will be audio only and questions can only be submitted over the phone by pressing star one one on your keypad. In order to get to as many questions as possible, please limit yourself to one question and one follow up. We also ask that you use restraint in reentering the queue to ask additional questions. We will now take our first question.

Thank you. Our first question comes from Michael Zaremski with BMO. You may proceed.

Hey, thanks. Good morning. First question, in John Murphy's prepared remarks, and he set up perhaps to have an even better 2025, I guess, you know, it was good to hear that, but a bit surprising, you know, given that the tail went from pricing to Increases has, you know, looks like it's meaningfully moderated. I don't know if you want to comment on where pricing is roughly, but it looks like low single digits at best. So I thought it was fair to assume the combined ratio mean reverts higher. And, you know, also the frequency tailwind you guys received as well in the industry in 2024 seems like that was much better than a normal year.

Yeah, I mean, I can comment overall on pricing. And if you want to add anything, Pat, you can. I feel like we are in a really great position pricing-wise. And we're in more of the position that we have wanted to be in the last several years when I've talked frequently about small bites of the apple. So we've taken rates up slightly in a handful of states. We've taken rates down slightly in a handful of states. And that's really where we want to be, to be able to allow our product managers to to tweak as needed to make sure that we reach our target profit margins. And then, you know, we obviously want to grow and grow as fast as we can. So we always are balancing those. So we feel really good about our pricing and we'll continue to watch it very closely. And we believe when we believe we can grow more that we want to let out. Some of that in terms of rate decreases like we did in Florida will do so. But we feel like we are in a really, really good position. And starting 2025, I think just in a position of strength with all that we have done. And I have to take this moment. to thank the 66,000-plus progressive people of what we accomplished last year. It was a volatile year before, you know, as we headed into 2024. But the fact—and John, you know, referenced it—the fact that we grew premium 21 percent to nearly $75 billion Added 18% in PIFs, 5.3 million additional PIFs in an 88A is really nothing short of phenomenal. But more importantly, that we did it with great results of our culture and engagement scores. And all those together are really difficult. It really takes a team in unison reaching for the same thing. And of course, everything's based on our core values. Thanks, Mike. Mike, also, I wanted to comment, I appreciated your in-depth Florida piece. That was good reading.

Do you guys want to add anything?

I appreciate it.

Can I ask one quick follow-up?

Sure can.

On policy growth seasonality, historically, you know, this time of the year, exhibits faster growth. Any comments on whether that would or wouldn't be the case in 25, just given, you know, I feel like the dynamics of the cycle is, you know, they're always a bit different.

Yeah, I think, you know, typically first quarter is higher. You've got, you know, tax tax payments dropping. So people shop. You saw the 18 percent PIF increase in our January results. So we feel good about our growth, you know, our intended growth in the first quarter. You know. We spent a lot on advertising last year, especially in the second half, and a lot of that was because we saw an opportunity to gain share, especially when our competitors had not quite priced in like we had more quickly, I think, than others. And so basically we'll have to let that play out. We're going to grow as fast as we can and do so to get to our target profit margins. But, yes, I would say typically first quarter is a pretty big shopping season, especially in the private passenger auto part. of the business.

Thank you.

Thank you. Our next question comes from David Motomaden with Evercore ISI. You may proceed.

Thanks. Good morning. Trisha, I just wanted to talk a little bit about your appetite for continuing to ramp the advertising spend. And I think In August, you had noted that the cost per sale was about, I think it was like 25% below your targeted acquisition costs. Wondering where that is today and what sort of runway you think you can continue to increase ad spend to capitalize on the growth opportunity?

Yeah, our CPS and TAC are much closer than that now because of what we have spent. And we also did invest in Q4 in some delayed response ads. So we did something that we called progress isn't overnight. And so those are things that we think about that really increase our brand and our presence in terms of, you know, hopefully retention. So those are a little delayed response. So we're a little bit tighter now. You know, we were actually talking about this before the call. You know, we look at our budget for media at the beginning of the year. And we work with Pat's team on upfront buys and things that we know we need to put into the system that we have to be very thoughtful about for the year. And then we have a lot of ability to flex both ways. And you've seen it both ways. And we've butted up against our 96. And you saw it last year when we were able to spend more. So that's how we're going to look at it this year. We're going to continue to spend to the efficiency. We obviously want to keep CPS below TAC. It's a little bit closer now. And a lot of it depends, too, on what competitors do. And if they're in the auctions, if they're spending more, they're spending less. So we're just going to react really quickly to all of those things like we have in the past.

Got it. Thanks. That's helpful. And then for my follow-up, yeah, I noticed that the policy life expectancy continued to tick down. This quarter sort of has been moderating a bit. But I think if I look at the comps, they're pretty high comps a year ago. Could you just talk through how you guys are feeling on the retention side of things? Because it feels like the new business is definitely robust, but some of the retention numbers have been moderating a bit.

Yeah, you're spot on with that. And obviously, you know, retention is such a big piece of our growth and really sort of the holy grail. We're not surprised because of the rate increase we have taken over the years that retention has dipped. You know, we're hopeful that it'll make a turn. It started to turn on the trailing 300 commercial auto. So, yeah, it's never great to have our PLEs go down either on a T3 or T12. We're working diligently, and you heard a little bit about that from John Murphy in terms of just making sure that we have this near-perfect balance of our claims guiding principles. And what we know is when people have a claim, they're more likely to stay because of the service we give them when we look at it from an NPS perspective. So what I would say is we're going to work diligently on turning that around. I think one of the biggest things you can do is have stable rates for your customers. You know, with all the things that have happened from an inflationary perspective, people are shopping. It's easy to shop. And there's a lot of shopping going on still. So if we can keep these prices stable, I think that is really a key when you get that renewal rate and you don't have to shop because it's stable or in some cases even going down. So that's really where we're at now. We obviously want that to improve for our overall growth.

Great. Thank you.

Thank you.

Thank you. Our next question comes from Christian Getzoff with Wells Fargo. You may proceed.

Hi. Good morning. So it's been very topical just to talk about, like, the tariffs, and I think your calls obviously lined up with it kind of going to effect today. So have you guys sized the potential impact on margins? It seems like it's going to be more of a second-half story, but I guess how are you kind of balancing – growing as fast as you can with something that's going to potentially push loss costs up in the second half? I guess, where do you find the balance between the two?

Yeah, super relevant and timely question. And clearly, typically, tariffs are a one-sided risk to our loss costs. So yes, we've been thinking about that a lot. And in fact, our pricing team is working with our economics team at PCM, and they have been for a while to understand the implication of of tariffs. And so we have a lot of, I'm not going to share with you the raw data, the assumption we use, but I will tell you about three weeks ago, I was reading through some of the materials they're putting out and it's evolving every day. And I called Pat to say what incredible work these two groups were doing and just really diligent. So, yeah, we actually have what we think at this time percentages would be on certain if certain tariffs happen. Now, those will ultimately change and we'll be able to kind of flex our models. It'll depend on the countries, the products, the magnitude of severity. But ultimately, we will price those into our indications. There's a lot of, I think, puts and takes, too, as things have unfloated. So with the tariffs that went into effect today, we'll have to think about new car prices. Do those prices get passed on from the OEs to our customers? What does that mean to values? Obviously, from both Mexico and Canada, we get a lot of our prices. parts to repair cars. And so when will those play out? I do agree with you. I think if things go as planned, I think it'll be more second half and into 2026. And then there's some other things we're thinking about that we're modeling. And that is if there's tariffs on oil, does that increase gas prices? Does that make people drive less? Does that change frequency? Even with immigration, is there a talent shortage in the body shop industry that happened a This morning, it looks like there might be some additional tariffs on lumber for Canada at a minimum. What does that do to home prices and, of course, home repair prices? And we've modeled that in as well as what I talked about with fixing cars. So we're modeling all of that together. And a lot of it will depend on how much inventory is out there. And then if you think about the future, and I'm always trying to think about second and third order effects. If you think about the future, and I was watching CNBC this morning, I thought, well, if we want to have more of our lumber that starts here in the United States, then we're going to need to build more sawmills. That can't happen overnight. But what does that do to trucking and loggers? And so it could be It could be a tailwind in terms of our commercial lines organization because that's very much based on macroeconomic data. But here's where we're at. We have a bunch of models. We're able to flex those models every time we get a new piece of data or the data changes. David, my GC, and his team are reading through all the executive orders and understanding how that affects us. And, you know, when there's disruption in pricing, we are really good to react really quickly, and you've seen that. And probably the last thing I'll say on this is that we are sitting in a good position because right now our margins are below our 96. So we're sitting on some margins so we can kind of play this out as things evolve.

Great. Thank you for the holistic response. And then for my follow-up for the ad spend, so It kind of sounds like it'll be maybe not to the same absolute dollar amount, but it sounds like the seasonality on the ad spend, because you typically spend a little bit more in the first half, it sounds like it'll continue to be kind of like spread out as we go through the year. And I understand there's some uncertainty with the tariff, so that could change drastically. But is it kind of right to think about in terms of the seasonality and ad spend seasonality kind of continuing to be skewed just given the higher customer shopping?

I mean, yeah, for the most part, we will spend when people are shopping and people have typically shopped in the quarter. But we're going to be really flexible to see what plays out. A lot of it isn't just what we're doing. It's what the competitors are doing. So like last year, we had a budget and then we increased it based on the opportunity to gain share when we could. So So that's the great part about the flexibility. We don't have a budget where we say we have to spend this much or it's gone the next year. It's flowing and it changes depending on the needs of our growth and watching what the competitors are doing and watching what's happening in pricing overall for both media spend as well as just overall pricing. You know, we're flexible, is what I'd say, as we talk about this all the time, what we need and why we need it. And we're going to try to reach our main objective, and that is grow as fast as we can at or below a 96.

Great. Thank you.

Thank you.

Thank you. Our next question comes from Joshua Shanker with Bank of America. You may proceed.

Yeah, good morning, everybody. I'm going to ask a similar question, maybe in a different way. If I look at the ad spending, it seems like you spent more in 4Q than you spent in 3Q. And the PIF growth, you know, slowed down in November a little bit, and then much in December, as we expect, is normal. That's the seasonality of it. But you talk about this, I guess, delayed response advertising in some ways. How does it work exactly? And, you know, if we look at, you know, how should we compare Add spend to PIF growth. What's the relationship there?

Well, we look at, when we spend, we look at a measure, take the delayed response out. We look at a measure called NP6, which is new prospects that are shopping new in the last six months. And we look at NP6 and how that increases. So we know people are shopping and we know they're active. So that's how we look at that. And of course, we look at our targeted acquisition costs and our cost per sale. So we look at all that together and that's for the immediate response. For the delayed response, and this is something slightly new, and John Murphy talked about it during his slides, we have a new purpose statement that we developed a few years ago. And we started what we call our anthem, and that is progress isn't overnight. And we spent some money on that in the fourth quarter, which we... you know, it's going to be harder to measure, and so we have some different measurements in their longer term. I'll probably be able to share this with you once we have them because they'll play out, but that's how we think about those two differently. Do you want to add anything, Pat? Are you good? Good. Thanks, Josh.

And then on claims, is there any evidence or numbers you give about cost per claim that the efficiencies you're building in are delivering a cheaper cost per claim than it would have been a year earlier under the same circumstances. I think back 15 years ago when you added the claim centers, this was a goal that the same claim could be satisfied more cheaply. Are there any statistics or confidence you have around your ability to resolve the same claim cheaper with the same input costs?

Yes, we have a lot of data and care deeply, obviously, about our LAE, but we look at cost per feature for claims. We look at features per day per FTE. So when you're thinking about what goes into all the different claim features, it's really getting it to the right person at the right time. And if we can do that throughput, that's going to be much more efficient. And as long as accuracy is still great, then that's what we care about. So we look at a lot of, actually a lot of data across the board. My team and I talk a lot about efficiency. And when I think about that, I think about it from a non-acquisition expense ratio. But how can we continue to get efficient? Because competitive prices is one of our strategic pillars. And so we have to continue to push that cost down. And of course, the curve that John showed, we want to continue to push that down and to the left.

Well, thank you for taking my questions.

Thank you.

Just a reminder that if you'd like to ask a question, you may press star one on your phone. Josh will take your last question.

Thank you. Our next question comes from Andrew Anderson with Jefferies. He may proceed.

Hey, good morning. Could you maybe talk about any changes you're seeing in bundle rates, and perhaps it would be helpful to break it down between in areas where you are growing the property book and areas where you're de-risking?

Yeah, that's a great question. We've been talking a lot about this and we refer to this in the annual report documents when we talk about our blueprint for the future. And so it's a good time, I guess, to step back a little bit. And I'm going to read you our mission statement for property because this has really been evolving and it's really important and bundle is a big piece of it. So our mission statement is progressive home primarily offers products for owner-occupied property bundles with progressive auto. So that is going to be, where permitted, the main thing we're going to have. We will restrict business coming in where we can to have it be home bundle, whether it's condo or home. We will build a diverse portfolio of products with partner agents who understand our underwriting strategy and proactively support it. When capacity is limited, will we use that capacity for bundles written with our partners in the agency channel? So that's the overarching mission statement. So we'll be referring to that over the next few years as we continue to have our blueprint for the future. Of course, first things first, we have to get the rate we need. So we had a rate in the system in 2024, and that will continue into 2025. Meanwhile, balancing that out with investments we're making in 2021. people, processes, IT, segmentation. And then we have the blueprint that talks about bundling, which I just talked about. We want to accept new business with auto home bundled, where permitted. We've talked, I think, a couple of times about Exiting the DP3. So we've exited in 44 states. And that is, I think, rental properties. And then really agent alignment, holding our agent partners to volume and quality bundles. And we have very specific expectations for our agents. And then, you know, we have to cost share with our insurers. Insurance, home insurance shouldn't be a maintenance product. So we cost share with mandatory wind and hail deductibles. And then what we call roofing materials payment schedule. Think of a sort of a sliding scale. on, um, roof depreciation as the roof ages. And then of course you've, we've talked a lot in the last couple of years about, um, de-risking and making sure that our portfolio across the board. So while I'm not going to share specifics of bundles, um, the majority of our, um, our homes are bundled with our auto. I will tell you that much. And I think probably, you know, another data that I won't share either, but it's, it's a very high percentage and, uh, uh, much a very much a majority is how many of our rental policies are bundled with auto. So think of what we call future Robinson. So these are people that are already bundled with us. And as they do buy a home, the next step would get to be progressive home and their auto. So that's that's a reason to believe in the future that will continue to bundle more auto and home. And there's a lot in the pipeline for us as we grow.

Thank you. Maybe just going back to tariffs, I suppose you can't prospectively reflect it in pricing, but the extent to which you start to see it, how many quarters or periods would it have to take before you would kind of be allowed to reflect that in a rate filing and have it be approved?

Well, it's a little bit different in different states. But as soon as we see the data, we try to put that into our pricing indications. And that, of course, is state by state. And then we work. There's different regulations in different departments. We work with each department to get that in there as soon as possible.

So it could be relatively quickly, I suppose, once there is an impact.

As soon as we see it in our data, we're able to present it to the departments of insurance to try to get the necessary rate.

Great. Thank you.

Thanks.

That appears to have been our final question. So that concludes our event. Josh, I will hand the call back over to you for the closing scripts.

That concludes the Progressive Corporation's fourth quarter investor event. Information about a replay of the event will be available on the investor relations section of Progressive's website for the next year. You may now disconnect.