Progressive Corporation (The)

Good morning, and thank you for joining us today for Progressive's second 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, quarterly reports on Form 10-Q, 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. Introductory comments in the presentation were previously recorded. Upon completion of the previously recorded remarks, we will use the balance of the 90-minute schedule for this event for live questions and answers with 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 31, 2024, as supplemented by our 10-Q reports for the first and second quarters of 2025, 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'm pleased to introduce our Personal Alliance President, Pat Callahan, who will kick us off with some introductory comments.

Pat? Good morning, and thank you for joining us today. Through the second quarter, 2025 continues to be one of our best years on record by all objective measures. We delivered strong profitability while simultaneously growing at an incredible pace, adding over $5 billion in premiums written and nearly 2.4 million additional PIFs during the first half of 2025 compared to the first half of last year. We've previously said it's easy to grow an insurance company if you're not focused on underwriting profit, and conversely, relatively easy to generate profit in insurance if you're not looking to grow. But simultaneously doing both while operating in the highly competitive US P&C marketplace requires the rare combination of strategic focus and relentless execution that we consider key sources of progressives' competitive advantage. Full statutory industry results released in June show that Progressive gained more than 1.5 points in personal auto market share in 2024, while outperforming the industry combined ratio by more than 7 points. Our 2024 market share increase was the largest share gain of any carrier in the past 15 years. This rare combination of profitable market share growth isn't an isolated event for Progressive. Over the past 15 years, we've increased our auto premium almost five-fold, while simultaneously running close to nine-point wider underwriting profit margins. Our performance is the direct result of executing against our four strategic pillars – people and culture, product breadth, brand, and competitive prices. Today, we'll focus on competitive prices and provide you with some insights into how our ability to predict and price to future loss costs and to rapidly deploy products and pricing to match our premiums to our costs remain key ingredients of our continued success. The compounded effect of doing this with each successive product model has enabled us to continue to make great progress towards achieving our vision of becoming the number one destination for consumers, agents, and business owners for insurance and other financial needs. Building on our exceptional underwriting profit performance, we continue to invest to drive continued growth. Despite seeing greater competition now than we did at the beginning of the year, Through the second quarter, we continued to see strong demand for our personal auto products across both of our distribution channels. The independent agent channel is a great barometer for the competitive environment, where available coverage options across carriers are presented via comparative raters, which provide agents and their clients real-time comparisons of how our products compare to those offered by other carriers. Every indication is that our auto products have continued to outperform on a relative basis, as evidenced by strong, year-to-date double-digit growth in new applications, premiums written, and policies in force. On the direct side, our marketing engine remains highly effective, generating high-quality prospects at near-record levels, and our conversion rates indicate that despite the increasing marketing spend, Our prices are still highly competitive and provide consumers a good value relative to other in-market options. Year-to-date, we have spent $2.5 billion on marketing, an increase of about $900 million compared to this time last year. And as our volume denominator grows, achieving year-over-year new application growth becomes more challenging. But so far, we have continued to leverage our scale in identifying new opportunities to refine where and how we invest our marketing spend to drive profitable growth. Similar to personal lines, we continue to rapidly grow market share in our commercial lines business while consistently beating industry combined ratios by 8, 10, and as much as 20 points over the last 20 years. This consistent profitability is particularly impressive when looking at how U.S. commercial auto continues to struggle with profitability, producing its 14th consecutive unprofitable calendar year in 2024. Our success can be attributed in part to the intense focus on commercial auto as a core line of business in our commercial lines offering. This autofocus, in conjunction with introducing the segmentation of commercial auto into business market targets more than 10 years ago, has enabled us to capitalize on meaningful and actionable differences between resulting vehicle types and usage that we can operationalize across all aspects of the business. This granular focus has allowed us to quickly develop segment-level insights and execute proactive rate and underwriting actions at the BMT level to deliver strong division-level performance, as we did late last year when we adjusted rates and underwriting across BMTs to drive written premium growth across all our BMTs other than for higher transportation. We're now extending those capabilities to our expansion product lines, like the business owner policy product. To support long-term positive contributions from these newer businesses, we leverage established pricing and product delivery capabilities to ensure we have the necessary monitoring and insights, in addition to leading capacity and the delivery agility to bring rapid rate and underwriting adjustments to market. Leveraging these proven capabilities should help our expansion commercial businesses deliver the profitable growth we expect from all of our underwriting businesses. A significant contributor to delivering our continued profitable growth is the ability to quickly and decisively respond to changes in loss costs to ensure we can remain open for business when inflationary pressures create hard markets and elevated shopping levels. This is no small feat, especially given the lack of historical precedent for some of the drivers of recent lost cost increases. Fast forward to today, and we're similarly working to model first, second, and third order effects of global tariffs and potential supply chain disruptions to determine the appropriate future rate levels for these emerging macroeconomic events. Our pricing teams are responsible for translating highly complex and dynamic internal and external data into timely rate-level recommendations. Each of our product teams are supported by a group of these talented individuals who leverage complex actuarial methods to understand and trend our future costs towards our goal of collecting the right premium to cover both the costs we'll incur and our target profit margin. Today, we'll be diving into the details of our personal and commercial lines pricing theory and practices. To guide us through this, we have two senior pricing leaders with us. First, Brad Grainger, who has been our national auto pricing leader for the past 17 years and who will be celebrating his 25th progressive anniversary later this month, will discuss some of the technical theories behind our pricing methodology. Following Brad, Jen Cubitt, who has been with Progressive for 21 years and recently took on the leadership of our commercial lines pricing organization, will explain how these theories are applied in practice at Progressive. Once again, thank you for joining us today. I'll now turn it over to Brad. Brad?

Thanks, Pat, and thank you everyone for joining this morning. What is our product? A property and casualty insurance company such as Progressive doesn't actually manufacture a physical product. Our product is not tangible. Instead, it is a transfer of risk from insured to insurer, exchanging the small probability of an adverse financial event in exchange for the payment of a premium. That transfer of risk is outlined in our policy contract. And That transfer of risk is both dependent on when accidents occur or the accident date and time bound within our short-term contract lengths of 6 or 12 months. Car accidents are not cornflakes. As opposed to a tangible product like cornflakes, where costs are largely known before the product is priced and sold, Progressive doesn't know for sure what our costs are until long after our product is priced and sold. That is precisely the transfer of risk from insured to insurer I just described, only now, from the perspective of the insurer, that risk is now ours. And as we will discuss in a few minutes, we do many things to mitigate that risk within both our pricing science and our operationalization of getting the right rate to market quickly. Pricing to expected cost. First, when we talk about pricing for costs, we are referring to all parts of our premium dollar. Losses, loss adjustment expenses, or LAE, general expenses, and profits. According to the Casualty Actuarial Society's Statement of Principles on Rate Making, quote, a rate is reasonable and not excessive, inadequate, or unfairly discriminatory if it is an actuarially sound estimate of the expected value of all future costs associated with an individual risk transfer, end quote. A few things to highlight there. First, It references expected value of future costs, where actual outcomes could be lower or higher. Second, it is always forward-looking or prospective, as it is an estimate of future costs. Third, today's presentation will focus primarily on not excessive and not inadequate costs. as opposed to not unfairly discriminatory, which is largely in the domain of our product development departments. This is analogous to the field of economics and the distinction between macroeconomics and the focus on changes in whole economies and aggregate variables and microeconomics and the focus on changes in individual firms and consumers. We will focus today on macro level pricing as opposed to the individual relative risk rating and segmentation of micro level pricing. And in addition to our approach being aligned with actuarial principles, it is also well aligned with state regulation as nearly all states legally require that rates are not excessive, not inadequate, and not unfairly discriminatory. And it also fits quite well within Progressive's vision to be consumers' number one choice via competitive rates. But to do so by growing profitably and adhering to our core value of profit. The fundamental pricing questions. There are two questions that completely underlie our approach. Number one, if we don't do anything to current rates, what loss plus lae ratio should we expect in the upcoming rate revision for the policies we are about to write and number two what do we need to do to current rates in order to hit our combined ratio target in the upcoming rate revision for policies we are about to write we refer to these as the fundamental pricing questions And in the coming slides, we will build the fundamental pricing equation to answer these questions. Actuaries develop predictions that minimize bias and variance. An enormous competitive advantage that Progressive has is the quality, granularity, and quick availability of data. Our growth and scale have only deepened that advantage. But if you don't think you have a blind spot, then you have a blind spot. And with all of this quality data, if we are not careful, we could slice the cake and slice the cake and slice the cake until all we have are crumbs. This is where we, in our pricing organizations, come in. Actuaries are experts in matching rate to risk, balancing responsiveness and stability, and maximizing accuracy and precision. And as we will see in the coming slides, as we try to price this accident year promise, our data is trying to fool us. There is no single perfect piece of data. Our work centers around correcting for bias or accuracy and spread and variance or precision and finding signal through noise. And bias, as used here, refers to statistical bias. From Wikipedia, quote, end quote. Every month, Progressive releases financial information publicly describing our underwriting performance by line of business. To align with generally accepted accounting principles, this is predominantly a calendar year or month view that includes incurred activity on all losses and LAE, regardless of date of occurrence. For the purposes of rate making, however, we are attempting to price for the accident year, that is, ensuring that we have the correct rates at the time the accidents occur, which I'll explain further in the next few slides. Calendar year incurred losses are a combination of paid losses and change in reserves. They can also be subdivided to show contribution to that calendar year of current accident year versus all prior accident years. We will now use a historical example derived from a progressive personal auto state comprehensive coverage to demonstrate how we can effectively answer the fundamental pricing questions. All amounts are in thousands of dollars. The first piece of data we readily have is trailing 12 calendar year incurred losses of $43.24 million. As we just stated, calendar year incurred losses can also be subdivided to show contribution of current accident year versus all prior accident years, as can be seen here, as we see the same paid loss plus change in reserves pattern for both the current accident year and all prior accident years. We will now use our simple example to fill in values for each element of the formulas. And in this example, when we isolate the contribution of this accident year to the current calendar year incurred losses of $43.24 million, we see that the current accident year incurred losses are $43.56 million. The other element of calendar year incurred losses is the contribution of prior accident years, also known as prior accident year runoff, which in this case is negative $327,000. The $43.56 million is current accident year losses is what we need to start to answer the fundamental pricing questions unbiased ultimate accident year losses equal accident year incurred losses times loss development factor loss reserving's goal is to set financial reserves to be adequate with minimal variation from date of loss until final settlement we examine the development over time of historical accident year losses as claims are reported and settled across the columns of a loss development triangle, as can be seen in the upper right. That is known as a loss development factor. In this case, the reserves set by claims and loss reserving have historically been adequate. In our example, that loss development factor is then slightly less than one at 0.99. At this point, we can also bring in another piece of data that we readily have. Trailing 12 calendar year earned premium of $61.14 million. Loss adjustment expenses are correlated with losses. Loss adjustment expenses can be divided into defense and cost containment, or DCC, which is defense, litigation, and medical cost containment expenses, whether internal costs or external fees, and adjusting and other, or A&O, which is adjusting and other overhead expenses, whether internal costs or external fees. Both can change in the short-term and long-term depending on a number of factors, including attorney representation rate, statutory and regulatory changes, changes in efficiency in our claims organization, among other possible causes, but in general, tend to move with losses. In this example, we have selected LAE to be 12% of losses. A portion of our costs are mean reverting, Forecasting elements of the fundamental pricing equation deals with two distinct forms of time series. First, time series with stationarity, the graph on the left. This series tends to revert to a historical mean and requires a longer experience period to provide an effective future forecast. Weather is a prime example of where this approach is warranted. Care must be taken to decide whether such historical mean needs to be slightly adjusted going forward due to environmental changes in our future pricing period. Time series without stationarity, the graph on the right. That series does not revert to a historical mean. It is dominated by trend and seasonality. We will discuss this further when we examine frequency trend severity trend, and premium trend. In this example, the last year contained $14 million of wind flood hail losses, well above our long-term expected average. Therefore, restating to the long-term expectation implies a weather factor of 0.926. For commercial lines, An additional area where we must consider this paradigm of reversion to the mean is in treatment of large losses. As with weather, care must be taken to decide whether such historical mean needs to be slightly adjusted going forward due to environmental changes in our future pricing period. Frequency and severity of losses change over time. What changes each over time? Essentially, this is time as a segmentation variable. It helps to separate the multiplicative components of losses as the drivers of each can be different. Frequency is the probability of having a claim. Severity is the dollar amount of the claim itself. Factors that can affect frequency include vehicle technology, safety laws, product mix, For example, deductibles or tier, statements, new business growth, retention, weather, seasonality, underwriting and billing. Apart from the magnitude of the trend itself, the number of months that we need to trend is important too. That is a function of time to price, file, get approval and elevate, policy term and and rate revision length. Remember the bullseye slide from earlier? The precision of our estimates declines, meaning we have a greater spread the further into the future we have to estimate. That is of particular importance in commercial auto as they have a preponderance of annual policies, which increases the number of months into the future we must trend. In our example, we have estimated frequency trend to be plus 1% annually. That needs to be applied for approximately 16 months from the midpoint of the historic period to the future average accident date of our prospective pricing period. The faster we can analyze our data, the shorter we can make our policy terms, and the more frequently we can elevate rate revisions, the fewer months we need to trend and the more we can reduce spread of outcomes and increase precision in our forecasts. The process is similar for severity. Factors that can affect severity include vehicle technology, safety laws, product mix, for example, limits, state mix, medical inflation, used car values, car part inflation, body shop labor rates, weather, seasonality, claims staffing. In our example, we have estimated severity trend to be plus 7% annually. As with frequency trend, that needs to be applied for approximately 16 months from the midpoint of the historic period to the future average accident date of our prospective pricing period. The further into the future we have to estimate, the wider the spread of future possible outcomes. Progressive changes rates frequently. Remember, the fundamental pricing equation is working towards answering the fundamental pricing question of determining what we need to do to current rates. Progressive changes rates a lot. Consequently, Any recent historical period of earned premium will include premium written at varying rate levels. This phenomenon is further exacerbated by the presence of varying policy terms, six months and 12 months. So, we need to adjust this historical premium entirely to today's current rate level. In our example, we have elevated two rate decreases in the last year. That means our current rate level factor is 0.958. Controlling for the effect of product mix shifts on loss trend. A frequency or severity trend that is caused by a product mix shift will not necessarily mean our rate adequacy position, as seen by our fundamental pricing equation, will shift. For example, Progressive has been shifting to Robinsons for several years. In isolation, what would we expect to happen to frequency and severity of losses? Frequency would decrease significantly due to more lower risk drivers in our book. Severity would increase for liability coverages due to higher purchase limits of liability. Overall, losses per exposure would decrease as the frequency decline would overwhelm the severity increase. But we would also be collecting less premium per exposure as we charge less for Robinsons per exposure. We control for the effect of product mix shifts on our frequency and severity via premium trend, which measures changes in average earned premium at current rate level over time. We must put all premium at a common rate level as only looking at changes in average earned premium over time would be confounded by progressives' frequent rate changes. The graphs of bodily injury earned premium on this slide illustrate this. While Progressive's average earned premium per exposure has increased due to our rate increases in recent years, the average earned premium per exposure when controlling for that, i.e., at current rate level, has declined. The net effect of the rate increases and product mix shift is still to have increasing bodily injury average earned premium per exposure. And therefore, a product mix shift will not necessarily mean our rate adequacy position would shift. It would only change if we are shifting into a part of our book that has a different relative level of profitability. If we are shifting into a part of our book that is less profitable, the rate need as indicated by the fundamental pricing equation would go up as frequency slash severity would rise more than premium and we would need more rate. If we are shifting into a part of our book that is more profitable, the rate need as indicated by the fundamental pricing equation would go down as frequency slash severity would rise less than premium. and we would need less rate. In our example here, in contrast to the graphs of progressive bodily injury, annual premium trend is actually positive at plus 5%. And like frequency and severity trend, that needs to be applied for approximately 16 months from the midpoint of the historic period to the future average accident date of our prospective pricing period. What target loss plus LAE ratio would meet our underwriting profit target? First, we determine a forward-looking estimate of expense ratio. Second, we work backwards to determine our target loss ratio, which is equal to 1 minus the expense ratio minus profit. In our example, expense ratio is 17.7% of premium. Together with our profit target of 4%, our budgetary loss plus LAE ratio is 78.3%. Some elements are correlated. While we have detailed the elements of the fundamental pricing equation individually, we do not assume the correlations do not exist between elements. Some examples are losses and LAE. Premium trend or product mix and frequency trend. Premium trend or product mix and severity trend. LAE and severity trend. Loss development factors and severity trend. Premium trend or product mix and expenses via the budgetary loss and loss adjustment expense ratio. Understanding these patterns can inform our predictions of each element and improve accuracy and precision of the fundamental pricing equation. Balancing responsiveness with stability. Remember the bullseye diagram from earlier? We always seek truth but observe data, which is truth plus random noise. Credibility, also known as the crown jewel of casualty actuarial science, helps us ultimately deliver the best minimum variance unbiased estimate, or as close to the bullseye pattern in the lower right-hand corner as possible, and allows us to slice the cake optimally to balance responsiveness and stability and achieve forecasts that minimize both bias and variance. We want to emphasize recent data such that random noise is kept to an acceptable level. And we want to emphasize that recent data because it is closest to what we can expect in our future pricing period in terms of our book of business and the external environment. But there can be a trade-off there as that data can be thinner and noisier, and we need to make adjustments to account for that noise. Credibility is a number between and including zero and one that we use to weight our data. The higher credibility is, the more weight we attach to our data in the fundamental pricing equation. A sample of experience reaches full credibility, so credibility equals one. If we have enough claims that 90% of the time our experience is within plus or minus 5% of the true value, that standard for full credibility for each coverage is determined through complex actuarial formulas and increases as the variability of experience increases. In our example, The standard for full credibility is 4,559 claims. We have over 27,000 claims in our experience period. So we have full credibility and credibility equals one or 100%. Our growth and scale has significantly enhanced our credibility and our ability to best react to changes in our environment. And in general, for personal auto, We have achieved that full credibility with one year of data in the overwhelming majority of our state channel coverage combinations. We now have developed the fundamental pricing equation where we can answer the first fundamental pricing question. If we don't do anything to current rates, what loss plus LAE ratio should we expect in the upcoming rate revision for the policies we are about to write? So that's our experience loss plus LAE ratio. We can also answer the second fundamental pricing question. What do we need to do to current rates in order to hit our combined ratio target in the upcoming rate revision for policies we are about to write? That's our experience loss plus LAE ratio divided by our budgetary loss plus LAE ratio. And one final step, is to weight our estimate with a complement via credibility. So the experience loss plus LAE ratio divided by the budgetary loss plus LAE ratio times credibility plus a complement of credibility times one minus credibility. The complement is an alternate estimate of rate need apart from the fundamental pricing equation that augments the fundamental pricing equation with an estimate of future net trend. In our example, we use a complement of credibility of plus 2.4%. The final product is what we refer to as a credibility-weighted rate level indication. Here, that is plus 1.3%. This concludes the theory of pricing. As you can see, it's complex with many variables and considerations and thus many ways to go astray. This is really, really hard to do successfully. We have been at this for decades, and combined with the availability, quality, scope, and size of our data, it is really, really hard to replicate this at our scale. And to be as accurate and precise as possible, when we apply this theory in practice, we have many additional considerations, which Jen Cubitt will discuss in the next section. Jen?