Accelerant Holdings

Hello, everyone, and welcome to Accelerant fourth quarter and full year 2025 earnings call. Please note that this call is being recorded. After the prepared remarks, there will be a question and answer session. If you'd like to ask a question during that time, please press star and then one on your telephone keypad. Thank you. I'd now like to hand the call over to Ahmed Olyakoubi, Investor Relations at Blue Shirt Group. Please go ahead.

Good morning, everyone. Welcome to Accelerant's fourth quarter 2025 earnings conference call. Joining me today to share our results are Jeff Radke, Accelerant's co-founder and CEO, Jay Green, Accelerant's CFO, and Ryan Schiller, Accelerant's head of strategy. Their remarks will be followed by a Q&A session. We ensure that press release and presentation concerning our financial results for the fourth quarter of 2025 yesterday and they are available on our investor relations website. Before we get started, I would like to remind you that our remarks today will include forward-looking statements, including those regarding our future plans, objectives, expected performance, and in particular, our guidance for 2026. Actual results may vary materially from today's statements. Information concerning risks, uncertainties, and other factors that could cause these results to differ is included in our SEC filings. including those stated in the risk factor section of our filings with the SEC. These forward-looking statements represent our outlook only as of the date of this call. We undertake no obligation to revise or update any forward-looking statements. Additionally, the matters we will discuss today will include both GAAP and non-GAAP financial measures related to both our consolidated results as well as our operating segments. Reconciliation of any non-GAAP financial measures to the most directly comparable GAAP measures is set forth in our earnings release. Non-GAAP financial measures should be considered in addition to, not as a substitute for GAAP measures. Finally, today's conference call is being recorded and webcast. Now I'll turn the call over to Jeff.

Good morning. Thank you for joining us to discuss our fourth quarter results. We had a fantastic quarter. beating our expectations on exchange-written premium, third-party premium, and adjusted EBITDA. All of these figures were in line with our pre-released results. Like last quarter, in addition to our earnings press release, we provided a presentation with more detail on our company. We also filed our first Form 10-K last night. All of these materials can be found on our investor relations website. Let me start with the topic that is on many of your minds, artificial intelligence. AI is the architecture of our business. It is embedded in how we operate and how we win. From our founding, we designed our platform to capture, structure, and continuously learn from specialty risk data at scale. And I'll be direct. The more AI transforms the insurance industry, the more it plays to our strength. We've built what we believe is the largest proprietary, decision-ready data set in specialty commercial insurance. We use that data to power algorithm-aided underwriting at scale, and we distribute that advantage through the most technologically adaptive segment of the market, MGAs. Everything we are about to describe flows from three structural advantages. First, our proprietary usable data Next, algorithm-supported underwriting. And last, technologically adaptive distribution. Let's start with the first. Our moat is our proprietary decision-ready data. We have assembled 134 million rows of specialty insurance data across 58,000 unique attributes. All of it is proprietary. But data alone is not the differentiator. Usable is the critical word. Our position in the value chain allows us to stitch together upfront underwriting submission data with the claims outcomes on the back end. That seems obvious, but it is rare for one entity to have this ability. That closed feedback loop, submission to binding to loss emergence, is what transforms raw information into decision-grade intelligence. We don't think anyone else can do that across a multitude of independent MGAs and 600 plus different specialty products. We then augment this proprietary data with third party data to further enhance our understanding of risks. The combination is powerful. Internal performance link data layered with external enrichment. No large language model or AI startup is going to have that kind of data. and we're adding more and more each day. The difficulty of building this kind of infrastructure should not be underestimated. Industry modernization efforts have struggled to connect and synthesize data across multiple different systems. Our platform was architected from inception to do exactly that. In fact, 34% of our workforce consists of engineers, data scientists, product managers, and designers. Experts that are focused on building and honing our platform. And as AI capabilities increase, the value of our data set compounds. In a world where models will be increasingly commoditized, differentiated data is the durable competitive advantage. And every submission, every underwriting decision, every claim flowing through the risk exchange deepens that advantage. Our second structural advantage is our engine. Data alone does not create value. It must inform decisions. The set of tools that we have developed mutually support one another to form an end-to-end engine. We deploy risk scoring models, AI risk ingestion, and real-time portfolio monitoring to optimize underwriting performance. As an example, just last month, we uploaded a portfolio of 1,679 new risks. And in just over a minute, our engine told us that 84% of those risks were in appetite. 9% needed underwriting review given specific concerns identified by the tool. And 7% were simply out of appetite. The engine then went on to draft exclusions and coverage specifications to optimize underwriting performance. That achievement is monumental. That would have taken a team of people at least a week. And that's how we continue to win in the market at increasing scale. Our engine provides tangible advantages for Accelerant and its members in three ways. Upfront underwriting precision, real-time portfolio management, and claims optimization. Let's dive into specific examples of each. Upfront underwriting precision. We identify complex, non-obvious relationships across variables like financial health, industry stresses, crime indices, prior loss patterns, and we integrate all those insights directly into the member underwriting workflows. That enables more precise risk selection and pricing. It also helps us to systematically avoid loss-driving outliers. That is a powerful combination. Proprietary, data-driven AI-enabled tools pushing profitable growth while avoiding poorly performing micro segments. That is how, based on our onboarding data, after the risk scoring models have done their work, members see a two to three point average improvement in their gross loss ratio while growing at a rate over 35% since inception. The second advantage is real-time portfolio management. We ingest member data as it is created and monitor performance continuously. That allows us to detect deterioration earlier, protect underwriting margin, and identify attractive growth opportunities. That's how we maintain a loss ratio in the low 50s. Finally, claims cost optimization. Our predictive analytics prioritize claims handling and surface subrogation opportunities, reducing loss creep and preserving profitability. Since inception, we saved our risk capital partners at least $100 million of loss using this capability. In total, the trajectory is clear. Underwriting is becoming increasingly autonomous. We've been building towards that shift for years. Whether underwriting is executed by members using our tools or as is happening increasingly automated within the platform itself, the risk exchange remains the infrastructure that evaluates, prices, and aligns capital. Strategically, that means that Accelerant wins regardless of who originates the business. Every policy bound and every claim resolved strengthens the model and improves the next decision. Our third structural advantage is our technologically adaptive, decentralized MGAs. From the very beginning, we have focused exclusively on MGAs because they are more agile and faster at adopting technology than traditional insurance company incumbents. And AI enhances that advantage. Members on our platform gain access to capabilities that would be difficult and expensive for them to build independently. With our help, they achieve faster submission triage and quoting, AI-driven coverage recommendations, enhanced risk selection tools, real-time portfolio insights, and lifecycle management, policy to claim. Today, our members can ask Accelerant AI, what's driving my loss ratio? And they can track the tool's reasoning to identify key performance drivers and unlock unseen opportunities. MGAs are entrepreneurial specialists operating in defined niches. That means that when Accelerant empowers its members with improvements in underwriting precision and faster response time, it translates directly into market share gains. And anything we can do to make our members better makes us better. So what does this all mean practically for our business? First, We can due diligence potential new members more quickly and completely. Our tools enable us to analyze their books of business and design underwriting guidelines in 20% of the time that it would take us to do so manually. The move from prospect to producing member takes half the time. When we onboard over 50 members a year, that makes a big difference. Second, once onboarded, those members grow more quickly. with 25% underwriter productivity uplift emerging in our initial efforts. Third, we can lower loss ratios for our risk capital partners, delivering more predictable underwriting performance as we grow. That is highlighted by our attractive loss ratio track record. The future of specialty insurance will be data rich, near autonomous, and capital efficient. AI enables accelerant specialized underwriters to win even more in their markets and moves capital closer to origination. What's the impact of all this? When data, underwriting intelligence, and capital alignment are integrated into a single infrastructure layer, that layer becomes disproportionately valuable. Our exchange services segment already reflects the operating leverage of that architecture. with near 70% EBITDA margins, driven by near zero marginal costs on incremental data and recurring revenue economics. And as automation increases, those structural advantages become more pronounced. Before leaving the topic of artificial intelligence, let's take a step back. At Accelerant, we set out to make the specialty insurance market work better for everyone. We believe the risk exchange is fulfilling that mission more quickly and completely because of the three structural advantages AI gives us. Turning back to the quarter, for those newer to our story, the risk exchange is a two-sided platform, the supply side and the demand side. The supply side is driven by the specialty underwriters, our members, who underwrite specialty insurance policy. These policies fuel our exchange. The demand side consists of our risk capital partners, comprised of insurance companies, reinsurance companies, and institutional investors. Those risk capital partners pay us a fee for access to our portfolio policies. We sit in the middle, sourcing members, monitoring them, and helping them to grow profitably by leveraging our AI advantages I just described. We leverage the scale of our accelerant platform to deliver technology to our members that they would struggle to develop on their own. As discussed, our engineers and data scientists are developing agentic solutions for our members and for internal use in the risk exchange. These solutions help members grow more quickly, reduce their loss ratios, and thus increase their profits. Our members value these tools and services. which is why we've consistently had an industry-leading 80s plus net promoter score. And Accelerant's reputation as the preferred partner for the best MGAs in the world is what drives the growth in new member MGAs joining quarter after quarter. For the demand side, we create value by sourcing, managing, and monitoring a high-quality portfolio of insurance policies. Why is our portfolio business so valuable to our risk capital partners? Well, it's stable, diversified, and highly profitable. You can best measure that using gross loss ratio, which has been in the low 50s. That attractive loss ratio leads to consistent and attractive returns for our risk capital partners. With that overview complete, let's talk about the KPIs that we saw this quarter. Now, last quarter, I set out the six key metrics that track the health of our business. During the fourth quarter, all six of those metrics were better than we forecasted. On the supply side, the first KPI is exchange written premium. Exchange written premium was $1.1 billion for the quarter. That's 24% year over year growth. Recall, we had a large premium low margin member that we terminated in Q3. Excluding that one member, the year-over-year growth would have been 32%. The second KPI is our member count, and we continue to attract the best MGAs in the world, with 15 additions in the fourth quarter, bringing the total to 280 as of year-end 2025. And the third KPI for the supply side is net revenue retention. For us, net revenue retention is the trailing 12-month exchange-written premium growth of our pre-existing members year over year. That includes terminated members. Net revenue retention was 126% for the quarter and 131%, excluding the large premium, low-margin member we terminated. So our members continue to benefit from the advantages our proprietary data and tools give them. On the demand side of the platform, our first KPI is gross loss ratio. That measures how profitable our portfolio is for our risk capital partners. We target a low 50s loss ratio over time, and for the fourth quarter of 2025, the gross loss ratio was 51%. The second demand side KPI is the amount of third-party direct written premiums. That measures our ability to attract insurers to participate on our risk exchange. Over the medium term, we expect this measure to reach two-thirds of total exchange-written premiums. And we have made stellar progress on this measure in 2025. For the first quarter, the measure was 19%. In the second, 27%. Third quarter, 32%. And for the fourth quarter, 40% of exchange-written premiums. We are well on our way to our medium-term goal and have demonstrated our ability to attract a growing and diverse stable of insurance company partners. The third KPI on the demand side is our net retention. That's defined as a trailing 12-month ratio of premiums retained on accelerants balance sheet to the total exchange-written premium. One important reminder here, by lowering our net retention, We also lower the revenue and EBITDA we book in our underwriting segment. Now, we welcome reducing the revenue in our underwriting segment, as it means we have placed more risk with our risk capital partners and generated relatively more fee-based revenue. For the fourth quarter, our net retention was 9%. That's in line with our expectations. In total, those six metrics, three on the supply side and three on the demand side, capture the health of our business. Short answer, we're executing extremely well. And because we are executing so well, we exceeded our guidance on all metrics. Ryan and Jay will share more details. Ryan?