Ladies and gentlemen, good day, and welcome to Yuanbao Inc.'s Third Quarter 2025 Earnings Conference Call. Today's conference is being recorded. At this time, I'd like to turn the conference over to Ms. Stella Liu, Investor Relations and Strategy Associate Director. Please go ahead. Thank you, Operator. Please note that today's discussion will contain forward-looking statements made under the Safe Harbor provisions of the U.S. Private Securities Litigation Reform Act of 1995. Such statements are not guarantees of future performance and are subject to certain risks and uncertainties, assumptions, and other factors. Some of these risks are beyond the company's control and could cause actual results to differ materially from those mentioned in today's press release and discussion. A general discussion of the risk factors that could affect Yuanbao's business and financial results is included in certain filings of the company, with the Securities and Exchange Commission. The company does not undertake any obligation to update this forward-looking information, except as required by law. During today's call, management will also discuss certain non-GAAP financial measures. For a definition of non-GAAP financial measures and a reconciliation of GAAP to non-GAAP financial results, please see the earnings release issued earlier today. Joining us today on the call from Yuanbao's senior management are Mr. Rui Fang, our Chairman and Chief Executive Officer, and Mr. Ray Wan, our Chief Financial Officer. Mr. Fang will deliver his remarks in Chinese, followed by an English translation. We will conclude the call with a Q&A session. As a reminder, this conference is being recorded. In addition, a webcast replay of this conference call will be available on Yuanbao's Investor Relations website. I will now turn the call over to our Chairman and CEO. Mr. Fang, please go ahead, sir. [Foreign language] Hello everyone, thank you for joining our third quarter 2025 earnings conference call. This quarter, we continued our trajectory of high-quality growth, with several core performance indicators hitting new record highs. In the third quarter, total revenues grew 33.6% YoY to RMB 1.16 billion. Net income surged 51.3% YoY to RMB 317 million. This marks our 13th consecutive quarter of profitability. As of the end of September, our cash reserves stood at RMB 3.75 billion, providing a solid financial foundation for our continued technological innovation, capital deployment, and strategic expansion. These strong results are a direct testament to our disciplined execution and continuous operational refinement. In the third quarter, we issued eight million new policies, with a 41.8% YoY increase. This momentum was powered by our enhanced AI and data capabilities, which have improved the precision of our consumer targeting and deepened our understanding of consumer needs. These insights feed directly back into our product innovation and scientific pricing processes, helping us build a distinct competitive edge. [Foreign language] On the product service front, we remain committed to using technology to lower the barriers to insurance access. To date, we have built a multidimensional product matrix spanning medical, critical illness, and accident insurance, while continuously rolling out innovative, inclusive solutions for diverse user protection needs. Recently, we collaborated with our partnered insurance carriers to launch a short-term critical illness insurance product. Its core value proposition is high coverage at an affordable price point by adopting a parallel lump sum payment plus multiple reimbursements model. We extend protection from the moment of diagnosis through ongoing treatment, effectively creating a closed loop of protection. This single policy provides both peace of mind during recovery and worry-free medical care, combining one-time lump sum compensation with multiple reimbursements for medical expenses. It represents a novel approach to inclusive innovation in critical illness insurance. By integrating insurance features and employing tiered reimbursement, we have optimized our cost structure to lower prices while expanding coverage. This significantly improves value for consumers and aligns with the market demand for balancing accessible coverage with affordability. [Foreign language] Turning to the industry landscape, commercial health insurance has become the vital component of China's multi-tiered healthcare protection system. The relationship between social health insurance and commercial health insurance is evolving into a new stage of coordination and complementarity. Inclusive health insurance will play a pivotal role in addressing the challenges posed by an aging population and alleviating the pressure on the public healthcare system, while unlocking a massive incremental market for commercial health insurance. The core driver lies in satisfying the health protection needs of hundreds of millions of underserved families. We believe that the key to unlocking this potential is to establish an internet-enabled service model that delivers cost-effective protection and optimized user experience and operational efficiency. This is how we translate the latent demand of this vast market into tangible growth momentum. [Foreign language] On the intelligence front, our tech AI technology and data infrastructure are now deeply integrated into our core operational workflows by embedding our proprietary large language model into critical functions, including risk identification, customer acquisition, product design, and claims processing. We have built a systematic AI-driven competitive mode that enhances operational efficiency and elevates the overall service capabilities. First, our LLMs are driving an end-to-end intelligent upgrade in R&D. By integrating LLMs and associated toolchains into the R&D workflow, we have achieved comprehensive efficiency gains across documentation and coding. For technical documentation, the LLM has generated over 1,000 documents. In coding, tools such as Model Context Protocol provide one-stop assistance, from requirement decomposition and code writing to unit test generation and automated validation. As a result, AI-generated code accounted for nearly 50% of new code developed in the third quarter. [Foreign language] Second, our LLMs are empowering our customer service system with intelligent summarization, assisted insights, and multimodal analysis. We have integrated LLM capabilities into customer service scenarios, focusing on call summarization and agent assistant functions. Embedded within the customer service workspace, these capabilities automatically generate service ticket summaries, extract key information post-call, and produce consumer intent labels, action logs, and recommended next steps. On the multimodal front, AI technology is employed to assist in consumer identity verification, while real-time voice analysis captures consumer sentiment dynamics, enabling agents to complete documentation and follow-ups more efficiently. [Foreign language] Furthermore, our LLMs are driving the intelligent evolution of modeling and feature mining within our full consumer service cycle engine. By incorporating LLM-assisted modeling and automated feature extraction technologies into this engine, we have been able to automate and deepen the complex feature engineering process. For instance, by leveraging LLMs to interpret pseudonymized or anonymized consumer behavior data, interaction content, transaction information, and product information, the system extracts valuable features. This approach reduces the reliance on manual feature design, allowing the large model to automatically generate and filter critical information, significantly enhancing both modeling efficiency and performance. [Foreign language] To summarize, the insurance technology and commercial health insurance sectors are benefiting from the dual tailwinds of policy support and rapid technological advancements. Under the national strategic guidance of building a multi-tiered healthcare protection system, the relationship between social health insurance and commercial health insurance has entered a new stage of synergy and complementary strength. Simultaneously, AI technology is fundamentally reshaping the operational logic of the insurance industry. Yuanbao is capitalizing on the significant growth opportunities in the inclusive health insurance market. On the product side, we are filling market gaps with innovative inclusive insurance offerings that lower the barriers to protection access. On the technology side, we are making forward-looking investments, embedding AI deep into our product design, operational workflows, and decision-making systems. AI has become an integral part of our management framework and a core driver of organizational upgrade. As our models iterate and business data accumulate, we can serve a massive user base with greater precision and efficiency, building an industry-leading intelligent service ecosystem. Looking ahead, with AI as our driving force, we will continue to upgrade our service model towards greater personalization and proactive care, while exploring new growth opportunities through the deep integration of AI and the ongoing accumulation of business data. We are committed to building a more resilient business model, reinforcing our long-term competitive edge and creating enduring value for all stakeholders. [Foreign language] Now I'll turn the call over to our CFO, Ray Wan, to present our financial results. Thank you, everyone. Thank you, Mr. Fang, and thank you, everyone, for joining today's earnings conference call. I'm pleased to walk you through another quarter's solid financial results characterized by healthy revenue expansion, optimized operational efficiency, improved profitability, and a strong and growing cash position. Our total revenues for the third quarter reached RMB 1.16 billion, representing a robust 33.6% YoY increase. This strong growth has primarily driven by sustained momentum across both our insurance distribution and system service revenue businesses. Turning to our revenue mix, revenue from insurance distribution services reached RMB 373.3 million, marking a year-over-year increase of 27.9%. This robust growth was primarily driven by a higher number of policies purchased on our platform, underpinned by more precise consumer targeting and enhanced marketing capabilities. System services revenues reached RMB 783.5 million, a 36.9% increase compared with the same period last year. This growth was propelled by ongoing improvements to our AI-integrated full consumer service cycle engine, which further enhanced our marketing solutions and precise analytics services for insurance carriers. In addition, the increase reflected an expanded scope of system service offerings provided to both new and existing insurance carrier partners. Moving to expenses, our total operating expenses increased by 31.2% YoY to RMB 803.4 million. Operations support expenses were RMB 45.1 million, remaining broadly stable compared with the same period last year. Selling and marketing expenses rose by 23.9% YoY to RMB 569.6 million, as we continue to invest in our marketing capabilities to attract new consumers and retain existing ones. G&A expenses increased by 97.8% YoY to RMB 93.1 million, primarily due to higher personnel costs, including salary, bonus, and benefits. R&D expenses increased by 56.8% YoY to 95.6 million RMB, reflecting our intensified R&D efforts and the expansion of our R&D team. These investments are essential in reinforcing our leadership position as a technology-driven online insurance distributor. As a result of our strong top-line growth and continued operating discipline, our profitability improved meaningfully this quarter. Net income increased by 51.3% YoY to 370.4 million RMB, with a net income margin expanding to 32% from 28.2% in the same period last year. Non-GAAP adjusted net income rose by 51.7% to RMB 390 million, representing a non-GAAP net income margin of 33.7%, up from 29.7% a year ago. We maintained healthy cash flow generation during the quarter, further solidifying our cash position. Operating cash flow was RMB 326.1 million, and we ended the quarter with a strong total liquidity balance of RMB 3.75 billion, which increased 82.3% YoY to 9.7% since the end of second quarter this year. This robust liquidity provides us with ample financial flexibility to fund the business growth and pursue strategic investments. To conclude, our third quarter results once again validate the strength and scalability of our business model. Looking forward, we will maintain a prudent focus on high-quality growth, operational efficiency, and a solid liquidity position, empowering us to continue investing with conviction and to drive sustainable growth. Thank you, and I would like to open the call to Q&A. Operator, please go ahead. Thank you. We will now begin the question and answer session. To ask a question, please press star one one on your telephone and wait for your name to be announced. To withdraw your question, please press star one again. For the benefit of all participants on today's call, if you wish to ask your question to management in Chinese, please immediately repeat your question in English. There may be a short pause as attendees register their questions. We will now take our first question from the line of Amy Chen from Citi. Please go ahead, Amy. Hi, this is Amy Chen from Citi, and thank you very much for the opportunity for a question. First, I want to congratulate the management on another robust quarter, both on revenue and earnings side. I have two questions. The first one being on selling and marketing expenses. We noted that as a percentage of revenue, actually, the efficiency of selling and marketing expenses has improved both year-over-year and quarter-on-quarter. I'm wondering what was the driver behind this improvement and if this has anything to do with seasonality and is it sustainable going forward. And the second one would be on. We have lost Amy's line there. Maybe we can go on to the next question. We will now take our next question from Yue Xu from CSC. Please go ahead, Yue. Hi, management. Congrats on your solid execution for the quarter. So my first question relates to a recent tax regulation change effective in October. So with a new 15% cap on ad spend deduction, have we seen some material impact on the overall bidding intensity across platforms? And how should we think about the future revenue growth going forward? And the second one is we have noticed some peers also expanding into public traffic acquisition. And how should we think about the margin or the customer acquisition cost going forward? Thank you, Yue. This is Ray Wan. I'll take on the Q&A. My first question regarding ad trends and tax regulation. So far, we haven't seen any material impact or changes to our ongoing business. We've been following it very closely as well. However, if this becomes a market-wide standard, it'll affect the entire industry, including advertisers as well as platforms, by driving up ad costs for everyone. As advertising costs rise across the industry, we do believe that players with stronger profitability and operational efficiency and cost controls are better positioned to stand out and achieve sustainable earnings, leading to potentially market consolidation or stronger growth. On your second question regarding competition in the public domain, yes, we've seen our partners increase investment in external traffic, which validates the success of our business model and technological capabilities, while also underscoring the substantial growth potential of the health insurance market. Meanwhile, the increase of external traffic by our partners serves as valuable market education, raising consumer awareness for commercial insurance because a large portion of the population still remains uninsured by commercial health plans, indicating that the industry's ceiling is still far from being reached. Today, commercial health insurance has become an integral component of China's multi-tier medical security system, as Mr. Fang mentioned, and the relationship between social health insurance and commercial health insurance is entering a new stage of synergy and complementary strength. In our view, the deciding factor in maintaining a competitive edge ultimately comes down to operational efficiency. With our optimized engine, we continue to grow and achieve attractive economics even at our current scale, and we will continuously train and optimize our engine, which is key to driving efficiency and maintaining our competitive edge. Thank you. Thank you. That's helpful. We will now take our next question from Amy from Citi. Please go ahead, Amy. Hi, this is Amy from Citi, and thank you for the opportunity. My third question is regarding marketing efficiency. We noted that your selling and marketing expenses as a percentage of total revenue actually improved both year-on-year and quarter-on-quarter. I'm wondering, is there any seasonality in this, or what was the core driver behind this improvement? And going forward, is this level of efficiency sustainable? The second question is regarding shareholders' return. Given our improved top-line growth as well as earnings, what are management's thoughts on perhaps dividends or share buybacks at this point? Thank you. Thank you, Amy. In terms of our market expenses, there is some seasonality depending on our acquisition strategy because sometimes we may want to avoid strong acquisition periods such as 2011, but we also continuously dynamically adjust our strategy based on growth targets and ROI targets. We've been adjusting our marketing approach in real time, and different approaches lead to effective outcomes, including potential shifts in age profile, spending power, and consumption habits of our consumer base. What we are seeing here are obviously improvements in our overall efficiency continuously over the last 13 quarters, but going forward, we believe we want to, as mentioned before, have a very balanced growth profile in tandem with our operational efficiency going forward. In your second question regarding shareholder return, we continue to evaluate best strategies in providing the best shareholder returns through various operational and capital markets opportunities. Like you said, dividends is certainly one of them that we are considering. Thank you. Thank you. Thank you. We will now take our next question from Yuan Liao from Citics. Please go ahead. Thanks, management, for taking the questions, and congrats for the strong quarter results. I have two questions. The first question is about AI and with the rapid development of the generative AI and AI agents. So how do you see this impacting your products and business models? And And could management share your strategic roadmap regarding future algorithm or product innovation? And the second question is about your target markets. So how do you view the current market penetration rate within Yuanbao's target demographic, and what potential do you see for the future upside growth? Thank you. Thank you, Yuan. So my first question, so we integrate AI capability in various aspects of our operation. As you know, on the front end for traffic acquisition, we have built a very strong engine with thousands of models and labels for each consumer, relying primarily on recommendation algorithms, which are tree-based models or GBMs. As for generative AI, we deploy them across our user acquisition journey, as well as internally, as noted by Mr. Fang, on our LLM capabilities and earnings highlight. The evolution of our AI agents and AI capabilities will play a crucial role here in both helping with generating innovation and potentially new earnings, as well as continued improvements across our business. So on the one hand, it'll help us continue to elevate consumer experience. On the other hand, it will allow us to continuously capture data insights, creating a feedback loop in addition to what we have already to further refine our model performance. On your second question regarding industry penetration, so looking at the industry landscape, commercial health insurance has become a vital component of China's multi-tiered healthcare protection system. The relationship between social health insurance and commercial health insurance is evolving into a new stage of coordination and complementarity, as Mr. Fang mentioned, so we do believe commercial health insurance will play a pivotal role in addressing the challenges posed by aging population and alleviating the pressures on the public healthcare system, so as local economies grow and innovative drug catalogs for commercial health insurance are established, we believe the demand for protection will rise continuously and very naturally. Yuanbao's online inclusive model is actually very ideally and perfectly suited to reach these demographics that are underserved by commercial health insurance. In addition, for users who have already purchased short-term policies, they are far from reaching their protection ceiling. We see tremendous headroom for upselling and cross-selling additional products such as critical illness, accident, etc., and there's huge potential in user purchasing policies for family members. Regarding premiums, we don't see it alone as a key driver. Instead, our focus is on leveraging AI and big data for very precise risk assessments, as well as understanding the pain points and needs of our consumers. We believe this will enable very defined pricing, leading to a healthy and sustainable ROI. It's, I think, a pretty long-winded way of saying that we have a lot of internal models of calculating the current penetration headroom, and we do believe we are very, very far from reaching any level of higher penetration, but additional data analysis we can discuss further. Thank you. Thank you. Very helpful. Thank you. We will now take our next question from [Jia Liang Yuan] from Huafu Securities. Please ask your question, Jia Liang. Hi, Yue. Thanks for taking my question. Congratulations on the strong results. I have two questions. First, regarding revenue growth, could you break down the quarter growth between new user acquisition and the higher premium per user? And looking forward, what do you see as the key driver for sustainable growth over the next three years? And my third question is about AI. Can you quantify the KPI improvements you are seeing in conventional efficiency? And will exporting these AI capabilities create new revenue streams or pricing power for the company in the future? That's all from me. Thank you. Thank you, [Jia Liang]. On your first question regarding revenue growth, so our revenue growth is driven by multiple factors. Now, for the next two to three years, we see three key drivers. Number one is market tailwind. As people become more insurance conscious, the penetration rate and growth in the health insurance sector is set to continue to increase. Second is cross-selling and product innovations to tailor to consumer needs because as we understand and analyze more user behavior data, we can recommend and innovate more suitable products. Third is our data advantage. With our growing data scale, we're constantly refining our models to better understand and to have better efficiency and accuracy. This is how we plan to ensure sustainable and healthy ROI. But in terms of the actual breakdown, it's a combination of multiple factors that really drives our revenue as well as our profitability. On your second question regarding AI, so as you know, our business started off by having a very strong AI-based or machine learning team that built out our engine. So AI capabilities and data infrastructure has been very deeply integrated across the entire user acquisition process chain, but now by embedding our large language model capabilities across key functions, including risk identification, customer acquisition, product design, and claim processing, we've systematically built an AI-driven competitive moat that will continuously enhance operational efficiency and elevate our service quality. Now, second, through our current engine, we're able to uncover more consumer needs in real time and week by week, month by month, and co-develop products with insurers that better meet today's market demand, as Mr. Fang mentioned, a new critical illness product. So together with our insurance carrier partners, we launched a short-term critical illness product. The core highlight is unlocking millions in coverage at an inclusive price point by adopting a parallel lump sum payment plus multiple reimbursement model. And so in summary, our AI capabilities have enabled us to, number one, on the product front, address coverage gaps through the launch of innovative inclusive insurance products to create and offer more value to our consumers, thereby lowering barriers to insurance services. And number two, on the technology front, establish a proactive deployment across all business processes, embedding AI deeply into product development workflow and decision-making systems to make it an integral part of our operational management framework. Now, whether this is going to create new revenue streams or unlock pricing outside, certainly from existing business model, we do believe that will help us allow us to continue to grow very effectively and efficiently. But new revenue streams in existing business, we think it will help us expand our potential product offerings. But in terms of diversification, that's also something that we're actively looking at. Thank you. Thank you, Yue. We will now take our next question from Yiting Xu from Southwest Securities. Please go ahead, Yingying. Thank you, management, for giving me this opportunity to ask a few questions. My name is Yiting Xu. I am the Chief Financial Analyst at Southwest Securities. First of all, I would like to congratulate Yuanbao on another strong quarter. I have two questions for the management team. My first question is about revenue growth. Looking ahead to 2026, I am curious to know what you see as the main drivers of Yuanbao's continued revenue growth. Is it crossing marketing spend, or is it improving the efficiency of your AI models? Is it expanding cross-selling, or maybe achieving higher commission rates with shareholders? Also, how do you expect these factors to change over the next three years? My second question is about competition and brand. Compared to ecosystem players like Ping An Good Doctor, or Ant Insurance, Yuanbao is an independent platform. I would like to know what is your strategy to strengthen Yuanbao's brand? How will you improve customer loyalty, and how do you plan to increase renewal rates over the next one to three years? Thank you. Thank you. Thank you, Thank you, Yiting. To answer your first question, now, in terms of growth, we conduct a very holistic assessment across multiple dimensions, including traffic acquisition at scale, model efficiency enhancements, cross-selling, and tailored to very specific market conditions. So by continuously mining data and refining our modeling capabilities, we aim to maintain very sustainable profitability even as our business continues to scale. So that's something that we've been very consistent about over the last couple of quarters. Now, regarding model efficiency, we're very strictly focused on assessing and ensuring that our customer acquisition costs remain stable or trend flat at the minimum as we continue to expand and grow at a very fast scale. Now, looking ahead, we'll continuously bolster our engine by adding or optimizing models. Our goal is to enhance predictive precision without disrupting our existing infrastructure. Now, we haven't provided guidance for 2026, but I guess for the remainder or for year 2025, we do believe that we'll grow at least 30% on a revenue basis and continue to maintain a very similar and healthy profit level. Now, for your second question regarding existing ecosystem players versus how do we plan to strengthen our brand moat and enhance customer stickiness, now, first, we operate on an AI-driven engine model where insurance distribution is powered by technology. We acquire users across the full spectrum of traffic channels without relying heavily on any one, allowing the potential for a stable and scalable source of new consumers, serving as the foundation of our future consumer base. Second, as an independent third-party insurance distributor, what sets us apart from ecosystem-based players is our capability for daily collaborative iteration across diverse teams, including big data, AI, business marketing, operation, customer service, etc. Our edge does not derive solely from core model or algorithm. Rather, it stems from a holistic iterative feedback mechanism that requires significant time accumulation to build over the last few years on a day-to-day basis. This involves very much a large part of cross-functional collaboration. So the AI team handles modeling and fine-tuning, while data team manages data governance, feature mining, business team, etc. So this integrated system, polished through daily multi-departmental collaboration, we do believe has brought us to where we are currently over the last few years. And we want to continue that operational know-how and operational excellence going forward to build our capabilities. Thank you. We will now take our next question from [Xingtao Chen] from CICC. Please go ahead, Xingtao. Thank you, management, for giving me the opportunity to ask questions, and congratulations on the strong performance in the third quarter, and I have two questions for the management. The first is, the efficiency of Yuanbao's model stands out against peers, so what's the key drivers behind this? Going forward, is there further room for improvements in net income margin and ROI? And the second one is regarding the competitive landscape, so how does the management view the competitive landscape of the industry over the coming years? Thank you. Thank you, [Xingtao]. So our ROI stems from the full digitization and automation of our insurance full-cycle engine or acquisition process, which leads to a comprehensive efficiency uplift across the entire user lifecycle. Now, this spans every single step of the process from adding pressure and user registration, purchase, cross-selling, after-sale services, and claim assistance. So by leveraging our engine to analyze massive user behavioral data, we continue to optimize conversion efficiency at every step. And that's what we want to continuously iterate to enhance our engine. Now, going forward, we do see potential for upside in efficiency, but what we have to balance, as mentioned, is we do believe the market has a very large room for additional penetration and growth. So we want to balance growth with profitability such that we are growing at least faster than how fast the market is growing to capture that market share. On your second question regarding competition, and then so today, we haven't observed any material changes to the landscape. This is primarily because the ad bidding process is both real-time and impartial, placing us on a level playing field with all the advertisers across platforms, including those in gaming incomes, etc. The platform bidding mechanism is very industry or player neutral. So with our optimized engine, we continue to grow and achieve what we believe is attractive economics as we continue to scale. So we want to make sure that we continuously train and optimize our engine. Furthermore, our competitive edge is not derived from just a few core models or algorithms. Instead, it stems from a comprehensive iterative feedback loop that has been built by us from one single model and one label starting from day one. So it hinges on a very deep collaboration across multiple specialized teams and being able to be very adaptive to the changing external environment. Now, so given the vast market potential, we're confident that our sustained iterative capabilities will allow us to maintain our existing position and leadership even as changes in the external environment. Thank you. Thank you for your insight. Thank you. We receive an online question here from Thomas Wong of Goldman Sachs. His question is, "Please provide updates on the following topics: sales momentum per policy premium and product mix, and the trend in commission rate and tick rate." Thank you. Thank you. So in the third quarter, our total revenue mainly driven by revenue from insurance distribution services growing at 27.9%. Revenue from system services grew a bit faster at 36.9%. Now, in the third quarter, our average premium and short-term policy remained generally consistent with historical levels, so tracking within normal ranges both year over year and quarter on quarter. Now, with the trending commission rate, so as for tick rate, it can be roughly estimated by dividing revenue by premiums. Now, looking at the full-year picture, we expect our tick rate to remain relatively stable to historical levels. Now, to emphasize, while tick rate is a very important metric, it's just one of several key factors we evaluate in our broader market strategy to optimize really our ROI. So we focus on balancing all of the key drivers, including tick rate. But this also includes price per policy, cross-selling efficiency, customer acquisition costs, and other operational metrics, not just tick rate alone. Thank you. That concludes the question and answer session, and I'd like to turn the conference back to management for any additional or closing comments. Thank you once again for joining us today. If you have any further questions, please feel free to contact us directly. We're Piacente Financial Communications. Our contact information for IR in both China and the U.S. can be found in today's press release. Have a great day. For your participation in today's conference, this does conclude the program. You may now disconnect your line.