Yuanbao Inc.

are Mr. Rui Fang, our Chairman and Chief Executive Officer, and Mr. Rui 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 the CEO. Mr. Fang, please go ahead, sir.

Hello, everyone. Welcome to Yuanbao's third quarter financial report conference in 2025. This quarter, we continued to continue the high-quality growth trend. Multiple core indicators echoed historically high. The total income increased by 33.6%, reaching RMB 11.58 billion. The net profit increased by 51.3%, to RMB 3.7 billion. We have maintained profit for 13 consecutive seasons. Until the end of the season, the company's cash reserve reached RMB 37.5 billion, which has provided strong financial support for our continued promotion, technical development, capital operation, and strategic expansion. As for the growth of performance, the core is the result of continuous optimization of the various stages of our operations. In the third quarter, the new supply chain reached Hello, everyone. Thank you for joining our third quarter 2025 R&S 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% year-over-year to RMB 1.16 billion. Net income surged 51.3% year-over-year to RMB 370 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 the strategic expansion. These strong results are a direct testament to our disciplined execution and continuous operational refinement. In the third quarter, we issued 8 million new policies with a 41.8% year-over-year 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.

In terms of product service, We have always been committed to the threshold of reducing insurance services through technology. At present, we have covered products with multiple scenarios such as medical insurance, intensive care insurance, and accident insurance, and continue to introduce innovative general solution solutions that meet the needs of users. Recently, Yuanbao Co., Ltd. has launched a short-term intensive care insurance to move the price of the general solution to the core of the million-dollar balance. a multiple-refund and multiple-refund model, so that the insurance can be extended from the moment of diagnosis to post-treatment treatment, and ensure that the insurance will be returned. A insurance bill can be used to ensure that people can rest in peace and see a doctor without worries, to ensure a multiple-refund and multiple-refund of medical expenses, and to provide a new solution for the innovation of heavy-duty insurance. Currently, our innovative products have been developed On the product service front, we remain committed to using technology to lower the barriers to insurance access.

we have built a multi-dimensional 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 and 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 the 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 units 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's demand for balancing accessible coverage with affordability.

In the direction of industry development, commercial health insurance has become an important component of our multi-level medical insurance system. Social health insurance and commercial health insurance are in the process of co-developing and complementing each other. Pohui Health Insurance will play a key role in the accumulation of population aging and health insurance pressure, and activate commercial health insurance. Its core drive is to meet 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 elevating 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.

In terms of intelligent construction, our AI technology and data system use deep energy to run the core process. Through the so-called source model, we will identify the risk of deep integration, purchase, product design, retail processing, and other core parts. Our systematic structure is based on AI as the base for competition. to promote operation and service upgrade. First of all, the R&D department of the large model has completed the entire process of intelligent upgrade. In the development process, by introducing large language model and related tool chain, the performance has been fully improved from document to code. In the technical document section, the large model has completed more than 1,000 document designs. In the coding stage, On the intelligence front, our 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 a thousand documents. In coding, tools such as model context protocol provides 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.

其次,大模型赋能人工客服体系, 实现智能摘要,辅助洞察与多模态分析。 我们在客服场景中, 探索性集成了大元模型的能力, 重点围绕通话总结, and customer support functions. This function is currently embedded in the artificial customer service workstation. After the call is over, it can automatically generate service, supply and demand, and supply key information, and generate customer demand intent labels to complete operation and follow-up processing suggestions. In terms of animal type, through AI technology, support verification, customer identity, implementation voice, record customer mood changes, and help customers complete the record and update as soon as possible.

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 summarizers, 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.

此外,大模型赋能消费者服务引擎 推动建模与特征挖掘向智能化演进。 我们在消费者全周期服务引擎中 引入了大元模型辅助建模与特征自动挖掘技术。 该技术能把复杂的特征工程 流程自动化和生路化。 By using a large-scale model to understand and standardize or anonymize customer behavior data, interaction content, transaction data, and product information, we can extract valuable characteristics from them. In addition, we can reduce the work of manually designing characteristics, and use large models to generate and select valuable information to greatly improve the modeling speed and efficiency.

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 autonomous 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.

The health insurance technology and the industrial health insurance industry are both supporting and upgrading the technology. On the one hand, the country is clearly building a multi-level medical insurance system. The relationship between social health insurance and industrial health insurance has entered a new stage of co-efficiency and mutual benefit. On the other hand, AI technology is deepening the operation logic of the insurance industry. Yuanbao has accurately grasped the positive opportunities of the general health insurance market. In terms of products, we accurately supplement and continuously launch innovative general health insurance products, reducing the threshold of insurance services. In terms of AI technology, we have carried out a comprehensive layout of the entire process of business, and have deeply embedded AI into the product process decision system, making it part of the management system. By continuously upgrading our organization, we will be able to continue to accumulate data on the model and the scale of our business. We will be able to understand and serve a large number of users with higher efficiency and accuracy, and build a smart service ecosystem that will lead the industry. Looking forward to the future, we will continue to use AI as a engine to promote the service model and upgrade to individualization and active care. To summarize, the insurance technology and commercial health insurance sectors are benefiting from the dual tailwind 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 strengths. 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.

下面,请我们的CFO来为大家介绍一下我们三季度的财务表现,谢谢各位。

Now I'll turn the call over to our CFO, Ray Wang, 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 1.16 billion RMB, representing a robust 33.6% year-over-year increase. This strong growth has primarily driven by sustained momentum across both our insurance distribution system service revenue businesses. Turning to our revenue mix, revenue from insurance distribution services reached 373.3 million RMB, marking a year-over-year increase of 27.9%. This robust growth primarily driven by a higher number of policies purchased on our platform, underpinned by more precise consumer targeting and marketing capabilities. System services revenues reached 783.5 million RMB, 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% year over year to 803.4 million RMB. Operations and support expenses were 45.1 million RMB, remaining broadly stable compared with the same period last year. Selling and marketing expenses rose by 23.9% year over year, to 569.6 million RMB as we continue to invest in our marketing capabilities to attract new consumers and then retain existing ones. G&A expenses increased by 97.8% year-over-year to 93.1 million RMB, primarily due to higher personnel cost, including salary, bonus, and benefits. R&D expenses increased by 56.8% year-over-year to 95.6 million 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% year-over-year to 374.70.4 million RMB. with the 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 390 million RMB, 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 326.1 million RMB and we ended the quarter with a strong total liquidity balance of 3.75 billion RMB, which increased 82.3% year-over-year 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 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 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-wise. I have two questions, the first one being on selling and marketing expenses. 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 does this have anything to do with seasonality and the 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 solidly valid and strong execution order. So my first question relates to a recent tax regulation change effective in October. So with a nearly 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 cost, the customer acquisition cost going forward?

Thank you. This is Ray Wan. I'll take on the Q&A. My first question regarding ad trends and tax regulations. 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 will 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 serve 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 industry 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. Feng mentioned, and the relationship between social health insurance and commercial health insurance is entering a new stage of synergy and complementary strength. So in our view, the deciding factor in maintaining a competitive edge ultimately comes down to operational efficiency. Now, with our optimized engine, we continue to grow and achieve attractive economics, even on 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. Thank you for the opportunity. I have two questions. My first question is regarding marketing efficiency. We noted that 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' returns. 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. So 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 W11, but we also continuously dynamically adjust our strategy based on growth targets and ROR targets. So we've been adjusting our marketing approach in real time, and different approaches lead to, you know, effective outcomes, including potential shifts in age profile, spending power, consumption habits of our consumer base. Now, 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. And your second question regarding shareholder return, we continue to evaluate best strategies in providing the best shareholder return through various operational and capital market opportunities. And 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 Citix. Please go ahead.

Thanks management for taking the questions and congrats for the strong quality results. I have two questions. The first question is about AI and with the rapid development of the generative AI and AI aging. How do you see this impacting your products and business models? And could management share your strategy roadmap regarding future algorithm or product innovation? And second question is about your target market. So how do you view the current market penetration rate within Yuanbao's target demographic and what potential do you see? for the future of growth? Thank you.

Thank you, Yuen. 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. Fung, on our LLM capabilities and new 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 continuously 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 health care protection system. The relationship between social health insurance and commercial health insurance is evolving into a new stage of coronation and complementarity, as Michelle Fong mentioned. So we do believe commercial health insurance will play a pivotal role in addressing the challenges posed by the aging population and alleviating the pressures on the public health care system. As local economies grow and innovative drug catalogs for commercial health insurance are We believe the demand for protection rights will rise continuously and very naturally. So 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, et cetera. And there's huge potential in user purchasing policies for family members. And regarding premiums, we don't see it alone as a key driver. Instead, our focus is on leveraging AI data for very precise risk assessment, as well as understanding the pain points and needs of our consumers. So we believe this will enable very defined pricing, leading to a healthy and sustainable ROI. So it's, I think, a pretty long window 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, Irene. Thanks for taking my question. Congratulations on the strong results. I have two questions. First, regarding revenue growth, could you break down the third quarter growth between new user acquisition and the higher premium pure user and the 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 TPI 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, Xiaolian. On your first question regarding your revenue growth, so our revenue growth is driven by multiple factors. Now, for the next three years, we see three key drivers. Number one is market tailwind. As people become more insurance conscious, the penetration rate and growth in health insurance sectors down 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 base 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 mode 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. Phan 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 offering 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. Whether this is going to create new revenue streams or unlock pricing upside, 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, Ray.

Thank you. We will now take our next question from Yingying Xu from Software Securities. Please go ahead, Yingying.

Thank you, management, for giving me this opportunity to ask a few questions. My name is Xu Yingying. I am the chief financial analyst at Southwest Security. 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 increasing marketing spend or is it improving the efficiency of your AI models? Is it expanding cost selling or maybe achieving higher commission rates with showreels? 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 customers' loyalty? And how do you plan to increase renewal rates over the next one to three years?

Thank you. Thank you. To answer your first question, now, in terms of the world, we conduct a very holistic assessment across multiple dimensions, including traffic acquisition and its 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 the year 2025, we do believe that we'll grow at least 30% on our revenue basis and continue to maintain a very similar and healthy profit level. Now, for our second question regarding existing ecosystem players versus how do we plan to strengthen our brand moat and enhance customer stickiness. At first, we operate on an AI driven engine model where distribution is powered by technology. We acquire users across the full spectrum of traffic channels without relying heavily on anyone, allowing the potential for a stable and scalable source of new consumers, serving as the foundation of our future consumer-based. 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, et cetera. Our edge is not derived 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, very much a large part cross-functional collaboration. So the AI team handles modeling and fine-tuning, while data team managers, data governance, feature mining, business team, et cetera. So this integrated system polished through daily multi-departmental collaboration, we do believe has brought us to 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 Tsingtao Chen from CICC. Please go ahead, Tsingtao.

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 YANBAO's model stands out against peers. So what's the key drivers behind this? Going forward, is there further room for improvement 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, Xintao. So our ROI stems from the full digitization automation of our insurance system. you know, full cycle engine or acquisition process, which leads to a comprehensive efficiency update across the entire user lifecycle. Now, this spans every single step of the process from adding pressure and user registration, purchase, cross selling, after sales services and claim assistance. So by leveraging our air 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 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, 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 placing us on a level playing field with all the advertisers across platforms, including those in gaming, e-commerce, et cetera. 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, and instead it stems from a comprehensive, iterative feedback loop that has built by us from one single model or 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 And so given the vast market potential, we were confident that our sustained iterative capabilities will allow us to maintain our existing position leadership even as changes in the external environment.

Thank you. Thank you for your insight. Thank you.

We received 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 for 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 take rate, it can be roughly estimated by dividing revenue by premium. Now, looking at the full year picture, we expect our take rate to remain relatively stable to historical levels. Now, to emphasize, while take rate is a very important metric, it's just one of several key factors we evaluate in our broader strategy to optimize, really, our ROI. So we focus on balancing all of the key drivers, including take rate. But this also includes price per policy, cross-selling efficiency, customer acquisition costs and other operational metrics, not just take rate at all. Thank you.

And that concludes the question and answer session. And I'd like to turn the conference back to Matt Schmidt for any additional or closing comments.

Thank you, Wes, again for joining us today. If you have any further questions, please feel free to contact us directly. We're Patented Financial Communications. Our contact information for IR in both China and the US can be found in today's press release. Have a great day.

Your participation in today's conference, this does conclude the program. You may now disconnect your lines.