Yahoo Finance

Xiaoying Xu

Thank you, Shen Peng. Before I go into details, please be reminded that all numbers quoted here will be in RMB. And please refer to our earnings release for detailed information on our financial performance on both the year-over-year and quarter-over-quarter basis, respectively.
In Q4, the company delivered solid performance with total revenue to reach CNY687 million up 4.2% YoY. For full year 2024, our revenue totaled CNY2.77 billion. In 2024, our non-insurance business accounted for near 15% of total revenue. Our Crowdfunding service fees amounted to CNY267.7 million while our digital clinical trial solution income reached CNY91.1 million, collectively reflecting diversified revenue stream.
Through AI-driven efficiency enhancement, and the refined operation management, our total operating costs and expenses in Q4 amounted to about CNY634 million, remaining stable compared to the same period of year. For the full year of 2024, overall operating costs and expenses decreased by 1.7% from last year.
Breaking this down, in Q4 operating costs increased by 7.2% year over year to CNY323.8 million, and this was primarily driven by an increase of CNY39.1 million in cost of referral and service fees, partially offset by a decrease in personnel costs. Sales and marketing expenses increased by 4.1% year over year to CNY182 million this quarter. This resulted from our strategic expansion in customer acquisition due to an increase of CNY30.2 million in marketing expenses for third-party traffic channels and partially offset by a decrease of CNY22.8 million in personnel costs.
General and administrative expenses declined significantly to CNY73.7 million, down 23.2% year over year mainly attributable to a decrease in allowance for credit loss and professional service fee. R&D expenses stood at CNY54.3 million, a 9.3% decrease from the same quarter of year, primarily reflecting optimized personnel costs.
However, our AI investment remains. In fact, we plan to increase investments in 2025 to further strengthen our technology edge. We have sustained remarkable profitability and double our annual net profit attributable to our ordinary shareholders. We continue to generate positive operating cash flow during this quarter. As of December 31, 2024, our cash position was CNY3.67 billion, providing a robust support for future growth initiatives. And this concludes our financial overview.
I will now pass to our Board Secretary, Jasmine to update on our business development.

Tracy Lee

Thank you, Xiaoying. In Q4, our insurance business achieved FYP of about CNY1.9 billion, representing 24.5% year-over-year growth so showing a 7% quarter-on-quarter decrease. Insurance-related revenue reached CNY580 million, down 1% Y-o-Y and 3% quarter over quarter, while operating profit stood at CNY103 million with an 18% operating margin.
During this quarter, our short-term insurance FYP surged 44.2% YoY to CNY1.43 billion driven by breakthrough in public customer acquisition through the real-time marketing optimization and the new payment channels, leveraging user insights. We introduced more inclusive short-term insurance products in this quarter, including medical plans tailored for individuals with pre-existing conditions.
For long-term insurance product FYP reached CNY460 million with a slight sequential decrease impacted by the product suspension of last quarter and the holiday reason in this quarter. In Q4, we optimized our team starting well maintaining high productivity per capita. Furthermore, we sustain our efforts to enhance and diversify our long-term insurance offerings with disability income insurance along achieving and FYP CNY90 million.
The company has also continued to develop its online planner model. In the fourth quarter, Shenlanbao independently contributed approximately CNY90 million in FYP. For our Medical Crowdfunding business as of end of 2004, around 470 million people accumulated -- donated CNY67.5 billion to about 3.4 million patients through our platform. Our platform percept thousands of campaign applications and over 50,000 image submissions with risk control remaining a top priority.
To enhance efficiency, we implemented a due model AI framework. On one hand, lightweight model now detected pixel-level image tempering in mid-second reducing false positive rates from 0.3% to an industry-leading 0.1%.
On the other hand, summarizing expense experienced from the accumulated cases from the past eight years extracting more than 1,700 characteristics to assist medical consultants and making reasonable prediction of those diseases and reducing the risk of caused by fraud and the corporation.
Following 2024 regulation update and the government official designation, Waterdrop as China's largest online service platform for individual seeking financial help, we will continue setting standards through technology-driven transparency and user-centric operations.
During this quarter, our Digital Clinical Trial Solution income continued its growth, realizing a year-on-year increase of 22.9%. We collaborated with a total of 177 pharmaceuticals and CROs. Moreover, we enrolled 880 patients and initiatives service for 79 new programs during the fourth quarter of 2024.
In addition, the platform leveraged AI models to enhance doctor patient service across scenarios like health management, automatic science content creation and education digital auditors. Multiple initiatives have been launched, both in efficiency and use experience well ensuring compliance. This is a key progress of each business line in this quarter.
Next, we will invite here Ran Wei, the GM of the Insurance business to deliver a keynote on Waterdrop AI-driven (inaudible).

Wei Ran

Thank you, dear investors and analysts. It's a great honor to present Waterdrop's achievements in AI and other [insure tech] during the earnings conference. Waterdrop has been deploying AI since 2019, starting with machine learning algorithms, [OCR and LP] technology to optimize insurance product recommendations, mismatching and rig control both in online conversion rates and service efficiency.
We established a series of digital infrastructure including data middle platforms, intelligence marketing system, smart CRM system, and AI risk control system, enhancing user experience will strengthen our insure tech leadership. This journey also cultivated a cross-functional R&D team, combining insurance expertise with AI capabilities.
This transformative way water has developed in here insure competitively barrier for AI applications, which can be divided into four core areas. Firstly, we have built a multi-dimension ecosystem interacting tax and voice interaction, digital (inaudible) and other innovations. Covering channels such as and AI calls, this enables seamless transaction between service, while accumulating multidimensional data.
Secondly, we have established a fully digitalized the service chain being demand identification, product matching, underwriting, and the claims we're setting. Unlike the conversational ability of general-purpose [ROM], our service chain requires not only massive knowledge bases but also precise control over the entire service workflows to ensure high reliability.
Currently, we handle tens of thousands of highly complex insurance [incurs] in a daily basis. [Literally] over eight years, we processed 100 million private data assets in the insurance industry, including 112 million operation data knowledge base of over 7,000 products and massive structured service data entries. This real-world data is in [repurpose] training material for building insurance-specific LLM.
Lastly, distinct from general purpose LLMs, Waterdrop vertical knowledge graph for insurance scenario, combining recommendation, insight, and service conversion. Across hundreds of refined operational or not, we employ specialized tools such as family coverage gap analysis of renowned customer design decision-making psychology models and resolution framework for customer objection.
For example, our model can generate customer -- customized insurance plan in real time based on user blooding duration, consultation, keywords, family structure, and other features. This following one capability system, integrating scenarios, service, data, and knowledge, ensuring the rapid implementation of orders of the AI solution. While general purpose still struggle with (inaudible) nations, our vertical models can already deliver definitive answers to our users.
Overall, the combination about the multiple scenarios and online data has offered a replaceable strategic value in insurance LLM. Next, I will demonstrate how our AI has delivered marble results. Over the past two years, we have actively adopted cutting-edge fundamental technologies while developing AI applications tailored to our business mirrors. I want to share some examples. Firstly, our insurance AI agent has end-to-end self-decision-making capability.
It integrated the ability of profession in (inaudible), in decision, execution. Leveraging mobile agent collaboration technology in the medical insurance scenario, it enables fully automatic decision-making up to 15 [unit] conversations. For example, a single call can automatically complete process, like understanding user needs, health risk modeling and the policy interpretation. Our AI agent can support modular agent unit collaboration in real time and the flexible transition across health insurance, auto insurance, and other scenarios.
The system rate of over 7,000 products and can respond within 2 seconds. Over our AI agent can dynamically optimize and algorithm by learning from the operational feedback and (inaudible) outcome through over 100,000 daily interactions. And secondly, we also continue to optimize our model through two main approach.
The first one is knowledge destination. This use technology like SFT and reasoning, it impacts millions of insurance-related knowledge to the model, making it comparable to the senior human [competent]. The second is the reinforced fine-tuning of the sales strategy. We integrated the DeepSeek and other open-source frameworks with our stock developed GRPO algorithm. This has increased model accuracy by 20%.
Furthermore, our AI agents can make multimodal interaction with our users such as real-time coordination of voice, tax and the image minimize the user waiting time. We also upgraded with an emotion adaptive system. It can dynamically adjust [speaking] speed and modified it's [tongue] based on semantic analysis.
For example, our AI agent will slow down by 20% when they interact with elderly users. Over the past two years, our 48 related patents have been granted with over 100 patents filed and nearly 100 AI innovations. Waterdrop is one of the first interact companies capable of enabling AI agent to independently close deals in complex serials.
Next, I will want to show you our detailed AI application results. Following a development path from single automation to advance the integration. Our LLM application now focused on two directions: co-pilot and AIA and directing serving users.
For our co-pilot application, we have quality control for pellets and sells co-pilots. Our quality control co-pilot can replace the manual sampling of service recording and perform tax analysis with 88% accuracy level of human for across voice and text channels, we expect the front-line quality control cost to be reduced by 40%, significantly improving efficiency. And our South copilot can enhance sales efficiency by enabling rapid summarization of client intent and tailored product recommendation.
This tool elevates the service quality and conversion rate, empowered our human agent to better meet client needs and are achieving -- achieve self-targets. About our AI agent, we have three different applications, including AI health insurance agents, AI service assistance and AI insurance planner.
For our AI health insurance agents, it can directly serve customers via voice-based conversation consultation, like single session lasting up to 15 minutes outperforming junior agent efficiency. It currently generates millions insurance premiums per month. project to reach tens of millions by year end. Beyond this, our AI auto insurance agents have entered daily training with two P&C insurers with selected projects already in user beta testing.
For our AI services business also (inaudible) embedded in our app, this 24/7 AI assistant and Q&A about user policy and the products you were interested in by 2015, we expect AI to reduce a transferring rate by 50% and improving efficiency by 50% compared to human agents.
Leveraging (inaudible) ability, we are developing an AI insurance planner to provide real-time, high-quality family insurance consultation and planning services, enhancing user experience and growth potential. And talking about the future outlook. In the next three to four years, along with AI technology, and the application trains that I just mentioned, based on our industry know-how, we will further consolidate our leading position in the [interact] industry.

Tracy Lee

Thank you for listening. And ladies and gentlemen, with that, we will conclude today's earnings conference call. We do thank you for joining. Have a good time.