Earnings Call: H2 2024

Mar 26, 2025

Summary

FY24 revenue rose 9% and adjusted net profit reached CNY 376m, while reported net profit declined. FY25 guidance targets double-digit revenue growth, with higher AI investment and near-term margin pressure expected.

Dear investors, analysts, and friends from the media, good afternoon. My name is Sandy Cheng, Director of IR at Bairong. I would like to thank all the investors online for following the development of Bairong. Bairong has released its 2024 annual results today, March 26, and will report and share the company's 2024 annual operating results as well as outlook for 2025, and answer your questions. This earnings call will be divided into three parts. Our CEO will present the business progress and outlook, followed by our CFO, who will interpret the financial performance, and finally, the Q&A session. All of our participants can enter their questions into the question bar of the live broadcast platform or call the following phone numbers. 02363623333, or 400-806-3263 from mainland China, or 301-836-02 or 800-961-505 from Hong Kong, or 2362-7371-00 from international. The passcode for Chinese line is 297236054, and for English line is 290534058. Managers will be happy to answer questions after the presentation. The earnings announcement contains forward-looking statements that reflect the company's current beliefs and expectations regarding the future. These statements contain words such as "anticipate," "believe," "intend," "estimate," "expect," or words of similar meaning. All statements other than statements of historical fact contained in this meeting are forward-looking statements. These forward-looking statements reflect the views of the company's management as of the day thereof and are not guarantees of future performance. Neither the company, any member of the group, nor any of its relevant affiliates, nor any of their respective directors, officers, employees, consultants, or representatives undertakes any obligation or expressly disclaims any obligation or undertaking to disseminate any forward-looking statements that are updated or revised. Now, I would like to introduce the company's management team present at the earnings meeting today. They are Mr. Zhang Shaofeng, Founder, Chairman of the Board, and CEO of Bairong. Executive Director, Senior VP, Chief Financial Officer, and Head of BaaS Insurance Scenario, Mr. Zheng Wei. Senior Vice President of Bairong and Head of MaaS and BaaS Financial Scenario, Mr. Duan Ying. Now, I would like to invite Mr. Zhang Shaofeng, Founder, Chairman of the Board, and CEO of Bairong, to update you on the business progress in the year 2024. Dear shareholders, investors, analysts, and friends from the media, good afternoon. Welcome to the 2024 annual performance announcement of Bairong. It is my great honor to update you on Bairong's business performance and growth and to share with you our views on Bairong's long-term development. First, I will briefly introduce Bairong. Our business primarily utilizes AI technology to assist thousands of institutions in two main areas. First, to help them manage risks and client assessment, be it for financial services, insurance, or non-financial services. We call this segment Model-as-a-Service or MaaS. We use technology to model risks and to manage risks, and we also provide marketing support to help our clients generate more income. In other words, we assist our clients in our effort to cross-sell and to increase their revenue. The Model-as-a-Service system, which leverages AI modeling to aid intelligent decision-making, receives on average about 300 million calls a day. Then we, through generative AI and VoiceGPT, support intelligent marketing and operations known as BaaS or Business-as-a-Service. We are able to deliver services and charge for fees on top of those services. We have made great progress and we have developed first-class infrastructure. Moreover, based on the AI GPT technology, we've developed AI products such as CybotStar and AvatarGPT. CybotStar is an AI agent platform that can help institutions solve practical business problems in a variety of processes and scenarios. To date, we've accumulated over 7,000 institutional clients, including household names such as Alibaba, Tencent, ByteDance, Xiaomi, ICBC, Bank of Communications, Ping An, SPDB, China Life, China Taiping, and Taikang, among others. Some of the marquee accounts contributing tens of billions in revenue to our company. Second, I'll present the highlights of our operations. The macro environment last year was very challenging. Market interest rates fluctuated, and banks were not having an easy time, particularly in terms of net interest margin, there was persistent pressure. According to data from National Financial Regulatory Administration, net interest margin, or NIM, declined from 1.69% in 2023 in fourth quarter to 1.52% in fourth quarter 2024, mainly due to factors such as reduction in loan interest rates, competition for deposits, and adjustment to existing house mortgage interest rates. By the fourth quarter of 2024, non-performing loan, or NPL ratio, dropped to 1.5%, down by 6 basis points from the previous quarters. However, it was still relatively high, and therefore, 2024 was a year of weak consumption and low credit confidence. The external environment was complex and challenging, but Bairong held its ground and achieved revenue growth and sustained its profitability. Our MaaS business resumed its double-digit growth in the second half of the year, which was really not easy because last year and this year saw shrinking client budget. In other words, our growth was achieved on the back of capturing market shares and wallet shares. Our BaaS business also maintained stable growth, especially the BaaS financial scenario revenue driven by generative AI, which increased by 19% year over year. Our gross profit margin remained above 70%, indicating that our investment in AI has not only brought us first-mover advantage, but also created economies of scale. In 2024, our profit margin reached CNY 266 million with a profit margin of 9%, a decline compared to 2023. However, the adjusted net profit reached CNY 376 million. The adjusted NP margin was 13%. In this challenging environment, we still achieved business stability and sustainability. It couldn't have been achieved without the long-term support, trust, and loyalty of our shareholders, investors, and analysts. On behalf of Bairong, I really want to thank everyone for your effort. Now I'd like to go over some of the work we've done in AI. I believe Bairong's greatest opportunity lies in artificial intelligence. AI is one of the most revolutionary and disruptive technologies in history. It is definitely going to transform productivity, and I think there's a consensus forming, which is the era of generative AI has arrived and almost every industry will be transformed by this new technology. Fortunately, we're at the front and center of this technological revolution. We believe the AI industry has a five-layer structural system. At the bottom layer, at the general purpose computing power and general purpose models, such as infrastructure, DeepSeek, Qianwen, and NVIDIA chips. Those are infrastructure solutions. They're like utilities that provide basic services and fundamental services. The second layer up is industry where case-specific computing power and models. For example, NVIDIA introduced some specific or specialized chips just recently, and we call those players at this layer the model factory. This is where Bairong has done very well because we have developed models catered to specific industry fields and scenarios. We would train our model to reduce the size and to improve responsiveness so that we can reduce customer cost when it comes to computing power purchase or utilization. Then we can also improve accuracy and reduce hallucination thanks to our specific training efforts. Then the third layer is what we call Cybot, which is the workflow and intelligent agent construction layer. This layer is a layer of development tools. This layer makes it possible for average employees to use drag and place to very simply create intelligent agents. The next layer is what we call agent market or agent store, where marketing, sales, legal, HR personnel are able to take advantage of applications at this layer. Those applications are task-specific, and these are what we usually know are our agents. We believe there is not going to be much, if any, general-purpose agents. Rather, these agents are going to be specialized. Then on top of that, you have CRM, ERP, and other systems that have integrated these agents. So some of the features will be replaced by agents, while some will be still traditional software. Bairong focuses on the second and the third layer. We develop industry-specific LLMs as well as the model factory that we built to make it possible for people to very easily develop the end agents that they can use. In the future, we might move up the layer, in terms of developing AI applications for the end user. Next, I would like to go over our business development. Over the last period, we have been fully committed to the R&D of AI technology. We have developed AI technology infrastructure that has put us in a very competitive place, in terms of product capabilities. Our VoiceGPT technology is fully self-developed, meaning that we are able to develop solutions from end-to-end, from the underlying layer to the application layer. Our LLM and NLP model is also fully self-developed, including the full stack training capabilities such as pre-training, post-training, SFT, DPO, and other activities. We have completed the training and deployment of multi-scenario and multi-model applications, be it risk management, marketing, or loan collection, or contract approval, and other tasks. We have also developed AI products such as CybotStar, AI agent platform, and digital human all-in-one machines. in 2024, our VoiceGPT made significant progress, and we have also made great progress elsewhere. 95% of the core technologies are self-built, and therefore our infrastructure cost is only 20%-30% versus our peers. In terms of voice synthesis, we support over 20 dialects and are able to express emotion in different scenarios with our model. Our model is able to continually improve and reinforce itself. They are able to learn from real-life interaction and with the user, and to become stronger over time. Now, in terms of product portfolio, we introduced a brand-new product, the CybotStar Enterprise Intelligent Agent platform. We know that ByteDance has Kouzi, and Alibaba has Bailian. While we face enterprise customers, Kouzi is more end-user facing. CybotStar is specifically designed for enterprise customers, and its mission to help clients apply large models to their various business scenarios. CybotStar, where the agent is able to take actions, it's not just a brain. Obviously, the brain is the LLM, but CybotStar is the brain plus the body. It's able to process text, image, videos, and it's able to get integrated into mails, messages, Weixin, including WeChat. We cover clients from insurance, financial services, as well as retail. In terms of payment models, our clients can choose to pay based on subscription, pay by project, or based on the revenue that they're able to generate. This is a flexible pricing model for our clients, and CybotStar is a very powerful and flexible platform that can meet the needs of different industries and companies of different sizes. We're very excited about the future of CybotStar, and we look forward to working with customers moving forward. Bairong has been widely recognized by all areas of society. In the first half of the year, Bairong's large model, BR-LLM, won prestigious awards. We were selected together with other LLMs such as Pangu, ERNIE, and Qwen into the 2023 annual Large Model Vitality List, which was a list put together by the Chinese Academy of Social Sciences. BR-LLM was also awarded the 2023 Annual Product by the Chinese Academy of Social Sciences and eNet Research Institute. In the second half of the year, we received more honors. In the 2024 New Technology Top 100, we were selected again by the organizer, and we were awarded the 2024 Large Model Innovation Application Award. We were given the CMMI Level 5 certification, the highest level by global standards. This means that we've reached the world's most advanced level in terms of software development, project management, and continuous optimization. CMMI, which stands for Capability Maturity Model Integration, is the authority in software development capability assessment, and Level 5 is indeed the most difficult to obtain. We've obtained 219 patents and software copyrights by the end of 2024, covering fields such as artificial intelligence, machine learning, privacy computing, human computer collaboration, and multimodality. Next, when it comes to ESG. As a leading enterprise in the field of data with a significant corporate social responsibility, today, I would like to share with you a particularly meaningful project, one that Bairong has recently participated in. This project is beyond financial sector. It's called AI Heartwarming Hut. We worked together with organizations who care about adolescent wellbeing and developed a program empowered by AI technology. We want to look out for the wellbeing, especially mental wellbeing of young teenagers. We know that many of them suffer from mental stress. Sometimes there can be dangerous incidents incurred by such mental stress. That is why we donated AI Heartwarming Huts to over 100 counties across China. This hut serves as an AI-powered emotional support center. It does come in the physical shape of a hut, and it features an integrated digital human system designed in the image of Dasheng or the Monkey King. This digital human interacts with children in their daily life, offering companionship and emotional support without the supervision of teachers and parents. So the kids can tell this Monkey King avatar what's making them unhappy or their concerns. The kids do not necessarily want to tell these things to teachers and parents, but they might want to share it with the AI digital human AvatarGPT. This kind of interactions can help them open their mind and address potential psychological pitfalls. At the core of this digital human is China's first large-scale AI model dedicated to adolescent emotional support. We have trained this model extensively with knowledge related to youth psychological care, as well as a wealth of general knowledge. This enables our digital human to answer many whimsical and imaginative questions. Moreover, the AI model can analyze speech tones and emotional cues, allowing the synthesized voice to carry a natural emotional warmth, ensuring that the conversations with children are empathetic. Beyond emotional companionship, we have equipped the AI Heartwarming Hut with additional capabilities, building a powerful intelligent ecosystem to extend the protection of adolescent wellbeing. For example, our smartwatch features real-time location tracking and heart rate monitoring, helping to detect potential bullying incidents in schools, because when kids are bullied, their heart rates go up, and automatic messages and notifications will be sent to teachers and school regulators so they can intervene in time. This has attracted a lot of positive attention from across society. We have implanted this in Beijing, Shenzhen, and Hebei, among other places. We will continue to work in this direction by collaborating with charity organizations so that our AI-powered hut can reach out to more adolescents, giving them a brighter, more intelligent future. At the same time, this year, we officially launched our integrated AI Green Finance Business Solution. This solution is our response to the national dual carbon strategy. It helps companies detect green projects. It can also help them with benefit assessment, ESG risk monitoring, thereby enhancing productivity. Our solution aligns closely with the action plan for promoting high-quality development of digital finance, jointly issued by its National Financial Regulatory Administration, the People's Bank of China, and five other departments. The plan encourages financial institutions to leverage carbon accounts, carbon emissions data, and ESG scores to explore innovative financial products and service models. There are several highlights. Number one, it is an integrated system covering underlying information systems, business processes, and top-level design. It meets diverse practical needs, including finance. Second, it has two AI capabilities. We have embedded our foundational large model, which is BR-LLM, and our AI agent application platform, CybotStar, bringing groundbreaking innovations to multiple scenarios and processes. It is also a 3-in-1 management system. Our solution helps financial institutions establish an effective management framework for clients, portfolios, and institutions. Fourth, it covers development on four fronts, supporting financial institutions in digitalization, informationization, technological innovation, and the data infrastructure to enhance green finance initiatives. It has already been implemented at two joint stock banks, achieving breakthroughs in environmental and corporate benefits. It was also recognized by the Ministry of Industry and Information Technology. Green finance not only benefits the present, but also ensures long-term sustainability. As a pioneering AI technology provider, Bairong will continue to leverage AI innovation, empowering financial institutions to explore new pathways and models for green finance development. Sixth, last but not least, I want to share with you our work plan and outlook for 2025. We will deepen our focus on vertical industries while expanding our investments in cross-industry fields. We are going to expand to non-financial sectors so as to achieve a business layout driven by AGI, structured along both vertical and horizontal dimensions. Our plan consists of four key areas. IT infrastructure, IT AI infrastructure. One is general IT infrastructure. Second, specialized AI infrastructure. Thirdly, AI internal empowerment for contract review, HR recruitment, our own customer service. The fourth will be something that we export, which is AI capability products. It is intelligent body itself. Let us zoom in on IT infrastructure. We aim to make our internet systems more flexible by adopting containerized and pooled technologies to enhance scalability. Additionally, we plan to unify multi-cloud and hybrid cloud management to improve operational efficiency. IT resources will be optimized based on the needs of different business units, with a goal of achieving 99.999% system reliability while cutting unit business costs. We will continue developing multimodal large models for text and voice with the goal of building a world-class AI voice infrastructure. We will buy more GPU, more training data. We will also recruit more high-caliber talent so that our AI infra or AI infrastructure will go from strength to strength. We aim to build a world-class AI infrastructure, and we plan to integrate AI into various internal operations, such as coding, image generation, and report generation. Today, AI is used to automate internal processes. About 20% of our codes are generated by AI automatically. Our internal codes are rather complicated, so 20%-25% is already a very high percentage of automated AI-generated codes for our processes. At the same time, we will bring our CybotStar AI products as a platform to the market while launching digital human products and voice agent solutions. In 2025, we will definitely drive business growth and technological innovation through increased investment, enhanced infrastructure, improved internal efficiency, and the development and commercialization of AI products, both in terms of financial segment and non-financial business. We believe what we invest this year will pay off in the year after next or maybe next year. If we do not invest today, then we will meet more obstacles in the future. That is why we have to do that now. In order to better seize market opportunities, Bairong has also undergone a comprehensive strategic upgrade. We are going to significantly enhance our R&D and business investments. We are going to occupy more market share regardless of cost, especially in pan-AI industries and more generalized AI use cases. In the general finance AI segment, we want to focus on customer service and payment collection. Previously, this kind of business used to be limited by number of headcounts you can hire, but our service breaks that boundary and allows us to increase the supply indefinitely. For internal operations, AI helps us reduce costs and improve efficiency in contract review, customer service, HR recruitment. It has already helped to cut our cost significantly where 80%-90% of the workload is carried out by AI and the cost is only 10% of what it used to be. This includes text-based and image-based intelligence systems. Our text-based customer service will be launched soon. This not only boosts efficiency but also reduces labor cost. Bairong's AI voice customer service agent is about to be launched. Industries such as retail, FMCG, and education are already benefiting from our AI solutions. We will continuously expand our business frontiers, leveraging AI to empower more industries step by step. With large-scale investment, this may put pressure on Bairong's profitability in 2024 and 2025, but I firmly believe that these efforts will deliver longer-term value and returns in the years to come. This concludes my brief remarks for Bairong's 2024 performance and future outlook. Thank you all for taking time to attend the 2024 Bairong Annual Performance Conference. Thank you. Thank you, Chairman John Fang, for your insightful and detailed presentation. Now, let's invite company partner, CFO, Senior Vice President of BaaS Insurance Industry Cloud, Mr. Zheng Wei, to present the 2024 performance and financial highlights. Thank you to all shareholders, investors, analysts, and media friends for joining us today. I will now walk you through Bairong's 2024 financial performance and highlights. First, financial overview. In the past year, our revenue reached CNY 2.929 billion, a 9% increase from last year's CNY 2.681 billion. Despite a challenging year, Bairong successfully achieved stable revenue growth and maintained sustained profitability. Gross profit reached CNY 2.142 billion, a 10% increase from last year's CNY 1.955 billion. Gross profit margin remained stable at 73%, primarily benefiting from the scalable AI cloud business model, which further realized the benefits of scale. Operating profit reached $285 million, with an operating profit margin of 10%. Net profit reached $266 million, with a net profit margin of 9%. Non-IFRS net profit reached $376 million, with a non-IFRS net profit margin of 13%. Non-IFRS EBITDA reached $486 million, with a non-IFRS EBITDA margin of 17%. Now, before we dive into different business lines, let's take a look at revenue structure. In 2024, our revenue saw steady growth, driven primarily by BaaS revenue, powered by generative AI, which grew 12% year-on-year to CNY 1.997 billion, accounting for 68% of total revenue. Within the BaaS business, financial industry cloud revenue grew 19% to CNY 1.411 billion, accounting for 71% of BaaS segment's revenue and 48% of total revenue. Insurance industry cloud actively responded to regulatory changes and witnessed a slight decline of 3%, hitting CNY 586 million, accounting for 29% of BaaS business revenue and 20% of total revenue. Our other business, MaaS, saw a 5% increase in revenue, reaching CNY 932 million, accounting for 32% of the total revenue. Now let's zoom in on MaaS business line. Our MaaS business aims to assist institutional clients in decision-makings by providing models and evaluation results with diverse application scenarios. In 2024, the CNY 932 million in MaaS revenue came predominantly from core clients who contributed CNY 300,000 annually. These core clients accounted for 76% of MaaS revenue. The number of core clients reached 211, with the average contribution per core client hitting CNY 3.37 million. Our BaaS business aims to enhance the efficiency of assets operation in vertical industries by leveraging generative AI and large models, and allows for large-scale reuse in various sub-segments such as banking, insurance, wealth management, and inclusive finance. Our BaaS financial industry cloud primarily helps institutions achieve more efficient intelligent marketing and intelligent operation, covering business scenarios such as retail lending, small and micro-lending, wealth management, and leasing e-commerce. The BaaS financial industry cloud charges a technical service fee based on the size of asset transactions facilitated. In 2024, as a leader in AIGC application implementation, our BaaS financial industry cloud revenue grew 19% to CNY 1.411 billion. Our insurance industry cloud deployed nationwide through Dong Insurance Brokerage. Our decision-making AI provides comprehensive customer insights, accurately recommends insurance products, and operates high-value policies with the help of generative AI and offline insurance brokers. We charge a commission based on the premiums of the policies sold. In 2024, our BaaS insurance industry cloud generated CNY 586 million in revenue. In terms of revenue structure, new policy revenue was CNY 487 million, down by 4% from last year's CNY 508 million. Life insurance renewal rates continued to exceed 90%, ranking among the top in the industry. Renewal revenue reached CNY 99 million, up by 2% from last year's CNY 97 million. Total premiums reached CNY 5.442 billion, up by 63% from last year's CNY 3.331 billion, significantly outpacing the 5.7% industry growth rate reported by the National Financial Regulatory Administration. Now let's look at profit and loss. In 2024, our gross profit margin remained stable at 73%, primarily benefiting from the scalable AI cloud business model, which further realized the benefits of scale. R&D expenses reached CNY 509 million, up by 34% from CNY 379 million in 2023, accounting for 17% of total revenue. The company continues to increase investments in AIGC and large models to support product supply and technological development. During the reporting period, our VoiceGPT intelligent voice product made significant progress in both technology and application, establishing top-tier infrastructure with all technologies being self-developed, effectively lowering costs. In addition, we successfully launched the CybotStar enterprise-level intelligent platform and have integrated large models such as DeepSeek, aiming to solve the application of large models in customer business scenarios. Sales and marketing expenses amounted to CNY 1.119 billion, accounting for 38% of total revenue, down by 2% compared to last year's or the previous year's total revenue. General and administrative expenses was CNY 328 million, accounting for 11% of revenue remaining stable. Net profit reached CNY 266 million, down from last year's CNY 335 million with a net profit margin of 9%. Non-IFRS net profit reached CNY 376 million with a non-IFRS net profit margin of 13%. In 2024, our cash equivalents, and similar financial assets totaled CNY 3.657 billion, a 9% decrease compared to CNY 4.032 billion at the end of last year. This decrease was primarily due to Bairong enhancing the efficiency of fund usage, increase in strategic investments, and repurchase efforts. The CNY 3.657 billion include cash and cash equivalents, CNY 739 million, large certificates of deposit, CNY 2.437 billion, and CNY 480 million in current financial assets measured at fair values through profit and loss. The company remains confident about its long-term future, and in 2024, the company repurchased a total of 25.49 million B shares from the open market, totaling 238 million Hong Kong dollars. As one of the few AI companies in China to have successfully implemented generative AI in practice scenarios and achieved profitability, Bairong has maintained a stable revenue growth and sustained profitability in 2024. Looking ahead, Bairong will continue to increase investments in R&D and marketing while empowering industry through AI. Thank you, everyone. Thank you so much, management, for the wonderful presentation. Now we open the line for questions. If you wanted to ask a question, please press the star key followed by number one on your phone. First press the star key, then press number one. For investors and analysts who are participating online, please type your questions in the Q&A section in the online platform. I will read the questions to everyone later. Please state your name and the names of your institution before asking questions. Thank you. Thank you. We have a few analysts who are waiting in line. Hi, my name is Xu Ran from Morgan Stanley. Hi, this is Xu Ran speaking. I am from Morgan Stanley. Thank you. My first question is about AI. There has been a really rapid development of AI technologies. My question is regarding management's view on DeepSeek. In particular, what are the core advantages of CybotStar versus DeepSeek? If there is room for cooperation, and also perhaps we can compare Cybot with Doubao and Yuanbao as well. We are a leader in the financial vertical. Just wondering, what are the key differentiators you have in the AI field? Thank you. Shaofeng will answer this question. Thank you so much for your question. This is indeed a very relevant question for many investors, and we were asked the same question many times since the emergence of DeepSeek. I think the emergence of DeepSeek is definitely a net positive for the industry, because it has definitely made AI a household technology almost overnight. I think that awareness improvement has been very positive. We can also leverage DeepSeek to develop agents. That is a positive for us as well. In terms of the cons, in the short to medium term, there is some negative impact as well because DeepSeek is freely available and it is also open source. Some large institutions might have this perception, which is perhaps they can develop LLMs by themselves, or they can deploy LLMs by themselves. Some large financial institutions had budgets still for AI models by the end of last year. But in Qwen, they put the budget on pause because now they wanted to give it a try themselves first. That is, I think, in the short term, a negative impact. Also, in a short period of time, you might, or rather in the short term, you might start to see a lot of small new entrants. Small startups who are technology service providers just like us. I think that is a negative as well. These two negative factors are mostly impacting our top line. I think in the medium to long term, it's going to be positive for us, because similar to Qwen as well as some of the other LLMs, we're talking about general purpose LLMs that are not specialized for specific tasks, and cost will be high, and then response tends to be slow, and hallucinations are bound. The other thing is, even with LLMs, you still need to build agents by yourself. Agents and LLMs are different. Many people have this misconception that AI equals LLM equals agents. Actually they're not the same thing. So with AI, you have generative AI, but then there's also decision-making AI. So AIs come in different flavors, and then AI is just the brain. For you to have a functional agent, there's a lot other things that need to be added. So I think customer education is definitely needed. In the meantime, I think for us, it's just really be patient. Over time, these institutional clients will realize that AI is not the same as agent, and they still need to rely on specialists such as us to help them build agents and to deploy AI models. I think DeepSeek is almost a symbol with political backing and with patriotism, or patriotic sentiment attached to it. You've seen so many announcements from SOEs as well as local governments regarding their deployment of the DeepSeek model, because nobody wants to be left behind in this wave. I think, in the short term, there is negative impact. I'm going to be honest about it, but that's going to be short term. So short term, we expect some pressure on the top line, especially with our larger institutional clients. However, DeepSeek is not the only flavor of AI, and AI is not agent. Also, the AIs can be generative AIs or can be decision-making AIs, and that which means impact for us is going to be short term. Secondly, DeepSeek is general purpose AI, while we specialize in industry-specific AI, and then CybotStar is able to be very important in terms of actual applications. We are different from Coze in that Coze is more a consumer-facing, media-facing type of technology. But when it comes to enterprise AI, I think you need to align values. You need to make improvements. You need to also be cost-effective. Enterprise applications need to have attractive ROIs, unlike applications that are facing consumers. Not to mention hallucinations. So we develop our technologies with business clients in mind. Yuanbao is also very different. Yuanbao is more like an agent that's a competitor to Alibaba's Quark. While CybotStar is more of a agents builder, which is different. So we may be compared with Coze, but we're definitely not the same as Yuanbao. Yuanbao and Doubao and Quark, they are consumer-facing AIs or AI models, while CybotStar is something that's completely different. So in answer to your question, I think perhaps there's going to be some pressure on the top line, especially from large institutions. But then with small or SME clients, we don't think that there's going to be any impact because they don't have the ability to deploy AI models by themselves. I think even with large institutional clients, it's really just a matter of time, and by the second half of this year, they will have realized their misperception, and they will have come back again to our services. Thank you so much for your answer, management. That's great. Yes. I wanted to add that the emergence of DeepSeek has been a net positive. It's also increased the watermark for the industry. The reason why we will not stop at any cost in terms of development, in terms of achieving differentiation, is because even with open source or free solutions, you already have a vast level of certification. Therefore, we will continue to increase our R&D to that effort. Thank you. Our next analyst in line, please. Thank you. Thank you, management, for taking my question. I am Uma from CITIC Jiantou, or CSC Financial. In particular, I know that the company has been expanding into non-financial services. However, I know such expansion is not easy. Just wondering how should we think about the company's potential making breakthroughs in those non-financial sectors? Answer. Thank you, Mr. Wu, for your question. We will continue to double down on financial services, but we will continue to invest in non-financial sectors as well. In terms of what we do with the financial services, there is MaaS, which is risk assessment, risk management, and then there's also marketing, which is about profit-sharing. We also now help our clients on compliance, on marketing material development, as well as on, for example, research note development. I think pricing model will be challenging. We all know that software subscription is a challenging model in China. With generative AI, we're able to achieve many great things. We can either charge by project, for example, if you've successfully recruited a person or you've successfully completed a project or have completed a research note, you can charge based on that. Or you could, for example, charge by FTE. For example, before an article would take about 55 minutes to complete. Now, with our solutions, you're able to finish it within, let's say, 35 minutes. So you can perhaps arrive at the time you can save for completing a contract. You can charge for the difference or for the cost saved. Obviously, this type of pricing, I think, requires Bairong as well as its peers in the industry to come to consensus with the end user. I think there's going to be a lag, which is understandable. But I think the important thing for us, for Bairong, is to explore different avenues to identify legitimate needs and to develop solutions to address those needs. We need to continue to communicate with clients to change the way they pay for services and change the way they develop budget. Even in the financial services sector, we still face challenges because there are many clients who charge by, for example, projects, which is already the preferred way because every project can be half a million or 1 million, or it could be by FTE, which is only, let's say, CNY 3,000 or CNY 5,000 a month. That, for us would not be able to make much, if any, profit. Obviously, we need to work with clients and to change their mindset. So I think for us, there are 2 tasks. The first is to identify a legitimate need, the second to change a client pricing perception. Obviously, when we expand into non-financial services, it's going to be more difficult because we're already a specialist in financial services, not to mention that clients in financial services tend to have deeper pockets. I think there are a lot of solutions, for example, VoiceGPT that are industry agnostic, which can be deployed in financial services, but also non-financial services such as call centers. I think we are definitely able to expand into non-financial services, but there is going to be challenges in terms of how we price our products. As an industry leader, we have a responsibility to educate the market, to define the market from scratch. BaaS and MaaS, both of these products were defined by ourselves. Nobody created such products in these categories. We used our own models to create the whole segment. Obviously as spearhead or as somebody who spearhead and create something from scratch, you have to pay for a lot of cost and then you will see a lot of challenges. Thank you both for the question and the answer. Let us take the next question from the phone. From Great Wall Securities, we have Analyst Chang Hong Yi on the line. Thank you, management. I am from Great Wall Securities. I am the Chief Technology Analyst. My name is Chang Hong Yi. I am very glad to be here to learn from you. My question has to do with your AI product portfolio. You mentioned you are going to invest a lot this year. Where do you see yourself in 5 to 10 years for Bairong? Is it like BaaS or AI models? Where do you want Bairong to be in terms of the size, volume or standard? Who are you benchmarking against? That is the first question. Mr. Tang, why do you just finish all the questions to let the management answer? I actually have a lot of questions. Do you need me to All right. Let me take your question. Mr. Tang, there is no benchmark. Let me just tell you clear cut, no benchmark for us. Short and clear. We are carving out a new path on our own. Maybe someday we will become the benchmark for somebody else. Question. In the area of AI, you mentioned we are trying to craft vertical models, but be it overseas or domestic models, the general AI models are trying to make inroads into vertical AI models. We started with verticals. Maybe you have specialized models, but it is kind of challenging for us to expand into general AI models in terms of the fine-tuning, this whole operational methodology, like the R&D process, which is going to take the same amount of resources. We are trying to shift it from vertical to general. Is that the case? Let me clarify. It is not general. It is more like a 10 industry AI model. When you say general AI, is it like a general intelligent agent or is the general AI model? We do not do large models, but we could provide a general intelligent agent for, let us say, HR recruitment or customer service. It's not really general in a general sense. A kind of cross-industry specific modules. They're specific to the different use cases of industry. If I understand you correctly, you're talking about the specific verticals within the industry, right? But when we use the term vertical, there are several meanings attached to it. Number one, it's industry specific. Second, it's use case specific or put in other words, for example, recruiting is one use case. Every industry has recruitment needs, but recruitment is different from legal review, so it's still vertical in a sense. It's specific to a specific task. Office would be the contrary example because every industry uses Microsoft Office. Basically you're saying it can be cloud, video or text. I'm trying to ask for computers, the data it processes. The use case it handles, every industry has recruitment needs, but the glossary they use are mostly general. But when it comes to voice recognition, specific industries will use specific jargon in the recruitment process. So when it comes to that specific terms, your model's recognition and ability to understand these different jargon will be of a different level. Is that the case? How do you see Bairong in 5 to 10 years? Do you want to tackle these verticals one by one and gradually becoming a more well-rounded general AI model? Because if you can cover all industries, it's not general in a true sense. But if you have all industry covered, then maybe the aggregated whole is also kind of a general model. Well, every industry has recruitment needs. If your model can cover 60% to 70% of different industries' recruitment needs, does that make you general? I guess it is general recruitment. Then same for training for contract review. It's all under HR, but it's use case specific. Recruitment is different from contract review or training, so it's pan-industry. By your definition, you are just saying that in specific areas, in specific use cases, it spans multiple industries at the same time. But sometimes an industry can be very technical. You have to understand the jargons, the glossaries. You have to make decision beforehand as to whether it's worth diving into if they are a high-value use case. Usually, recruitment price is CNY 1,500 per head count. Now, if they can pay CNY 15,000, that obviously is going to worth it. But you also have to look at the volume. If they pay CNY 2,000, only slightly higher than CNY 1,500, but your volume is much smaller, so that's not enough output for the input we invest. So when I say pan-industry, what I really mean by that is that we span certain industries. It can be applied to maybe 30%. If it's only applicable to 4 to 5 different industries, only 45% of the industry is too narrow. I wouldn't call it pan-industry. So if I understand correctly, your models, you want it to span 30-plus different industries, and then in specific use cases such as recruitment, marketing, legal, those functional tasks, you want your model to deliver better coverage across several industries, right? In selective industries. Yes. Basically, we want it to apply to the same use case across different industries. The use case itself might be slightly general, but it is by no means a general AI in and of itself. Thank you so much for your question. We also have questions raised online through the chat function. Let me read the questions. The first one is from CICC, Liada. Thank you for giving me the chance to ask the question. I am CICC analyst Liada. I would like to ask a question about your 2025 income and profit guidance. Where are you going to spend most of the R&D budget in 2025? How will investment in new business areas affect the company's profitability? I am going to give the floor to the CFO. Thank you. As I just reported during the financial highlights, 2024 is going to be a year where Bairong showcases our flexibility and resilience. In the second half of the year, we saw a 22% increase. Our MaaS business has also witnessed a positive recovery. The fundamentals it stands for profit, the cash flow, have all maintained a high level. As you can see, in order to further deepen and widen our technical moat, our total R&D spend increased to CNY 509 million, up by 34%. We also know that CybotStar platform, digital humans, and VoiceGPT are launched one after another, getting great market feedbacks. So for our AI application capabilities, it has been going from strength to strength. In 2025, we expect annual revenue to achieve double-digit growth. At the same time, like the Chairman has said, we believe in creating long-term value for shareholders. We will continue to invest more in R&D expenses, building our technology pipeline so as to prepare ourselves for future competition. At the same time, we will improve our operational efficiency, optimize our asset allocation so as to deliver on the growth target. We believe AI is the core strategy of our company's growth. We will stay faithful to investing in AI business. My estimate, in 2025, we are going to add CNY 300 million of spending through continuous innovation and resource allocation. We will keep our leading position in the market so as to create long-term value for shareholders. Thank you so much. We have another question on the line. Jiang Den from Zhongtai Securities, please. Hi, my name is Jiang Den from Zhongtai Securities. My question is regarding something that Shaofeng just mentioned. On new technologies, we mentioned CybotStar and also new progress with regard to CybotStar. Can we get an update from management and the areas of application, please? Thank you. Thank you. This is Shaofeng. I can talk about VoiceGPT first. Our free and most abundant source of data will be interaction with real humans. We have AI who are a synthetic voice. Users who are real humans, their interaction and their emotions and their responses are real. Those data are not available anywhere online because what you can find online tend to be written text, which is very different from anything that you see online. Even with Weixin messages, those messages are different because they are written and you can potentially withdraw a message on Weixin, you can rephrase your messages. With verbal interaction, it is, I think, the most authentic way of interaction. We also would purchase corpus that are text from third-party providers. Also, we have other data sources such as voice, such as text. Again, we have our own verbal chat history, and second is from third-party providers, and sometimes we also receive data from our clients. Of course, with our CybotStar, we definitely need to differentiate ourselves from peers such as Coze. What I heard is, Coze is not necessarily receiving all that attention in terms of the 2B business. Perhaps they are more used to or focused on the consumer-facing business. Second, even if they pay attention to the 2B business, they do not necessarily have the expertise to serve institutional clients well, because it is difficult to align values and ensure that confidentiality is protected, no data leakage, and then good performance as well. A lot of our clients are large institutions who have high requirements for our solutions. We also believe that the agents we create need to be multimodality. They need to understand voice, text, video, and also needs to be able to incorporate internal data sources, such as MySQL. There is also unstructured data that perhaps lie in a client's data lakes that can potentially be leveraged as well. CybotStar is an agent that is inside of an organization, and it needs to take full advantage of that positioning, and it needs to take full advantage of the areas of, for example, resources that are available. But to make that possible, we need to continue to invest in our R&D pipeline. Thank you. We have a few questions from online. This question is from Su Chung from Minsheng Securities. The question is regarding our MaaS segment. If the management can perhaps update us on signs of recovery in the second half of 2024, and if those signs can point to improving pricing strength and growth in 2025. Following a weak year of 2024, what are our plans for 2025 in terms of expansion and in terms of further investment? Thank you for the question. MaaS is obviously based on the output that it generates, which can help our clients make smart decisions. Bairong has built very rich client profiles over the course of its history, and it has a very close partnership with many clients. We understand our clients' preferences, their business needs, and their qualifications. Among a lot of other data that we collected, which allow us to, for example, develop proprietary solutions for credit scoring and for other scoring solutions. We indeed had a year of weakness last year because of the macro environment. But Bairong is at a position of strength. It has an analyst team that's multiple times in size. It also has, equally, a much larger sales team, as well as the engineer team. This is Bairong's core advantage. In 2025, Bairong will continue to expand its R&D effort to develop its superstar products and solutions. It will also continue to develop industry specific solutions that are up to date. Bairong will continue to capture both new market shares and new wallet shares. It is our belief that our MaaS competitiveness will continue to improve, which will put us in an even more advantageous position in the market. We've been offering MaaS for close to a decade, and we are definitely a leader. From user acquisition to conversion to paying users, as well as high value users who pay us over CNY 300,000 a year, we've had a very good tier of customer base. As we continue to introduce new products and solutions, and as we continue to expand our client base, we believe that there's going to be a lot of upside for us in terms of ASP and in terms of, I think, further expansion of the client base. Thank you. Our next question is from Huatai Securities, Chen Yuxian. Thank you. This is Chen Yuxian from Huatai Securities. My question is regarding negative impact from the insurance sector. Wondering how Bairong intends to respond to the issue of declining fees. Yes. Thank you for your question. The insurance industry indeed faces multiple challenges. There is the adjustment of product pricing rates and the correction of customers' purchasing power and willingness to pay. All these things have put pressure on the demand. The insurtech and intermediary services are undergoing reshuffling with the new policy environment. Despite the short-term pressure, we are still bullish on the long-term value of the sector. We believe demand driven by demographic changes is inelastic, and it's accelerating. The demand from an older demographics and greater awareness of health all points to irreplaceable of insurance products in terms of risk management. The market is transforming from a price competition to value creation. I think, which for insurers, this means higher requirements for professional capabilities. This has created, I think, upside for Bairong to provide its specialized services. In 2024, we remain committed to customer-centric approach, deepening the development of specialized services, and enhancing capabilities for our clients. Our insurance cloud platform integrates AI to provide intelligent support for thousands of advisors. We have a network that covers over 20 provincial level regions, and we have over 100 local outlets to support operations of our clients. We have accelerated the application of generative AI and decision-making AI, and we've developed system solutions for sales optimization and customer value enhancement. On the other hand, we've accelerated the development of our support solutions for more efficient business management, which aligns with industry trends. For year 2024, the scale of premium in facilitated by us exceeded 5 billion yuan, a year-over-year increase that's much higher than the growth rate of the industry average. Our insurance business demonstrated strong resilience in a challenging environment. Looking ahead, we will continue to uphold the customer centric philosophy, deepen application of AI, enhance service experience, and improve operational efficiency. We believe that with greater professional expertise and digital capabilities, we'll be able to take leading position in the market and create more value for shareholders and our clients. Thank you, Mr. Wei. Thank you, Chen Yuxian, for your question. We have Mr. Sin Kun from Guotai Junan. The question is: In recent years, with technological innovation, financial security has also become a hot topic. There have been negative public opinions regarding issues such as personal information leakage and marketing calls harassment. How does the management view these issues from the perspective of data security and privacy protection? What measures have been taken to ensure compliance with relevant laws, regulations, and industry standards? I am going to give the floor to Mr. Duan. As a technology company focused on serving corporate institutions, we always view data security and user privacy protection as a core responsibility. The company has already passed the National Information Security level protection level 3 certification, also known as the Ministry of Public Security certification. We have also received international software industry CMMI level 5 certification, ISO/IEC 27701 Privacy Information Management System certification, the People's Bank of China Enterprise Credit Business Operating Records certificate, and China Quality Certification Center's Information Technology Service Management System and Business Continuity Management System certification, as well as certifications from the Huarca Certification Center in privacy information management, information security management system, and quality management system. Additionally, we are a member of the Privacy Computing Alliance of the China Academy of Information and Communication Technology. Moreover, we have continuously maintained an AAA enterprise credit rating in Beijing for seven consecutive years. From technology to management process, we fully meet both domestic and international high standards for privacy protection. We have made continuous investments in privacy computing, federated learning, blockchain, and other fields. We also have developed the Bairong privacy computing platform, which places us at the industry's forefront in terms of data security. Our self-developed VoiceGPT has powerful intelligent voice capabilities. In order to reduce customer complaints and improve the accuracy of product matching, we combine decision-making AI and generative AI at a commercial application level. Our MaaS business system, with its rich user profiles and product understanding, can significantly reduce customer complaint risks and deliver suitable products to the right audience through precise mass matching, so that we make sure that the right products are given to the people who really need it. This really helps to drive down customer complaints ratio. From the perspective of data security and privacy protection, we have taken various measures to ensure the safety of customer information during voice interactions. First, the conversation content of VoiceGPT. Such content undergoes strict review, both internally at Bairong and at institutional client level. Furthermore, during the pre-training and inference phases of the large model, VoiceGPT sets up a dedicated safety barrier mechanism where additional checking agents oversee the data. These measures help ensure data security and compliance. At the same time, Bairong's CybotStar provides full-process model generation control, making content generation safer. We use robust technologies and strategies to construct the three layers of defense: pre-interception, generation intervention, and post-processing. This ensures the protection of content generation throughout all stages, from input to output. This mechanism not only immediately blocks the generation of harmful or sensitive information, but also allows us to trace the entire content generation process, ensuring that the generated content is secure, reliable, and trustworthy. Thank you so much, Mr. Duan. In the interest of time, I still see a lot of questions from investors and analysts. Feel free to schedule another meeting to seek your answers. Please scan the QR code on the screen to schedule a meeting with our AI-backed assistant. Also, we are going to update you on the latest developments at Bairong through our regular announcements. If you have other questions, feel free to reach out to our IR website, ir.brgroup.com, or email us at ir@brgroup.com. Thank you so much for your participation in our 2024 performance conference. We look forward to seeing you again in our future conferences. Thank you.