代币化规模冲上 43 亿,Securitize 怎么反倒亏了 550 万美元?

marsbitPublished on 2026-08-20Last updated on 2026-08-20

Abstract

Securitize最新季度财报显示,其平台代币化资产管理规模创下43亿美元新高,同比增长16%;平台交易量达53亿美元,飙升147%。然而,公司总营收却同比下降5%至1440万美元,其中代币化业务收入下滑约12%,调整后EBITDA转为亏损550万美元。这表明业务规模扩大并未同步带来盈利增长。 公司首席财务官解释,目前绝大部分交易量尚未商业化变现,收入主要来自新项目对接等一次性服务。资产服务收入虽小幅增长,但交易变现仍是中长期机遇。管理层已将全年营收指引从最初的1.1亿美元下调至7000万-8000万美元。 行业分析指出,Securitize面临的“规模与营收脱节”是代币化行业的普遍挑战。当前收入多依赖于定制化项目落地,难以规模化;真正的持续性收入需转向“基础设施收入”模式,即通过标准化系统长期管理链上资产,覆盖权限、合规、交易等环节。简单用营收除以交易量计算费率会失真,因大量交易并未产生收益。 未来,若Securitize能成功推动代币化股票等高频交易业务,或可改善盈利;但若商业模式仍依赖项目制,即便规模持续增长,盈利压力仍将存在。行业的核心考验在于,新增规模能否不依赖新项目即自主产生持续收入。

撰文:Gino Mato

编译:Saoirse,Foresight News

Securitize 完成上市后的首个季度财报:平台代币化资产平均管理规模创下 43 亿美元的历史新高,同比上涨 16%;平台交易量飙升 147%,达 53 亿美元。

但公司总营收同比下降 5%,仅为 1440 万美元;代币化业务收入下滑约 12%,至 780 万美元;调整后息税折旧摊销前利润转为亏损 550 万美元。

相较于去年同期,该公司将更多资产搬上链,处理的业务体量大幅增加,赚到的钱却变得更少。

首席财务官解读规模与营收的落差

Securitize 首席财务官 Francisco Flores 在财报电话会议上表示,现阶段来自资产管理规模的收入占比微乎其微,平台绝大部分交易量至今没有实现商业化变现。

他补充道,代币化业务的大部分收入,依旧来源于对接全新协议、拓展业务网络这类项目。

而资产服务收入,也就是管理平台存量资金所收取的相关服务费,表现要好得多,同比小幅上涨 3%,达到 660 万美元。Flores 称,交易变现属于中长期机遇,当前商业模式尚且无法挖掘这部分收益。

Securitize 上市前的资料曾预测,公司 2026 年总营收可达 1.1 亿美元,息税折旧摊销前利润为 3200 万美元。管理层称,其中 8500 万美元营收有合同保障、属于经常性收入,或是依托现有资产规模与合作关系,因此当初的预测具备较高可实现性。

如今管理层把全年营收指引下调至 7000 万‐8000 万美元。公司上半年总营收为 3390 万美元。若要达成指引下限,下半年每个季度需要实现约 1800 万美元营收;想要触达指引上限,则单季度营收要接近 2300 万美元。

如果要实现最初 1.1 亿美元的目标,每个季度营收需要达到 3800 万美元,相当于本季度营收水平的 2.6 倍以上。

代币化资产规模和营收为何出现巨大落差

代币化平台 Brickken 首席执行官 Edwin Mata 表示,Securitize 财报暴露出来的矛盾,是整个行业都面临的结构性难题。

他提到,代币化资产的管理规模可以一路走高,但背后的商业盈利模式却很难同步规模化;仅仅把更多资产上链,并不能自动生成一套可以同步增长的商业模式。

Mata 解释,目前代币化落地大多依靠大型定制项目、专属系统对接、适配不同司法辖区,同时还要为每一次新资产发行提供大量专业服务。

每新增一类资产、进入一个全新司法辖区、推出一款新产品,往往都等于开启一套全新落地项目。当收益需要靠逐个项目定制落地来实现时,代币化资产的扩张速度,就会远远跑赢能够带来的经常性收入。

Mata 认为,真正巨大的商业机会,出现在资产完成上链之后,而非发行环节。企业需要一套可以长期管理金融产品的基础设施,覆盖权限管控、合规审查、数据上报、收益分配、企业行为处理、二级市场转让等全套能力。

这就是实施收入和基础设施收入的区别:实施收入是把资产部署到区块链所收取的一次性费用;基础设施收入,则是维持资产在链上持续运转带来的持续性费用。

在他看来,想要拿到基础设施收入,代币化行业需要向企业软件看齐:搭建标准化基础设施,打造可复用的工作流程,一套体系同时支持多种金融产品、适配多个司法辖区。

复杂业务架构依旧需要咨询与专业服务,但核心盈利逻辑,要内嵌到基础设施本身。

为何简单计算平台费率会造成误判

Moon Pursuit Capital 创始人兼管理合伙人 Utkarsh Ahuja 认为,Securitize 这份财报很有现实警示意义:行业落地速度和商业化变现速度,完全没有同步。

他向投资者抛出问题:当资产管理规模、交易量持续扩张,商业层面会发生什么?这些增量有多少可以转化为持续性收入?利润率能否改善?业务规模做大之后,运营效率会不会随之提升?

Ahuja 表示,代币化行业正在进入理性发展阶段。过去数年市场已经验证,机构确实愿意将现实世界资产上链;现在轮到支撑该赛道的基础设施商业模式接受考验。

随着更多机构资金涌入代币化资产,投资者会更加看重收入质量、客户留存、利润率,以及长期运维资产的商业回报。这也是区分平台究竟是实打实可持续业务,还是单纯讲增长故事的关键。

如果拿 Securitize 的 1440 万美元营收直接除以 53 亿美元的交易量,看似可以算出一个不错的平台费率,但这套算法完全不能反映公司真实盈利情况。

Securitize 统计的交易量口径很宽泛,包含投资、赎回、分红、跨链资产迁移;而首席财务官 Flores 也坦言,这部分交易量中,只有极少部分可以产生收益。

更贴合现实的结论是:Securitize 至今还没有建立成熟的「平台活跃度‐收益分成」模式,这个事实,远比任何单一费率数字都更值得重视。

代币化资产的规模‐营收矛盾后续将如何演变

看涨情景:Securitize 发力代币化公开股票业务,依靠发行方代币化股票、券商能力、原子结算,催生高频交易,进而赚取交易手续费。管理层认为,相比代币化国债、信贷产品,代币化股票的交易属性更强。但该业务属于中长期业务布局,影响不会体现在今年的业绩周期内。

想要全年营收接近甚至达到 8000 万美元,下半年每个季度需要拿到约 2300 万美元营收,相比当前季度要有明显提速。

看跌情景:资产管理规模、交易量继续创新高,但底层商业模式依旧依赖一个个定制项目,代币化业务收入波动剧烈,资产服务收入增速过慢,无法对冲上述问题。

若全年营收仅仅达到 7000 万美元的指引下限,单季度仅需要约 1800 万美元营收,只比本季度略高。即便对外公布的业务规模持续创新高,调整后息税折旧摊销前利润依旧有可能保持亏损。

代币化行业接下来要面对的核心考验:当平台再新增十亿级别的资产规模或交易量,能不能不靠新项目,就自主产生持续性收入。

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Related Questions

QSecuritize 2026年第二季度的关键财务数据中,代币化资产管理规模(AUM)和营收表现分别如何?

ASecuritize 平台代币化资产平均管理规模(AUM)创下43亿美元的历史新高,同比增长16%;平台交易量飙升147%,达到53亿美元。然而,公司总营收同比下降5%,仅为1440万美元;其核心的代币化业务收入下滑约12%,至780万美元;调整后息税折旧摊销前利润(EBITDA)转为亏损550万美元。这形成了业务规模扩大但收入和利润却下降的显著矛盾。

QSecuritize 首席财务官(CFO)是如何解释平台规模(AUM、交易量)与营收增长不同步的现象的?

A首席财务官Francisco Flores解释称,现阶段来自资产管理规模(AUM)的收入占比微乎其微,平台绝大多数的交易量至今并未实现商业化变现。代币化业务的收入主要来源于对接新协议、拓展业务网络等一次性项目实施收入,而非管理存量资产产生的持续性服务费。交易变现被认为是中长期机遇,当前的商业模式尚无法有效挖掘这部分收益。

QBrickken首席执行官Edwin Mata认为代币化行业在商业模式上面临的核心结构性难题是什么?

AEdwin Mata指出,代币化资产的管理规模(AUM)可以快速增长,但其背后的盈利模式却难以同步规模化。目前的代币化落地严重依赖为每个新资产类别、新司法辖区或新产品进行的定制化项目开发,导致收入呈现一次性、项目制的特点(实施收入),而无法随着AUM的增长自动产生持续、可扩展的收入。他认为,真正的巨大机会在于资产上链后的持续管理(基础设施收入),这需要行业向企业软件看齐,建立标准化、可复用的基础设施和工作流程。

Q分析师Utkarsh Ahuja对于简单地用Securitize的营收除以其交易量来计算“平台费率”的做法提出了什么批评?

AUtkarsh Ahuja认为,用1440万美元营收直接除以53亿美元交易量来计算所谓“平台费率”的做法具有误导性,完全不能反映公司的真实盈利情况。因为Securitize统计的交易量口径非常宽泛,包含了投资、赎回、分红、跨链迁移等多种活动,而其中只有极少部分能够为公司带来实际收益。更重要的是,这表明Securitize尚未建立起成熟的、能将平台活跃度(交易量)与收入分成就挂钩的商业模式,这个事实比任何单一费率数字都更值得关注。

Q文章对Securitize及代币化行业未来的发展提出了哪两种主要的情景展望?

A文章提出了两种未来情景展望: 1. 看涨情景:Securitize通过发力交易属性更强的代币化公开股票业务,催生高频交易并赚取交易手续费,从而将规模转化为持续性收入。但这属于中长期布局,短期内难见成效。 2. 看跌情景:资产管理规模和交易量继续创新高,但底层商业模式仍然依赖一个个定制化项目,导致代币化业务收入波动剧烈,而资产服务收入增长过慢,无法弥补缺口,公司可能持续亏损。 文章总结的核心考验是:平台新增十亿级别的资产或交易量时,能否在不依赖新项目的情况下,自主产生持续性收入。

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What is AGENT S

Agent S: The Future of Autonomous Interaction in Web3 Introduction In the ever-evolving landscape of Web3 and cryptocurrency, innovations are constantly redefining how individuals interact with digital platforms. One such pioneering project, Agent S, promises to revolutionise human-computer interaction through its open agentic framework. By paving the way for autonomous interactions, Agent S aims to simplify complex tasks, offering transformative applications in artificial intelligence (AI). This detailed exploration will delve into the project's intricacies, its unique features, and the implications for the cryptocurrency domain. What is Agent S? Agent S stands as a groundbreaking open agentic framework, specifically designed to tackle three fundamental challenges in the automation of computer tasks: Acquiring Domain-Specific Knowledge: The framework intelligently learns from various external knowledge sources and internal experiences. This dual approach empowers it to build a rich repository of domain-specific knowledge, enhancing its performance in task execution. Planning Over Long Task Horizons: Agent S employs experience-augmented hierarchical planning, a strategic approach that facilitates efficient breakdown and execution of intricate tasks. This feature significantly enhances its ability to manage multiple subtasks efficiently and effectively. Handling Dynamic, Non-Uniform Interfaces: The project introduces the Agent-Computer Interface (ACI), an innovative solution that enhances the interaction between agents and users. Utilizing Multimodal Large Language Models (MLLMs), Agent S can navigate and manipulate diverse graphical user interfaces seamlessly. Through these pioneering features, Agent S provides a robust framework that addresses the complexities involved in automating human interaction with machines, setting the stage for myriad applications in AI and beyond. Who is the Creator of Agent S? While the concept of Agent S is fundamentally innovative, specific information about its creator remains elusive. The creator is currently unknown, which highlights either the nascent stage of the project or the strategic choice to keep founding members under wraps. Regardless of anonymity, the focus remains on the framework's capabilities and potential. Who are the Investors of Agent S? As Agent S is relatively new in the cryptographic ecosystem, detailed information regarding its investors and financial backers is not explicitly documented. The lack of publicly available insights into the investment foundations or organisations supporting the project raises questions about its funding structure and development roadmap. Understanding the backing is crucial for gauging the project's sustainability and potential market impact. How Does Agent S Work? At the core of Agent S lies cutting-edge technology that enables it to function effectively in diverse settings. Its operational model is built around several key features: Human-like Computer Interaction: The framework offers advanced AI planning, striving to make interactions with computers more intuitive. By mimicking human behaviour in tasks execution, it promises to elevate user experiences. Narrative Memory: Employed to leverage high-level experiences, Agent S utilises narrative memory to keep track of task histories, thereby enhancing its decision-making processes. Episodic Memory: This feature provides users with step-by-step guidance, allowing the framework to offer contextual support as tasks unfold. Support for OpenACI: With the ability to run locally, Agent S allows users to maintain control over their interactions and workflows, aligning with the decentralised ethos of Web3. Easy Integration with External APIs: Its versatility and compatibility with various AI platforms ensure that Agent S can fit seamlessly into existing technological ecosystems, making it an appealing choice for developers and organisations. These functionalities collectively contribute to Agent S's unique position within the crypto space, as it automates complex, multi-step tasks with minimal human intervention. As the project evolves, its potential applications in Web3 could redefine how digital interactions unfold. Timeline of Agent S The development and milestones of Agent S can be encapsulated in a timeline that highlights its significant events: September 27, 2024: The concept of Agent S was launched in a comprehensive research paper titled “An Open Agentic Framework that Uses Computers Like a Human,” showcasing the groundwork for the project. October 10, 2024: The research paper was made publicly available on arXiv, offering an in-depth exploration of the framework and its performance evaluation based on the OSWorld benchmark. October 12, 2024: A video presentation was released, providing a visual insight into the capabilities and features of Agent S, further engaging potential users and investors. These markers in the timeline not only illustrate the progress of Agent S but also indicate its commitment to transparency and community engagement. Key Points About Agent S As the Agent S framework continues to evolve, several key attributes stand out, underscoring its innovative nature and potential: Innovative Framework: Designed to provide an intuitive use of computers akin to human interaction, Agent S brings a novel approach to task automation. Autonomous Interaction: The ability to interact autonomously with computers through GUI signifies a leap towards more intelligent and efficient computing solutions. Complex Task Automation: With its robust methodology, it can automate complex, multi-step tasks, making processes faster and less error-prone. Continuous Improvement: The learning mechanisms enable Agent S to improve from past experiences, continually enhancing its performance and efficacy. Versatility: Its adaptability across different operating environments like OSWorld and WindowsAgentArena ensures that it can serve a broad range of applications. As Agent S positions itself in the Web3 and crypto landscape, its potential to enhance interaction capabilities and automate processes signifies a significant advancement in AI technologies. Through its innovative framework, Agent S exemplifies the future of digital interactions, promising a more seamless and efficient experience for users across various industries. Conclusion Agent S represents a bold leap forward in the marriage of AI and Web3, with the capacity to redefine how we interact with technology. While still in its early stages, the possibilities for its application are vast and compelling. Through its comprehensive framework addressing critical challenges, Agent S aims to bring autonomous interactions to the forefront of the digital experience. As we move deeper into the realms of cryptocurrency and decentralisation, projects like Agent S will undoubtedly play a crucial role in shaping the future of technology and human-computer collaboration.

1.1k Total ViewsPublished 2025.01.14Updated 2025.01.14

What is AGENT S

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