This Week, Everyone Is Helping AI Open Bank Accounts

marsbit發佈於 2026-03-19更新於 2026-03-19

文章摘要

This week, major players in finance and tech are racing to build payment infrastructure for AI agents. Stripe and Paradigm-backed blockchain Tempo launched its mainnet with a valuation of $5 billion, introducing the Machine Payments Protocol (MPP) to enable autonomous machine-to-machine transactions. Simultaneously, Visa unveiled a command-line tool for AI payments, Mastercard acquired stablecoin firm BVNK for $1.8 billion, Coinbase upgraded its crypto payment protocol x402, and Sam Altman’s World released an AI identity verification toolkit. The core problem: AI agents increasingly need to spend money autonomously—on APIs, compute, data, and services—but traditional payment systems (bank accounts, credit cards) require human authentication, creating a bottleneck. Both traditional finance giants and crypto-native companies are converging on solutions, leveraging existing card networks or blockchain-based systems to reduce friction for AI-driven transactions. Despite the flurry of high-value investments and infrastructure launches, current transaction volumes remain minimal (e.g., x402 processed just $65.4K in 24 hours). The market is nascent, resembling early internet infrastructure build-outs where demand eventually caught up with supply. The race is on to capture what could become a foundational layer for AI commerce—whether through traditional rails or crypto pipelines.

Author: David, Shenchao TechFlow

On March 18th, another blockchain mainnet went live.

It's called Tempo, backed by Stripe and Paradigm. Stripe is one of the world's largest online payment companies, processing $1.9 trillion in transactions last year; Paradigm is one of the largest venture capital firms in the crypto industry. The two jointly invested $500 million in Tempo last year, valuing the project at:

5 billion.

A $5 billion blockchain, not speculating on cryptocurrencies, not doing DeFi, not issuing memes. On the day of the mainnet launch, Tempo's most high-profile product was:

Enabling machines to pay machines.

This might sound abstract, but you can think of it as AI now having to pay for every step. Calling an API costs money, buying computing power costs money, pulling a batch of data from a database costs money...

But the existing payment systems are all designed for humans. Bank accounts require ID cards, credit cards require facial recognition, Alipay requires SMS verification codes.

AI can't pass any of these.

It can help you complete an entire workflow, but when it comes to the payment step, it has to stop and wait for a human to press "confirm."

So, launched alongside the mainnet is an open protocol called MPP (Machine Payments Protocol), co-developed by Stripe.

Simply put, it sets rules for transactions between machines, including how to request payments, how to authorize, how to settle, etc.

The envisioned scenario is that AI can autonomously spend money within preset limits without needing human approval for every transaction. On launch day, over 100 service providers had already integrated, including OpenAI, Anthropic, and Shopify.

But Tempo isn't the only one doing this this week.

Within five days, Visa established a new department and launched an AI payment tool, Coinbase's payment protocol underwent a major upgrade, Mastercard acquired a stablecoin company for $1.8 billion, and Sam Altman's World released a toolkit specifically for AI identity verification.

Five giants rushed through the same door in one week, eager to open bank accounts for AI.

Two Paths, One Door

Tempo is helping AI with settlements. But settlement is just one part of the payment system. For an AI Agent to truly spend money autonomously, it also needs payment tools, funding channels, and identity verification.

Here, traditional payment companies and crypto companies are competing for the cake using their respective strengths.

On March 18th, the same day Tempo's mainnet launched, payment giant Visa also moved. Its newly established Crypto Labs department released its first product: Visa CLI, a tool that allows AI Agents to initiate credit card payments directly from the terminal.

No API key needed, no pre-registration required. If an AI needs to buy some service while running a task, it can pay with one line of command. Visa calls this "command-line commerce."

Visa's global card network connects billions of cards and tens of millions of merchants. If AI payments can run on this existing network, it doesn't need to wait for any new infrastructure to mature.

Visa is extending the old path. Its competitor Mastercard chose another way: buying the path outright.

On March 17th, Mastercard announced the acquisition of London-based stablecoin infrastructure company BVNK for $1.8 billion. This is the largest stablecoin acquisition in the history of the crypto industry.

The purpose of this acquisition is straightforward: if AI payments are going to use stablecoins, then let those stablecoins flow through my pipes.

On the crypto-native side, the moves are equally密集 (dense).

Coinbase's x402 protocol completed a major upgrade, expanding its payment scope from a few stablecoins to all ERC-20 tokens, while also releasing the MCP toolkit, allowing developers to integrate AI tools into the payment network with one click.

The two sides seem to start from different points, but their actions point in the same direction: Traditional payment companies are embracing crypto, crypto companies are embracing AI. Ultimately, crypto infrastructure is becoming the underlying pipeline for AI payments.

One环节 (link) remains. AI can spend money, but how does the merchant know if there's a human responsible for the AI spending the money?

On March 17th, World, co-founded by Sam Altman, released AgentKit, integrated with Coinbase's x402. It does only one thing: allow the AI to prove, while paying, that there is a verified real person behind it. The merchant can confirm that someone is responsible for the transaction but cannot see who that person is.

Five days, five companies. Settlement, channels, tools, protocols, identity. Every环节 (link) has been卡位 (staked out).

AI Cake Divided, Only the Cashier Left

Over the past three years, most positions on the AI industry chain have been taken.

The model layer is the table for OpenAI, Anthropic, Google, and a number of Chinese companies. Computing power is locked down tightly by Nvidia. The application layer is a bloody red ocean from programming assistants to search engines...

Every layer is crowded, and the competitive barriers in each layer are getting higher.

But the payment layer is still relatively vacant.

It's not that no one thought of it, the timing just wasn't right. AI Agent payment has a prerequisite: AI must first have the ability to independently complete an entire task chain. If it can only chat, doesn't need to call APIs, doesn't need to buy computing power, doesn't need to hire other Agents to work, then payment is not a rigid demand.

Over the past year, this prerequisite has slowly been established.

OpenClaw allows AI to directly operate computers, the MCP protocol allows AI to access external services, and the Agent capabilities of various large models saw concentrated breakthroughs in the second half of 2025. AI changed from a "conversation tool" to a "tool that gets work done," and getting work done costs money...

The demand for spending money has arrived, but the infrastructure for spending money does not yet exist.

This is why Stripe, Visa, Mastercard, and Coinbase acted simultaneously. For traditional payment companies, this is the first time they have gained a home-field advantage in the entire AI wave. They can't make models, they can't make chips, but payment is what they've been doing for decades.

Visa's global card network connects billions of cards and tens of millions of merchants, Mastercard covers over 200 countries, Stripe processed $1.9 trillion in transactions last year. If every AI expenditure flows through these pipes, the more capable AI is, the more money they make.

For crypto companies, the logic is somewhat different.

Coinbase CEO Brian Armstrong once said something very direct: "AI can own a crypto wallet, but it can't open a bank account."

Every step of the traditional financial system confirms "who you are." Opening a bank account requires an ID card, applying for a credit card requires facial recognition, every transaction requires an SMS verification code. AI is software, not a person; it can't pass any of these checkpoints.

But crypto wallets don't need these. A private key is an account. For an AI Agent, on-chain payment is the path of least resistance.

Crypto or not, AI payment will be a new infrastructure-level market. The difference is only whose pipeline is more suitable for machines.

Road Built, Cars Not Here

The story seems all set here, five giants are in place.

But there's a number worth looking at.

Coinbase's x402 protocol is currently the earliest landed and widest-reaching AI payment protocol. According to x402scan data, the total transaction volume of the entire ecosystem in the past 24 hours is $65,400. 150,000 transactions, averaging less than 50 cents per transaction.

What infrastructure is paired with this number? Tempo is valued at $5 billion, Mastercard spent $1.8 billion to acquire BVNK, Visa specifically established a new department, Stripe personally wrote the protocol.

Billions in valuation infrastructure, serving a daily transaction volume akin to a roadside bubble tea shop.

All infrastructure businesses seem to have this常态 (normal state).

On the eve of the 2000 internet bubble, telecom companies laid millions of kilometers of fiber optic cables under the sea. After laying them, they found that global internet traffic only used 5% of it. Most of those companies went bankrupt, but the cables remained.

A decade later, video streaming and mobile internet filled those pipes. The road pavers didn't make money, but the road was real.

AI payment is at this stage now. The demand logic is sound: AI Agents are indeed becoming more capable, they indeed need to spend money autonomously, they indeed need a new financial infrastructure.

Everyone is on the starting line, but after the starting gun fires, they find that, for now, they are the only ones on the track.

As for whose road ultimately succeeds, and when the first truly autonomous AI transaction happens in your life, it might be faster than everyone expects, or it might be slower than everyone expects.

The only certainty is that this battle has already begun, and your wallet and mine might be the last to know.

相關問答

QWhat is Tempo and what is its primary purpose as described in the article?

ATempo is a new blockchain mainnet launched by Stripe and Paradigm, with a valuation of $5 billion. Its primary purpose is not to trade cryptocurrencies or engage in DeFi, but to enable 'machine-to-machine payments'—allowing AI systems to autonomously pay for services like API calls, computing power, or data without human intervention for each transaction.

QWhich major payment companies made significant moves in the AI payment space during the week mentioned in the article?

AVisa, Mastercard, and Stripe all made significant moves. Visa launched a new tool called Visa CLI for AI agents to initiate credit card payments, Mastercard acquired stablecoin infrastructure company BVNK for $1.8 billion, and Stripe co-developed the Machine Payments Protocol (MPP) for Tempo.

QWhat problem does the current payment system pose for AI agents according to the article?

AThe current payment system is designed for humans and requires identity verification steps like ID cards, facial recognition, or SMS codes—all of which AI agents cannot pass. This forces AI workflows to pause at the payment step, waiting for human approval, hindering full autonomy.

QWhat role does encryption infrastructure play in AI payments as per the article?

AEncryption infrastructure, such as blockchain and crypto wallets, provides a low-friction path for AI payments because it doesn't require human identity verification. AI agents can use private keys to hold and spend funds autonomously, making it easier for machines to transact compared to traditional banking systems.

QWhat is the current scale of AI payment transactions on Coinbase's x402 protocol, and what does this indicate about the market?

AAccording to x402scan data, the daily transaction volume on Coinbase's x402 protocol is $65,400, with 150,000 transactions averaging less than $0.50 each. This indicates that despite massive infrastructure investments and high expectations, the actual market for AI payments is still in its very early stages, similar to historical infrastructure booms where demand lags behind supply initially.

你可能也喜歡

中国AI为什么发展得这么快?答案藏在实验室内部

本文通过作者走访中国头部AI实验室的经历,探讨了中国AI快速发展的原因及其与美国的路径差异。文章指出,中国AI的优势不仅在于人才、工程和迭代速度,更在于其务实的组织方式:少谈概念,多做模型;强调团队执行而非个人明星;倾向于自研核心技术栈而非依赖外部服务。 中国AI生态呈现出与美国不同的发展模式:美国注重原创范式、资本投入和顶尖科学家的个人影响力;中国则更擅长在已有方向上快速追赶,通过开源协作、工程优化和大量年轻研究者的投入,将模型能力迅速推向前沿。中国的许多核心贡献者是学生,他们带着谦逊和专注投入工作,较少受个人主义或哲学讨论的干扰,更专注于模型构建本身。 在产业层面,中国公司普遍持有“技术所有权”心态,倾向于自建而非购买技术栈,大型科技公司纷纷研发自己的大语言模型以掌控核心技术。尽管对英伟达算力有强烈需求,且国内数据产业不如西方发达,但中国AI需求正在增长,更接近云市场的支出模式而非传统的SaaS市场。 文章认为,未来的AI竞争不仅是模型能力的比拼,更是组织能力、开发者生态和产业执行力的竞争。中国AI正以自身独特的方式参与全球前沿,两种不同的发展路径正在形成。作者最后强调,尽管存在地缘政治紧张,但全球开放AI生态的繁荣对世界更为有益,并表达了对中美在AI领域协同发展的期望。

marsbit15 小時前

中国AI为什么发展得这么快?答案藏在实验室内部

marsbit15 小時前

3年5倍,百年玻璃厂重生

本文探讨了拥有175年历史的玻璃制造商康宁公司如何在AI数据中心建设浪潮中,借助光纤需求爆发实现业绩与股价的飞跃。文章核心内容如下: AI数据中心对光纤的需求出现结构性爆发,根据CRU数据,年增长率高达75.9%,导致供需缺口扩大。英伟达为此投资康宁等三家公司,总金额达45亿美元,旨在打通从激光器、光芯片到光纤的全链条。康宁作为被选中的光纤供应商,承诺大幅扩张产能。 需求爆发的背后有两重逻辑:一是光纤核心材料“预制棒”的扩产周期长、工艺要求高,供给存在刚性约束;二是AI芯片算力提升迫使数据通信从电转向光,以降低能耗并提高传输效率,这直接推动了高端特种光纤(如用于CPO共封装光学)的需求。AI数据中心的光纤用量可达传统机柜的5-10倍,并随GPU集群规模超比例增长。 在此背景下,康宁光通信业务收入从2023年的13亿美元快速增长,2026年Q1同比增长93%,并获得了Meta、英伟达等科技巨头的长期大额订单。虽然从全球市场份额看康宁并非最大,但其在超低损耗、高密度、高抗弯等AI所需的高端特种光纤技术上具备优势,且企业级(数据中心)客户收入占比已超40%,这使其区别于以电信运营商客户为主的其他厂商。 文章指出,光纤涨价红利正惠及全行业。康宁当前股价和估值已大幅攀升,未来表现将取决于CPO技术落地节奏、大客户订单执行情况以及“空芯光纤”等潜在技术变革的影响。尽管前景看好,但短期过快的涨幅也可能带来波动风险。

marsbit15 小時前

3年5倍,百年玻璃厂重生

marsbit15 小時前

交易

現貨
合約

熱門文章

什麼是 $BANK

銀行人工智能:銀行未來的革命性步伐 介紹 在這個科技迅速進步的時代,銀行人工智能處於人工智能(AI)和銀行服務的交匯點。這個創新的項目旨在重新定義金融格局,通過人工智能的力量提高運營效率、安全措施和客戶體驗。在我們探索銀行人工智能的過程中,將深入探討這一項目的內涵、運作動態、歷史背景以及重要里程碑。 銀行人工智能是什麼? 從本質上講,銀行人工智能代表了一項變革性倡議,旨在將人工智能整合進各種銀行運營中。這個項目利用人工智能的能力來自動化流程、改善風險管理協議,並通過個性化服務增強客戶互動。 銀行人工智能的主要目標包括: 銀行功能自動化:通過利用人工智能技術,銀行人工智能旨在自動化日常任務,減輕人力資源的負擔並提高效率。 加強風險管理:該項目利用人工智能算法來預測和識別風險,從而強化針對欺詐和其他威脅的安全措施。 銀行服務個性化:銀行人工智能專注於通過分析客戶數據和行為提供量身定制的金融產品和服務。 改善客戶體驗:實施由人工智能驅動的解決方案,如聊天機器人和虛擬助手,旨在為用戶提供更接近人類的互動,徹底改變客戶與銀行的互動方式。 有了這些目標,銀行人工智能將自己定位為在提高銀行效率、安全性和以用戶為中心的關鍵角色。 銀行人工智能的創造者是誰? 關於銀行人工智能的創造者的具體細節尚不清楚。因此,在可用信息中尚未確定具體的個人或組織。圍繞該項目創建的匿名性引發了問題,但並未減少其雄心壯志的願景和目標。 銀行人工智能的投資者是誰? 與項目的創造者類似,關於銀行人工智能的投資者或支持組織的具體信息尚未披露。沒有這些信息,很難概述可能推動該項目向前發展的財務支持和機構支持。儘管如此,擁有堅實的投資基礎對於在這樣一個創新領域中保持發展至關重要。 銀行人工智能是如何運作的? 銀行人工智能在幾個創新領域運作,專注於使其與傳統銀行框架區分開來的獨特因素。以下是主要的運作特點: 自動化:通過應用機器學習算法,銀行人工智能自動化銀行內的各種手動流程。這樣不僅減少了運營成本,還使人力工作者能夠將精力轉向更具戰略性的活動。 先進的風險管理:將人工智能整合到風險管理實踐中,使銀行獲得準確預測潛在威脅(如欺詐)的工具,確保客戶信息和資產的安全。 量身定制的財務建議:通過持續學習客戶互動,人工智能系統發展出對用戶需求的細緻理解,能夠對財務決策提供量身定制的建議。 增強的客戶互動:利用由人工智能驅動的聊天機器人和虛擬助手,銀行人工智能提供了更具吸引力的客戶體驗,使用戶能夠快速解決問題,從而減少等待時間並提高滿意度。 這些運作特徵使銀行人工智能成為銀行業的先驅,建立服務交付和運營卓越的新標準。 銀行人工智能的時間線 了解銀行人工智能的發展軌跡需要看其歷史背景。以下是突顯重要里程碑和發展的時間線: 2010年代早期:對人工智能整合到銀行服務的概念開始引起關注,隨著銀行機構認識到潛在利益。 2018年:隨著銀行開始使用聊天機器人等人工智能工具進行基本客戶服務和風險管理系統以改善安全處理,人工智能技術的實施顯著增加。 2023年:人工智能的技術不斷進步,生成式人工智能被引入進行更複雜的任務,如文件處理和實時投資分析。今年標誌著人工智能技術為銀行提供能力的重要飛躍。 2024-當前狀態:截至今年,銀行人工智能正處於上升軌道,持續的研究和開發預示著將進一步提升銀行業務的能力。對人工智能應用的持續探索暗示著未來令人興奮的發展。 銀行人工智能的關鍵點 人工智能在銀行中的整合:銀行人工智能專注於採用人工智能來簡化銀行流程並改善用戶體驗。 自動化和風險管理的聚焦:該項目強烈關注這些領域,旨在減輕例行任務的負擔,同時通過預測分析增強安全框架。 個性化的銀行解決方案:通過利用客戶數據,銀行人工智能提供滿足個別用戶需求的量身定制銀行服務。 對發展的承諾:銀行人工智能致力於持續的研究和開發,確保其隨著技術的持續演變而保持適應性和持續相關性。 結論 總結來說,銀行人工智能展現了銀行業的一個重要進步,利用人工智能重塑運營範式、提高安全性,並促進客戶滿意度。儘管有關創造者和投資者的信息仍有缺口,但銀行人工智能的明確目標和功能機制為其持續發展提供了堅實基礎。隨著人工智能技術的不斷進步和與銀行業的融合,銀行人工智能在金融服務未來的影響力將十分顯著,改善我們對銀行的理解和互動方式。

116 人學過發佈於 2024.04.06更新於 2024.12.03

什麼是 $BANK

如何購買BANK

歡迎來到HTX.com!在這裡,購買Lorenzo Protocol (BANK)變得簡單而便捷。跟隨我們的逐步指南,放心開始您的加密貨幣之旅。第一步:創建您的HTX帳戶使用您的 Email、手機號碼在HTX註冊一個免費帳戶。體驗無憂的註冊過程並解鎖所有平台功能。立即註冊第二步:前往買幣頁面,選擇您的支付方式信用卡/金融卡購買:使用您的Visa或Mastercard即時購買Lorenzo Protocol (BANK)。餘額購買:使用您HTX帳戶餘額中的資金進行無縫交易。第三方購買:探索諸如Google Pay或Apple Pay等流行支付方式以增加便利性。C2C購買:在HTX平台上直接與其他用戶交易。HTX 場外交易 (OTC) 購買:為大量交易者提供個性化服務和競爭性匯率。第三步:存儲您的Lorenzo Protocol (BANK)購買Lorenzo Protocol (BANK)後,將其存儲在您的HTX帳戶中。您也可以透過區塊鏈轉帳將其發送到其他地址或者用於交易其他加密貨幣。第四步:交易Lorenzo Protocol (BANK)在HTX的現貨市場輕鬆交易Lorenzo Protocol (BANK)。前往您的帳戶,選擇交易對,執行交易,並即時監控。HTX為初學者和經驗豐富的交易者提供了友好的用戶體驗。

951 人學過發佈於 2025.05.09更新於 2025.05.09

如何購買BANK

相關討論

歡迎來到 HTX 社群。在這裡,您可以了解最新的平台發展動態並獲得專業的市場意見。 以下是用戶對 BANK (BANK)幣價的意見。

活动图片