Nvidia Blog 04月25日 00:02
Capital One Banks on AI for Financial Services
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在NVIDIA AI播客中,Capital One的执行副总裁兼首席科学家Prem Natarajan分享了该公司如何利用生成式AI和智能体系统重塑金融服务业。Capital One采用“测试、迭代、完善”的方法,构建专有AI技术,以服务超过1亿客户。其AI策略强调利用专有数据构建差异化服务,并结合开放权重基础模型与深度定制,以支持金融服务任务的专业化模型。Natarajan还强调了负责任的AI设计,实施严格的安全措施。Capital One的云原生技术栈与AI工厂的概念相契合,通过整合硬件、软件和开发工具,实现数据转化为可操作的智能。

🏦Capital One 采取“测试、迭代、完善”的方法,平衡创新与严格的风险管理,构建专有AI系统为超过1亿客户提供服务。

💡Capital One 并非简单集成第三方解决方案,而是利用其庞大的数据存储库构建专有AI技术。Natarajan强调,数据优势即AI优势,专有数据能构建差异化服务。

🛠️Capital One 的AI架构结合了开放权重基础模型与深度定制,支持创建擅长金融服务任务的专业化模型,并集成到可以采取行动的多智能体工作流程中。

🛡️负责任的AI是Capital One设计流程的基础。团队采用“通过设计实现责任”的方法,实施强大的安全措施,确保安全部署。

🏭Capital One 的云原生技术栈与AI工厂的概念相契合。AI工厂整合了金融机构生成智能所需的全部组件,包括硬件、软件、网络和开发工具,用于金融服务中的AI应用。

Financial services has long been at the forefront of adopting technological innovations. Today, generative AI and agentic systems are redefining the industry, from customer interactions to enterprise operations.

Prem Natarajan, executive vice president, chief scientist and head of AI at Capital One, joined the NVIDIA AI Podcast to discuss how his organization is building proprietary AI systems that deliver value to over 100 million customers.

“AI is at its best when it transfers cognitive burden from the human to the system,” Natarajan said. “It allows the human to have that much more fun and experience that magic.”

Capital One’s strategy centers on a “test, iterate, refine” approach that balances innovation with rigorous risk management. The company’s first agentic AI deployment is a chat concierge that helps customers navigate the car-buying process, such as by scheduling test drives.

Rather than simply integrating third-party solutions, Capital One builds proprietary AI technologies that tap into its vast data repositories.

“Your data advantage is your AI advantage,” Natarajan emphasized. “Proprietary data allows you to build proprietary AI that provides enduring differentiated services for your customers.”

Capital One’s AI architecture combines open-weight foundation models with deep customizations using proprietary data. This approach, Natarajan explained, supports the creation of specialized models that excel at financial services tasks and integrate into multi-agent workflows that can take actions.

Natarajan stressed that responsible AI is fundamental to Capital One’s design process. His teams take a “responsibility through design” approach, implementing robust guardrails — both technological and human-in-the-loop — to ensure safe deployment.

The concept of an AI factory — where raw data is processed and refined to produce actionable intelligence — aligns naturally with Capital One’s cloud-native technology stack. AI factories incorporate all the components required for financial institutions to generate intelligence, combining hardware, software, networking and development tools for AI applications in financial services.

Time Stamps

1:10 – Natarajan’s background and journey to Capital One.

4:50 – Capital One’s approach to generative AI and agentic systems.

15:56 – Challenges in implementing responsible AI in financial services.

28:46 – AI factories and Capital One’s cloud-native advantage.

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Capital One AI 金融服务 专有数据
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