Nvidia Blog 05月15日 06:00
Visa Makes Payments Personalized and Secure With AI
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Visa正在利用人工智能技术增强其全球客户网络的服务,重点关注欺诈预防、个性化和代理商务。Visa每年处理数千亿笔交易,即使是微小的技术改进也能产生巨大的影响。该公司每年防止400亿美元的欺诈。人工智能还为Visa的个性化系统提供支持,为持卡人提供更智能、更相关的优惠和推荐。Visa也在努力实现代理商务,即人工智能代理帮助客户进行支付,例如,人工智能代理可以访问支付凭证,在接到指示时代表消费者处理交易,例如预订旅行安排。

🛡️ Visa利用AI预防欺诈,每年防止高达400亿美元的损失,即使是小幅改进也能节省大量资金。

🛍️ AI驱动Visa的个性化系统,为持卡人提供更智能、更相关的优惠和推荐,通过构建用户抽象表示来保护隐私。

🤖 Visa正在探索代理商务,AI代理可以代表客户处理支付事务,如预订旅行,从而简化支付流程。

⚙️ Visa分享了企业采用生成式AI的最佳实践,包括尽可能使用开源模型,并建立强大的治理和技术团队之间的关系。例如,Visa使用GPT-4将遗留代码转换为Python,节省了500万美元。

🔑 Sarah Laszlo建议企业采用生成式AI时,应尽可能使用开源模型,并发展强大的治理和技术团队关系。

Think tap to pay — but smarter and safer. Visa is tapping into AI to enhance services for its global network of customers, focused on fraud prevention, personalization and agentic commerce.

Sarah Laszlo, senior director of Visa’s machine learning platform, joined the AI Podcast to discuss how artificial intelligence is powering the next generation of payment experiences.

Visa processes hundreds of billions of transactions each year, so even small technological enhancements can have a large impact.

The company prevents $40 billion in fraud annually. “There’s so much attempted fraud that, even though we’re very good at preventing it, marginal improvements save large dollar amounts,” Laszlo said.

AI also powers Visa’s personalization systems, delivering smarter, more relevant offers and recommendations to cardholders. The company’s unique dataset presents a huge opportunity to improve transaction predictions — but also brings privacy challenges.

“The key to addressing those challenges is building abstract representations of users — embeddings that capture preferences without exposing private data,” Laszlo said.

The company is also working toward agentic commerce — where AI agents help customers with payments. For example, AI agents with access to payment credentials can handle transactions on behalf of consumers, like booking travel arrangements, when instructed.

Laszlo shared best practices for enterprises adopting generative AI. She also recommended using open-source models when possible and developing strong relationships between governance and technical teams. In one success story, Visa used GPT-4 to convert legacy code to Python, saving $5 million, with just one engineer completing 50 conversion jobs in a quarter.

To learn more, watch Laszlo’s GTC session, The Next Era of Payments: How Generative AI is Shaping the Future.

Time Stamps

03:28 – Visa’s priorities for AI use.

07:09 – How Visa optimizes resources using virtual GPUs.

14:42 – AI factories and unified pipelines.

18:52 – Best practices for AI in financial services.

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Visa 人工智能 支付 AI欺诈预防 代理商务
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