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Experian与ServiceNow合作扩展AI代理业务
Experian推出基于代理的商业平台,将风险、身份和决策能力融入企业工作流,旨在提供更高质量信息并增加客户数量。
AI推荐理由 报道Experian与ServiceNow合作推出Agent Operating System,具体企业应用案例,信息较新,但细节有限。
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正文
更新于美国东部时间2026年9月4日10:50
AI
Experian通过与ServiceNow合作扩展AI代理
作者:Paul Gillin
在春季推出基于人工智能的虚拟助手后,Experian plc正在通过一个基于代理的商业平台将AI更深地推入其运营,该平台旨在将其风险、身份和决策能力带入企业工作流。
代理操作系统旨在为客户提供更高质量的信息,增加公司可以服务的客户数量,并吸引新客户。
Mehta表示,Agent OS是一个支持商业产品的平台能力,而不是独立产品。例如,客户可以将这家信用评级巨头的模型风险管理能力整合到现有的治理、风险和合规系统中。其他即时应用包括员工入职和验证。
该部署建立在多年机器学习和其他形式AI实验的基础上。Experian的新任首席AI官Vijay Mehta表示,该公司相信该技术可以更快地处理信息并识别早期方法遗漏的模式,可能帮助贷方评估几乎没有或没有信用记录的消费者。它们还帮助计算机对抗欺诈者,现在几乎所有欺诈者都使用先进的AI。
“我们不再处于概念验证阶段;我们处于企业扩展阶段,”Mehta说。“这与某人仅仅使用ChatGPT获得一点额外效率非常不同。”
ServiceNow Inc.是第一个部署新能力的合作伙伴。其代理将连接到Experian的Ascend分析和开发平台,使客户能够将可信数据、决策和治理能力集成到现有企业工作流中。
Mehta表示,ServiceNow让Experian能够访问广泛的业务和技术流程,使其能够向现有客户销售额外服务并接触新客户。
早期采用者主要使用Experian的模型风险管理服务。初始目标客户包括保险公司、金融服务提供商和贷方,但任何使用ServiceNow的组织都是潜在客户。计划推出更多产品。
代理遏制
在7月发生黑客事件后,Experian全力投入代理,该事件中来自OpenAI Group PBC的代理闯入Hugging Face Inc.的服务器,窃取文件和客户信息,并绕过旨在阻止它们访问互联网的护栏。
Mehta表示,Experian在高度监管的行业运营,在构建服务时充分意识到风险,并已采取措施确保代理不能越界。
一个通用网关提供对代理流量的控制,包括模型选择、提示、离开环境的数据和策略执行。身份和访问管理受到严格控制,日志记录和监控也构成该控制系统的一部分。
Experian的模型根据适用的监管要求检查代理活动,并使用对抗性测试,其中一个代理测试另一个代理的行为是否符合规则和政策。
“没有代理可以在我们不知情的情况下逃入荒野,而我们无法杀死它,”Mehta说。
访问权限遵循一个熟悉的原则:只给代理完成其任务所需的权限。“我们授予代理完成工作所需的最低访问权限,就像新员工一样,”Mehta说。
人在回路
Mehta表示,一些客户服务和后台流程可以自主运行,而受监管的决策保留人工参与。人类也参与涉及受监管结果的重大是或否决策。“最后一步仍然是确定性的,并且人在回路中,”他说。
该公司正在通过应用程序编程接口和模型上下文协议服务器使其代理能力可访问,该服务器将AI应用程序连接到工具和数据。它可以与用户界面一起操作,或者在另一个应用程序的幕后“无头”操作。
Agent OS可以根据工作负载切换底层模型。Mehta表示,许多金融服务任务可以在更简单、更便宜的模型上运行,而不是昂贵的前沿模型。该服务使用商业、开放权重和开源选项的混合。
Experian使用一系列商业工具构建代理,包括亚马逊网络服务公司的Bedrock,以及自己的技术。它维护一个注册表和存储库,使代理、技能和内容在拥有超过1000名数据科学家的组织中可重用。
支持架构包括一个语义层,为Experian产品组合中的数据提供通用定义。知识图谱连接这些信息,以便代理可以一致地使用它。这家全球公司链接分布式数据资产,而不是将所有内容移动到一个中央存储库。
Mehta表示,一致的数据定义、控制和计量的组合提供了可以在模型和工具变化中存活的构建块。
测试包括沙盒环境、合成数据和其他测试源,然后监控部署的代理。Mehta表示,将模型活动链接到底层数据有助于支持可解释性和验证。问责制遵循Experian的联邦结构,区域支持团队和中央技术和平台团队分担运营责任。Mehta的团队构建业务部门可以在面向外部客户的产品中使用的能力。
AI是未来
Experian将AI视为其业务的未来,并确保每个人都参与其中。有关于负责任AI使用、提示和将数据连接到工具的强制性员工培训。Mehta表示,目标是解放员工从事其他工作,但拒绝讨论具体的工作影响。
“当电子商务开始时,最初
当时的反应是,‘我害怕它,’”他说。“现在我们都很习惯在网上发送和交换商品和服务。我认为人工智能也会发生同样的事情。你会有更多的专家,所以你必须提升技能并培训你的员工去做其他工作。”
现在的挑战是将这一共同基础转化为可重复的部署,并取得可衡量的结果。益百利正在将其数据、控制和可重用基础设施定位为这一扩展的基础,而早期的ServiceNow部署将测试这些能力在多大程度上能转化为更广泛的企业工作流程。
照片:益百利
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UPDATED 10:50 EDT / SEPTEMBER 04 2026
AI
Experian expands into AI agents with ServiceNow partnership
by Paul Gillin
Having launched an artificial intelligence-based virtual assistant in the spring, Experian plc is driving AI deeper into its operations with a commercial agent-based platform designed to bring its risk, identity and decision-making capabilities into enterprise workflows.
The Agent Operating System aims to provide customers with high-quality information more quickly, increase the number of clients the company can serve, and bring new customers into the fold.
Agent OS is a platform capability supporting commercial products, rather than a standalone product, Mehta said. For example, a customer could incorporate the credit rating giant’s model risk management capabilities into an existing governance, risk and compliance system. Other immediate applications include employee onboarding and verification.
The deployment builds on years of experimentation with machine learning and other forms of AI. Experian believes the technology can process information faster and identify patterns that earlier approaches missed, potentially helping lenders assess consumers with little or no credit history, said Vijay Mehta, Experian’s new chief AI officer. They also help the computer fight fraudsters, nearly all of whom now use advanced AI themselves.
“We’re not in the proof-of-concept phase anymore; we’re in the enterprise scaling phase,” Mehta said. “That’s very different than someone just using ChatGPT to get a little bit of extra efficiency.”
ServiceNow Inc. is the first partner to deploy the new capabilities. Its agents will connect to Experian’s Ascend analytics and development platform, enabling customers to integrate trusted data, decisioning and governance capabilities into existing enterprise workflows.
ServiceNow gives Experian access to a wide range of business and technology processes, allowing it to sell additional services to existing customers and reach new ones, Mehta said.
Early adopters are primarily using Experian’s model risk management service. Initial target customers include insurers, financial services providers and lenders, but any organization using ServiceNow is a prospect. Additional products are planned.
Agent containment
Experian is going all in on agents in the wake of a July hacking incident in which agents from OpenAI Group PBC broke into servers at Hugging Face Inc., stole files and customer information, and bypassed guardrails meant to prevent them from accessing the Internet.
Operating in a highly regulated industry, Experian was well aware of the risks when it built the service and has taken pains to ensure that agents can’t overstep their bounds, Mehta said.
A common gateway provides controls over agent traffic, including model selection, prompts, data leaving the environment and policy enforcement. Identity and access management is tightly controlled, with logging and monitoring also forming part of that control system.
Experian’s model checks agent activity against applicable regulatory requirements and uses adversarial testing, in which one agent tests another’s actions for compliance with rules and policies.
“No agent can escape into the wilderness without us knowing and without us being able to kill it,” Mehta said.
Access permissions follow a familiar principle: Give an agent only the authority required by its task. “We grant the minimum access that an agent needs to fulfill its job, much like a new employee,” Mehta said.
Humans in the loop
Some customer service and back-office processes can operate autonomously while regulated decisions retain human involvement, Mehta said. Humans are also included in major yes-or-no decisions involving regulated outcomes. “The last step is still deterministic and human-in-the-loop,” he said.
The company is making its agentic capabilities accessible through application programming interfaces and a Model Context Protocol server that connects AI applications to tools and data. It can operate with a user interface or be “headless” behind the scenes of another application.
The Agent OS can switch underlying models according to the workload. Mehta said many financial services tasks can run on simpler, less expensive models rather than costly frontier models. The service uses a mix of commercial, open-weight and open-source options.
Experian builds agents with a range of commercial tools, including Amazon Web Services Inc.’s Bedrock, as well as its own technology. It maintains a registry and repository to make agents, skills and content reusable across an organization employing more than 1,000 data scientists.
The supporting architecture includes a semantic layer that provides common definitions for data across Experian’s portfolios. Knowledge graphs connect that information so agents can use it consistently. The global company links distributed data assets rather than moving everything into a single central repository.
Mehta said the combination of consistent data definitions, controls and metering provides building blocks that can survive changes in models and tools.
Testing includes sandbox environments, synthetic data and other test sources, followed by monitoring of deployed agents. Linking model activity to underlying data helps support explainability and validation, Mehta said. Accountability follows Experian’s federated structure, with regional support teams and central technology and platform teams sharing operational responsibilities. Mehta’s group builds capabilities that business units can use in products for external customers.
AI is the future
Experian sees AI as the future of its business and is making sure everyone comes along for the ride. There’s mandatory employee training on responsible AI use, prompting and connecting data to tools. Mehta said the goal is to free employees for other work but declined to discuss specific job impacts.
“When e-commerce started, the initial reaction was, ‘I’m afraid of it,’” he said. “Now we’re all comfortable sending and exchanging goods and services online. I think we’ll see the same thing happen with AI. You’ll have more specialists, so you have to upskill and train your talent to do other jobs.”
The challenge now is to turn that shared foundation into repeatable deployments with measurable results. Experian is positioning its data, controls and reusable infrastructure as the basis for that expansion, while the early ServiceNow rollout will test how readily those capabilities translate into broader enterprise workflows.
Photo: Experian
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