摩根大通将 Claude Code 使用范围扩展至工程团队之外
JPMorganChase Broadens Claude Code Use Beyond Engineering Teams
Anthropic 于 2026 年 11 月 9 日宣布,摩根大通正把 Claude 推广到工程师以外的员工,覆盖产品开发、基础设施、风险评估以及资产与财富管理。Claude Code 运行在该行自有基础设施的容器化开发平台 Devspace 中,智能体不直接获取员工凭证或内部系统权限,访问权限分阶段放开,每个新 Claude 模型都需通过银行审批。所有变更需经过数千项自动化测试和强制流水线审批关卡,Claude 无法自行签核,生产变更仍由人负责。
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摩根大通把 Claude Code 从工程团队扩展到投行、资管与风控,并给出分阶段授权和人工审批的落地约束。
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Anthropic announced on November 9, 2026 that JPMorganChase is rolling out Claude to more employees beyond engineers, extending AI-assisted work into product development, infrastructure, risk assessments and asset and wealth management. The expansion pairs broader access with strict limits on what agents can reach and who can approve production changes.
At the center of the engineering expansion is Claude Code, Anthropic’s coding agent, which plans work, writes code, runs tests and opens pull requests. In the Corporate and Investment Bank, Anthropic says work is moving into production faster, with the resulting capacity redeployed against business priorities. Engineers are modernizing additional legacy systems and sharing their own agents, including tools for pull-request review and self-healing.
Work Beyond the Codebase
Infrastructure and operations teams use Claude Code for monitoring, alerting and root-cause analysis. Product teams are using Claude to turn requirements directly into engineering backlogs, while other teams apply Claude Code to risk-and-controls assessments and program planning. The expansion also reaches the work around coding: research, requirements, design and planning.
Investment Teams and Advisor Tools
In Asset & Wealth Management, JPMorganChase is placing employees with business insight alongside technology and product specialists in small, empowered teams. Claude Code is now part of their engineering workflow. Anthropic says this structure is helping the teams deliver customized client investment solutions at scale and move faster, while every change faces more rigorous testing before it reaches clients.
Separately, J.P. Morgan Asset Management announced a connector in October 2026 that brings 55ip’s ActiveTax Technology into Claude for Financial Advisors. It lets advisors evaluate the tax impact of moving a client’s holdings into a new portfolio. The advisor product combines connectors and workflow skills for research, preparation and documentation; investment recommendations, client communications, compliance determinations and other regulated activities remain subject to human review and approval.
Controls Decide What Reaches Production
Claude Code runs inside Devspace, JPMorganChase’s containerized development platform, on the firm’s own infrastructure rather than on developer desktops. Agents do not receive direct access to employee credentials or internal systems. Access widens in stages, and each new Claude model must pass the bank’s approval process before employees can use it.
Thousands of automated tests and approval gates check every change. An enforced pipeline gate returns a hard pass or halt, so Claude cannot sign off on its own work, and people remain accountable for every production change. That architecture keeps model output separate from production approval, even as Claude’s assigned work expands.
Security is another part of the deployment. Anthropic says JPMorganChase’s security team uses its frontier models to find and fix vulnerabilities faster, and points to Project Glasswing as the earlier description of that work. Announced on April 7, 2026, Glasswing included JPMorganChase among its launch partners, which were to use Claude Mythos Preview in defensive security work.
At the Glasswing launch, JPMorganChase Chief Information Security Officer Pat Opet described an early opportunity to assess next-generation AI tools for defensive cybersecurity across critical infrastructure. “We will take a rigorous, independent approach to determining how to proceed and where we can help,” he said.
Anthropic says JPMorganChase’s requirements are shaping what it builds for other regulated institutions. The bank’s rollout shows the practical meaning of that influence: AI is reaching more financial workflows, while staged access, model approvals and human accountability determine how far agents can go.