AnthropicAnnouncement
Agents for financial services
Summary
Anthropic is releasing ten ready-to-run agent templates for financial services, targeting work such as pitchbook creation, KYC screening, and month-end close operations. Each template packages task-specific skills, governed data connectors, and subagents, and is available as a plugin for Claude Cowork or Claude Code, or as a cookbook for Claude Managed Agents. Claude add-ins for Excel, PowerPoint, Word, and, soon, Outlook carry context between applications, while new connectors and a Moody’s MCP app provide access to market, research, credit, and company data. The announcement says the updates pair best with Claude Opus 4.7, which leads Vals AI’s Finance Agent benchmark at 64.37%, and states that templates are available today through the financial services marketplace.
Context
Financial services teams face time-consuming work including building pitchbooks, screening KYC files, and closing the books at month-end. The agents also address workflows requiring access to market, research, credit, and internal company data.
Approach / What changed
Ten reference architectures combine skills, governed connectors, and subagents. They can run as plugins in Claude Cowork or Claude Code, or as cookbooks for Claude Managed Agents, with Microsoft 365 add-ins carrying context across applications and new partner connectors and an MCP app extending data access.
Takeaways
Each finance template combines domain instructions and knowledge, governed data access, and subagents for specialized tasks such as comparables selection or methodology checks.
Claude Managed Agents cookbooks support long-running sessions, per-tool permissions, managed credential vaults, and an audit log of tool calls and decisions.
The release includes connectors from providers such as Dun & Bradstreet, FactSet, Guidepoint, IBISWorld, and Verisk, plus a Moody’s MCP app for proprietary credit ratings and company data.
Source and freshness
- Source
- anthropic.com
- Published
- Added to Yomu
Summaries are generated from the original by a language model. Check the original before relying on it.
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