“What makes this integration powerful is that Claude isn’t just being given more data; it’s being given the verified context and decision logic required to act,” said Alex Zuck, General Manager of Risk at Dun & Bradstreet. “That means outputs that are not only personalized to the user and situation, but also explainable, auditable, and consistent, all essential components for organizations to act with confidence in high stakes, regulated environments.”

This represents a fundamental shift in how onboarding gets done, enabling agentic systems to replace manual steps, siloed tools, and case management with one automated workflow. For example, a financial institution can use D&B data in Claude to onboard new corporate clients in seconds, automatically verifying who they are, how they’re owned, their risk profile, and generating audit ready documentation.

Together, Claude and D&B enable users to create onboarding agents that combine natural language instructions with verified data anchored in the global standard D-U-N-S^® Number business identifier and decision ready risk logic honed over years of real world client use.

“Agents in onboarding workflows must understand who they’re dealing with,” Zuck said. “D&B gives Claude a persistent, verified view of business identity through the D U N S Number, as well as the context required to reason about ownership, control, and risk. By bringing this business verification layer into Claude, we’re helping organizations move faster on onboarding without compromising safety, accountability, or trust.”

Through the MCP based integration, users can securely access D&B’s Commercial Graph to:

• Verify the identity of businesses they engage with across complex ownership and control structures.

• Evaluate exposure across global third party and supplier networks.

• Automate onboarding agents that incorporate real time risk intelligence into decision making processes.

• Automate the creation of risk decision documentation.

This approach represents the future of knowledge work for enterprises: AI systems that do not simply summarize information, but operate with verified enterprise context, risk logic, and governance.