Dun & Bradstreet announced AI capabilities built on Gemini Enterprise to power complex credit and risk workflows. Enabled by Model Context Protocol (MCP) server integrations, this collaboration helps users build governed AI systems for faster onboarding, stronger risk decisions, and scalable lending workstreams.
AI is becoming an integral part of how financial institutions evaluate customers, extend credit, and manage risk, increasing the importance of the information that informs those decisions. But in a 2026 Dun & Bradstreet survey, only 8% of financial services and insurance organizations report that their enterprise data is fully ready to support AI at scale. The D&B Commercial Graph
supports the shift to more reliable AI workflows by providing the foundational context layer that allows agents to understand business identity, relationships, and risk across the global economy. The resulting outputs are consistent, explainable, and auditable.
“Banks have spent decades building digital infrastructure. The next competitive advantage is building an intelligence infrastructure for AI,” said Scott Spencer, General Manager of Finance & Credit at Dun & Bradstreet. “Our collaboration with Gemini Enterprise helps financial institutions apply AI to the business-critical decisions they make every day by grounding those decisions in verified business context.”
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“Financial institutions want to use AI for their most complex workflows, but they can’t compromise on trust and transparency,” said Satish Thomas, Vice President, Google Cloud.
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