Dun & Bradstreet announced the availability of agentic credit and portfolio management workflows through the Databricks Marketplace and Databricks OpenSharing, according to a company press release dated July 6, 2026.

The workflows are built on the D&B Commercial Graph, which uses the D-U-N-S Number as a business identifier to provide data on business identity, relationships, and risk. The tools are designed to assist finance teams with credit origination, credit policy optimization, and portfolio risk monitoring.

In one anonymized portfolio example cited by the company, the workflows improved bad debt capture rate from 30% to approximately 38%, which the company said translated to more than $6 million in incremental bad debt avoided.

The three workflows offered include a credit origination tool that verifies businesses and suggests credit limits and payment terms; a credit policy optimization tool that uses an AI agent to assess policy performance; and a portfolio risk monitoring tool that identifies deteriorating accounts and exposure across customer segments.

"Finance leaders are under pressure to move faster, support growth and manage risk with greater precision," said Scott Spencer, General Manager for Finance and Credit at Dun & Bradstreet. "With the help of agentic AI, tasks that would take analysts days or weeks are completed in seconds."

Sarah Branfman, Global VP of ISV and Data Partners at Databricks, said the integration allows customers to combine their own data with Dun & Bradstreet's commercial data natively within the Databricks platform.