Dun & Bradstreet launches agentic workflows on Databricks

Dun & Bradstreet has launched agentic credit and portfolio management workflows that run inside the Databricks platform. The tools use the D&B Commercial Graph, accessed through Databricks Marketplace and OpenSharing, and combine D&B’s verified business data with a customer’s own data to support credit origination, policy analysis and portfolio oversight.

The company says the workflows use agentic AI to automate tasks such as business verification, risk enrichment and case triage. In an anonymized portfolio example cited by Dun & Bradstreet, the workflows raised bad capture rate from 30% to about 38%, which the company reported as translating into more than $6 million in incremental bad debt avoided. Dun & Bradstreet also reports that processes that previously took analysts days or weeks can be completed in seconds within Databricks.

One workflow verifies businesses and enriches cases with commercial and risk data to recommend approve, decline or triage actions and to suggest credit limits and payment terms. A second workflow analyzes existing credit policy performance, identifies ways to increase predictive power and estimates the financial impact of potential policy changes. A third monitors portfolio risk to help finance teams spot deteriorating accounts earlier and surface risk and growth opportunities across customers, markets and geographies.

The Commercial Graph is anchored by the D-U-N-S Number identifier and provides a data layer that Dun & Bradstreet says gives AI agents a consistent, explainable and auditable context for reasoning about business identity, relationships and risk. Delivering the data inside Databricks via Marketplace and OpenSharing lets customers use D&B reference data in analytics, machine learning and AI-agent workflows without separate data pipelines or moving data off the platform.

Scott Spencer, General Manager for Finance and Credit at Dun & Bradstreet, stated: “Finance leaders are under pressure to move faster, support growth and manage risk with greater precision. By leveraging verified business information from D&B’s Commercial Graph in the Databricks environment, we’re helping businesses streamline credit origination, continuously improve policy decisions, and gain a clearer view of portfolio risk. With the help of agentic AI, tasks that would take analysts days or weeks are completed in seconds.”

Sarah Branfman, Global VP, ISV and Data Partner at Databricks, added: “CFOs and finance teams need more than experiments with AI, they need practical ways to improve decisions and manage risk. Making D&B data available through Databricks Marketplace and OpenSharing helps customers build connected credit and risk workflows that support faster, more informed action.”

Dun & Bradstreet positions the workflows as operational tools for credit teams to use continuously for policy tuning and ongoing portfolio surveillance rather than as one-off analytics experiments.