Dun & Bradstreet Adds Agentic AI to Compliance Workflows

Dun & Bradstreet

Data and analytics company Dun & Bradstreet has introduced new agentic AI capabilities for compliance workflows.

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    The new offering is designed to “reduce processing times by 70-90% and transform risk mitigation into a business enabler,” D&B) said in a Monday (June 22) news release.

    Available within the D&B Risk Analytics platform and “fully agentically” thanks to its model context protocol (MCP) server, this offering lets organizations embed verified D&B data, models and workflows into artificial intelligence (AI) assistants and custom agents, speeding onboarding, screening and due diligence, the release added.

    “As the pace and complexity of regulations accelerate and bad actors find new ways to exploit businesses, compliance teams are at a breaking point,” said Alex Zuck, general manager of risk at Dun & Bradstreet.

    “The typical approach of throwing investment into fragmented software, data and services isn’t sufficient, especially as the talent and roles needed to fight back have never been harder to keep or to hire. While AI has been offered as the silver bullet, companies have struggled to implement the data they need to fuel it. That changes today.”

    According to the release, the platform is designed to help companies continuously monitor know your customer/know your business (KYC/KYB) compliance and make quicker decisions using verified business data from the D&B Commercial Graph.

    “Traditional KYB onboarding takes days and sometimes weeks. Even tasks like determining the ultimate beneficial owner of a company require searching registries, validating documents and piecing ownership together manually,” Zuck added.

    “D&B can now complete that process and more in seconds, delivering all of it into clients’ onboarding workflows without human intervention.”

    PYMNTS looked at the role AI plays in compliance in a recent interview with Baran Ozkan, co-founder and CEO at Flagright.

    “The bigger value for AI is on the investigation side,” Ozkan said. “Detection doesn’t resolve the operational burden that follows.”

    Even as detection systems evolve, banks, FinTechs and crypto firms still face overwhelming alert volumes, leading compliance teams to absorb increasing downstream costs. Even false positives can drive up operational expenses, because investigators must still prove that no meaningful risks are present.

    “Every single false positive has a cost associated to it because someone actually has to work on it,” Ozkan said. “They have to investigate, make sure it’s not a true positive, there is no real risk and dispose it. But that all takes time. And time means money.”