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Kobalt Labs Selected by Bangor Savings Bank to Streamline BaaS Risk and Compliance Management

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Kobalt Labs Selected by Bangor Savings Bank to Streamline BaaS Risk and Compliance Management

Kobalt Labs, the AI-native risk and compliance platform for financial institutions, today announced that Bangor Savings Bank, Maine’s largest bank with more than $7 billion in assets, has selected Kobalt as the centralized platform to support fintech due diligence, ongoing partner oversight, and marketing compliance across its growing Banking-as-a-Service (BaaS) program.

As financial institutions expand Banking-as-a-Service offerings, managing fintech partner risk has become increasingly complex. Banks must evaluate large volumes of documentation, maintain ongoing oversight, and demonstrate clear auditability across partner relationships. Kobalt helps institutions streamline these processes while maintaining rigorous risk management standards.

Facing increased complexity across a growing network of fintech partnerships, Bangor Savings Bank sought a more centralized and scalable approach to due diligence, partner oversight, and compliance management.

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With Kobalt, Bangor Savings Bank can automate document analysis, generate evidence-backed risk assessments, and track review progress in real time. The platform also streamlines ongoing monitoring and partner collaboration, while maintaining source-linked documentation and audit trails to support regulatory oversight.

“Bangor Savings Bank is demonstrating how financial institutions can modernize their risk and compliance operations as their fintech programs evolve,” said Kalyani Ramadurgam, CEO of Kobalt Labs. “We’re proud to support their team with technology that makes rigorous oversight more efficient and scalable.”

The Bank’s decision followed a hands-on evaluation in which its compliance team tested Kobalt using actual fintech documentation. The evaluation demonstrated the platform’s ability to analyze complex materials, generate evidence-backed assessments, and provide traceability into the source documents supporting each finding.


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