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Narmi Launches Microsoft 365 Copilot Connector, Bringing Customer Financial Data Securely into Existing Banking Workflows

Microsoft

New AI capabilities simplify customer data analysis for banks and credit unions, streamlining relationship management, lending and daily operations

NEW YORK CITY, NY / October 26, 2026 / Narmi, a leading provider of digital banking solutions for financial institutions, today announced the expansion of its Model Context Protocol (MCP) capabilities to Microsoft 365 Copilot, bringing secure access to customer financial data directly into existing admin banking workflows. The integration enables bank and credit union staff to retrieve customer information, manage fraud inquiries, assess lending or liquidity activity and monitor financial transactions through natural language queries.

Building on the launch of Narmi's AI Marketplace, the integration further advances the company's efforts to bring practical AI into daily banking operations. Rather than manually compiling reports or navigating disparate banking systems, staff can now use Microsoft 365 Copilot to gain a more comprehensive view of customer financial activity, assess lending needs and uncover opportunities to strengthen existing relationships.

"AI is quickly becoming an essential part of how financial institutions operate, but its value depends on how easily employees can access and act on the information they need without compromising security or privacy," said Chris Griffin, Co-Founder of Narmi. "By extending our AI capabilities to the tools bankers already use every day, we're giving institutions a more intuitive way to identify growth opportunities and make informed decisions, all while maintaining the security and oversight that banking demands."

With Microsoft 365 already widely used across the banking industry, the expanded Copilot connector capabilities allow customer financial data to be integrated into familiar enterprise tools without introducing additional platforms or operational complexity. Through the enablement, banking staff can now use natural language queries to support a variety of back-office functions, including:

  • Relationship management: Review customer account activity, identify significant outflows to external institutions and uncover potential customer growth opportunities.

  • Lending and liquidity: Analyze customer cash flow, monitor line of credit utilization and assess lending applications to support more informed credit decisions.

  • Operations and risk: Review transaction histories, identify unusual payment activity and support fraud investigations.

  • Customer onboarding: Track account application statuses and review onboarding progress to streamline internal processes.

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