Snowflake Launches Cortex AI for Financial Services with MCP Server Public Preview, Security and Compliance Controls

Snowflake Launches Cortex AI for Financial Services with Secure AI Capabilities

Snowflake has introduced Cortex AI for Financial Services-a suite of AI capabilities and partnerships built to help financial institutions unify data and deploy AI models, applications, and agents with security and compliance controls suited for regulated environments.

The release focuses on making trusted data usable for AI while maintaining governance. For finance teams, this means faster AI delivery without compromising on control, auditability, or risk standards.

Key components

• Model Context Protocol (MCP) Server - public preview: A managed server that lets organizations safely use proprietary data alongside third-party datasets from Snowflake partners.
• Agent and app connectivity: Teams can connect the MCP Server to various applications and agent platforms to build context-rich AI agents and apps that work across their data and AI stack.
• Security and compliance: Controls aligned to regulated industries to help satisfy governance, risk, and audit requirements.
• Data ecosystem: Access to high-quality, trusted datasets from leading financial data providers and publishers.

Why this matters for finance leaders

• Risk and compliance: Build AI workflows that respect data boundaries and audit needs across KYC, AML, surveillance, reporting, and model governance.
• Productivity: Enable AI agents to pull context from market data, risk systems, and client records without manual stitching.
• Speed-to-value: Use a managed MCP Server to reduce integration overhead and shorten time from pilot to production.

Practical next steps

• Identify 1-2 high-value pilot domains (e.g., client reporting, risk summaries, compliance case triage) where AI agents add measurable output and can cite sources.
• Stand up a governed data slice for the pilot: classify data, set PII boundaries, define access policies, and map required logs for audit.
• Connect MCP Server to a limited set of internal and partner datasets; validate latency, relevance, and cost profiles.
• Run legal, compliance, and model risk reviews early-document data lineage, retention, approval workflows, and human-in-the-loop checkpoints.

Where to learn more

For official product details and ecosystem partners, visit Snowflake.

If you're planning a pilot and want a market scan of practical tools, see AI tools for finance.