Snowflake Cortex AI: Enterprise-Ready AI for Financial Services

Snowflake has launched Cortex AI for Financial Services, a specialized suite of artificial intelligence tools designed to help financial institutions unify their data systems and deploy secure, compliant AI models, applications, and agents. This offering addresses the sector’s stringent regulatory and security demands while enabling faster insights and operational efficiency. The announcement also includes a new managed Model Context Protocol (MCP) Server, currently in public preview, which allows organizations to integrate proprietary and third-party data from partners such as FactSet, MSCI, Nasdaq eVestment, and The Associated Press. Through the MCP Server, customers can link their Snowflake data with leading AI agent platforms like Anthropic, CrewAI, Cursor, Devin by Cognition, Salesforce’s Agentforce, and Windsurf, building context-aware AI agents and applications tailored to specific business needs.

Baris Gultekin, Snowflake’s Vice President of AI, emphasized that financial services firms are often early technology adopters but face distinct hurdles like fragmented data, compliance complexity, and strict governance. By embedding AI directly within their existing data environment and supporting secure interoperability with remote agents, Snowflake helps these organizations accelerate critical workflows and tap into a unified ecosystem of data, AI, and applications.

Cortex AI for Financial Services introduces enterprise-ready agents that streamline complex financial operations such as market analysis, quantitative research, fraud detection, customer support, and claims management. These capabilities help reduce operational costs, save time, and generate faster insights. The MCP Server further enhances interoperability, securely connecting Snowflake data with third-party applications and data sources.

The ecosystem incorporates trusted data from top financial data providers and publishers. Companies can integrate structured data from CB Insights, Cotality, Deutsche Börse, MSCI, and Nasdaq eVestment via Sharing of Semantic Views, which will be generally available soon. Unstructured data from CB Insights, FactSet, Investopedia, The Associated Press, and The Washington Post is accessible through Cortex Knowledge Extensions, now generally available. By blending this industry-specific content, including market analysis, expert research, and news, with their own proprietary data in Snowflake, financial firms achieve deeper, more accurate AI-driven results.

Key features within the Cortex AI for Financial Services suite include:

Complex Machine Learning Workflows – Data scientists in finance frequently spend significant time on data preparation and repetitive coding for risk modeling, forecasting, trading analytics, and compliance. The Snowflake Data Science Agent automates data cleaning, feature engineering, model prototyping, and validation, helping teams transition from raw data to production-ready models more rapidly. This automation supports quantitative research, fraud detection, customer 360, and underwriting processes.

Analysis of Unstructured Data – Financial organizations manage vast amounts of unstructured information, including market research, earnings call transcripts, and transaction details, which traditionally require manual review or complex ETL processes. Snowflake Cortex AISQL introduces AI-powered extraction and transcription functions, enabling users to efficiently process documents, audio, and images at scale. This transforms workflows in customer service, investment analytics, claims management, and next-best-action recommendations.

Easy Access to Flexible Insights – While Data Science Agent and Cortex AISQL serve technical and research teams, Snowflake Intelligence (in public preview) provides business users with a conversational interface to query data using natural language. It draws from both Snowflake-stored data and third-party sources, apps, and agents, allowing non-technical staff to uncover actionable insights from structured tables and unstructured documents. This democratizes data access and accelerates business decision-making across the organization.

Beyond financial services, the Snowflake MCP Server extends connected, interoperable AI capabilities across all industries. AI agents enhance large language models by interacting with external tools, executing complex workflows, and understanding organizational context. However, integrating these agents with enterprise systems has historically required custom solutions, slowing AI adoption. The MCP standard offers a uniform method for LLMs to connect with data, APIs, and services. With Snowflake MCP Server, enterprises can:

Enable MCP Server to connect with tools built on Snowflake – The server links Cortex Analyst and Cortex Search to external AI agents via a standards-based MCP interface, unifying structured and unstructured data retrieval. This simplifies application architecture, removes the need for custom integrations, and speeds up the deployment of context-rich AI apps and agents.

Access proprietary and third-party data shared on Snowflake with external tools – Remote agents can now connect to Snowflake data and third-party data shares available through Snowflake Marketplace via Cortex Knowledge Extensions. This enables seamless interoperability across the broader AI ecosystem without compromising security or governance.

The MCP Server supports integration with a wide range of agentic applications and platforms, including Anthropic, Augment Code, Amazon Bedrock AgentCore, CrewAI, Cursor, Devin by Cognition, Glean, Kumo, Mistral, Salesforce’s Agentforce, UiPath, Windsurf, Workday, and WRITER.

(Source: ITWire Australia)