ActiveViam and Databricks Partner to Launch Real-Time Risk Analytics for Capital Markets

ActiveViam and Databricks have integrated their platforms to provide financial institutions with validated, real-time risk analytics for AI agents. This collaboration allows capital markets firms to deploy agentic AI workflows that use trusted risk calculations directly within their existing data governance frameworks, bridging the gap between experimental AI and production-ready risk management.

What was announced

ActiveViam has launched a new integration with the Databricks Data + AI Platform, introducing Atoti Intelligence to the Databricks ecosystem. This agentic AI architecture allows financial institutions to build AI agents that can call deterministic risk tools directly. Rather than requiring agents to generate SQL or code against raw data tables—a process prone to errors—the system provides direct access to validated calculations for Value at Risk (VaR), Expected Shortfall (ES), Fundamental Review of the Trading Book (FRTB), valuation adjustments (xVA), and liquidity ratios such as LCR and NSFR.

The integration is designed to maintain strict data sovereignty and security. Each calculation is executed within the customer’s own Databricks environment, adhering to established governance, lineage, and access controls. Because the system utilizes the customer’s approved Large Language Model (LLM), proprietary data and intellectual property remain on the platform. This builds upon ActiveViam’s existing DirectQuery support, which provides a live connection to query governed Databricks data. For existing ActiveViam users, the collaboration allows for consolidation onto Databricks without the need to rebuild risk measures or hierarchies, while Databricks customers gain access to specialized capital-markets risk analytics without developing them in-house.

"Databricks gives banks one governed home for their data, while Atoti turns it into risk intelligence they can trust and sign off on, without copying data out. The result is the same number every time, traceable to the trade and precise enough to sign off. Everything runs inside the firm’s own environment and under its existing Databricks governance, so its data and IP never leave. We’re proud of this integration with the Databricks Data + AI Platform and look forward to seeing our clients take full advantage of this new capability."

Alan Lee, Chief Product Officer at ActiveViam

The companies involved

ActiveViam is a global provider of enterprise risk intelligence, specializing in the capital markets sector. The company's technology is designed to handle the massive data volumes and complex calculations required for real-time risk management and regulatory compliance. By providing a platform that can aggregate data from disparate sources and perform high-speed analytics, ActiveViam has established itself as a critical infrastructure provider for banks, hedge funds, and other financial institutions that require immediate insights into their market and liquidity exposure.

Databricks is a major player in the data and AI space, known for its "lakehouse" architecture that combines the best elements of data lakes and data warehouses. The company provides a unified platform for data engineering, data science, and machine learning, enabling organizations to manage their data and AI assets in a single, governed environment. With a strong presence in the financial services industry, Databricks has focused on helping firms modernize their data stacks to support advanced analytics and the deployment of generative AI at scale. The platform's open architecture is a key differentiator, allowing for broad integration with specialized industry tools like those provided by ActiveViam.

What FF News has reported before

FF News has closely followed the expansion of the Databricks ecosystem as it seeks to scale enterprise AI capabilities. Recently, the publication covered how Wipro and Databricks Launch Dedicated Business Practice to Scale Enterprise AI, highlighting the growing demand for specialized consulting and implementation services around the Databricks platform. This move aligns with a broader trend of financial institutions seeking to move away from legacy systems, as seen when Nationwide Modernizes Core Banking for 15M Customers with Microsoft AI. Other recent developments in the AI and capital markets space include the launch of an AI-Powered Open Underwriting Stack for Insurance Carriers by Appian and Synechron, and Clear Street Launches Private Markets Platform for Pre-IPO Access and Credit Financing, reflecting a wider industry push toward automated, data-driven decision-making.

What this means

This integration addresses one of the most significant hurdles in financial AI: the "hallucination" risk of Large Language Models when dealing with complex mathematical calculations. By allowing AI agents to call deterministic, pre-validated risk tools rather than asking them to write their own code, ActiveViam and Databricks are providing a blueprint for "agentic" workflows that regulators might actually approve. This puts pressure on traditional risk software vendors who rely on siloed data models. The move suggests the industry is shifting toward a model where specialized analytics live on top of a unified data lakehouse, rather than requiring data to be moved to a separate risk engine.