dv01 Launches Agentic Infrastructure for Structured Finance

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Jonathan Warrick, Head of dv01
Image Credit: Jonathan Warrick, Head of dv01
dv01, a leading capital markets fintech company driving technological innovation and loan-level transparency in structured finance, has unveiled its agentic infrastructure. The company launched AI agents for its DealStudio and Credit Facility Management offerings, along with Model Context Protocol (MCP) connectivity for collateral analysis and cashflow modeling. Together, these capabilities enable firms to leverage AI across ABS and RMBS workflows.

“The industry is approaching a fundamental shift in how work gets done, and AI cannot be treated as a feature. Agents need transparent loan-level data, reliable analytics, and fuller context of a transaction to connect insights that may be fragmented across teams and systems,” said Jonathan Warrick, Head of dv01. “We’ve spent more than a decade building that foundation and are adapting our infrastructure to support agent-driven workflows, so firms can move beyond automating tasks and expand what is possible across structured finance without lowering the standards for rigor, control, and accountability.”

Operationalizing AI with Built-In dv01 Agents and MCP

  • AI agents built into the dv01 platform: Provide source documents and instructions, then review, refine, and approve the work. The dv01 agents can turn an offering memorandum into a draft structure or use a credit agreement and loan data to configure a facility and draft borrowing base and monthly servicer reports.
  • MCP for client-built agents: Analyze collateral and run cashflow projections using dv01 data and analytical capabilities in a client’s own AI environment. Connect ChatGPT, Claude, or internal AI applications through the dv01 MCP server without building a separate custom integration.

The dv01 Semantic Layer: Grounding AI With Structured Finance Context

dv01’s Semantic Layer assigns consistent business meaning to standardized loan-level data by mapping source fields to defined concepts, establishing how metrics are calculated, and incorporating documented deal- and servicer-specific exceptions.

Through the dv01 MCP server, large language models (“LLMs”) call dv01 capabilities built on this foundation instead of interpreting raw data or recreate methodologies within the model. This gives those agents the structured finance context needed to return analysis grounded in dv01-defined data and methodologies.

Building Agentic Infrastructure for Structured Finance

AI has become a strategic priority across capital markets, but deployment remains uneven across firms and desks. As agents take on more of the preparation and execution, market participants will increasingly focus on defining objectives, directing workflows, reviewing evidence and exceptions, and applying judgment. This shift makes the infrastructure beneath the work even more important.

dv01 is the trusted partner providing the infrastructure to seamlessly integrate agents into established workflows, grounded in the data, calculations, domain context, and controls the market requires.

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