RiskSpan Launches Agentic AI for MBS Data — Instant, Transparent Insights for Agency MBS Professionals
RiskSpan, a leading provider of data analytics solutions for the structured finance industry, announced the release of Agentic AI for MBS Data, an AI-powered MBS analyst that delivers instant, sourced, and context-rich analysis in plain English — no coding required.
Solving the MBS Data Bottleneck
While Agency MBS loan data is readily available, meaningful insights for many users often remain locked behind complex SQL or Python queries. This creates a barrier for traders, portfolio managers, and risk teams who need answers quickly to avoid missing opportunities.
“Our clients told us they needed faster, clearer access to this data,” said Suhrud Dagli, RiskSpan’s Co-Founder and Chief Innovation Officer. “Agentic AI removes the technical barrier and delivers the kind of immediate, transparent insight that our clients have come to demand.”
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A 24/7 AI-Powered MBS Analyst
With Agentic AI for MBS Data, users simply ask a question in plain English — such as “Which Ginnie Mae 2020 production pools had the fastest speeds in Q2?” — and get back clear, visualized, and fully-cited answers in seconds. Ask Complex Questions, Get Instant Answers – No SQL or Python required.
Key benefits include:
- Full Transparency – All sources cited for confidence and compliance.
- Deeper Insights – Surfaces patterns and drivers you might not think to look for.
- Narrative-Ready Reporting – Polished summaries and visuals for executives and clients.
- Efficiency – Eliminates dependence on technical teams for everyday queries.
Designed for How MBS Professionals Think
From spotting prepayment anomalies to explaining performance shifts, Agentic AI identifies not just the what but the why. It transforms hours of manual analysis into seconds of actionable insight, enabling faster, more informed decision-making.
Agentic AI for MBS Data is available now. RiskSpan is offering live demos to showcase how the platform transforms the way MBS data is interrogated and reported.
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