About StressGen
Stress scenarios rooted in context, not conjecture.
Why We Built StressGen
Financial institutions spend weeks building stress scenarios by hand — assembling spreadsheets, reading regulatory documents, and relying on institutional memory.
We built StressGen to close that gap: institutional-grade stress scenarios generated in minutes, anchored in six independent layers of context, with every number traceable to a source.
Our Approach — Context at Every Layer
Context is not a feature. It is the methodology. Every scenario passes through six independent layers before it reaches your desk.
Regulatory Context
RAG retrieval from 200+ pages of CCAR/DFAST supervisory guidance.
Market Context
Live data from FRED, Yahoo Finance, OpenBB, and 15+ sources.
Market Intelligence
News sentiment, social signals, prediction markets, and SEC filings.
Statistical Context
C-Vine copulas propagate shocks with computed, not assumed, correlations.
Historical Context
20 years of risk factor data for calibration against historical distributions.
Likelihood Intelligence
Quantitative scoring ranks each scenario against current market conditions.
What This Means in Practice
When you generate a scenario with StressGen, every shock is debated by AI economists, validated against regulatory guidance, propagated through statistical models, and scored against live market conditions. The result is not just a scenario — it is a defensible, auditable, context-rooted stress test with full provenance for regulatory examination.
Beyond Generation
Generating scenarios is step one. StressGen also lets you:
- •Analyze scenarios — ask questions about any scenario in natural language, grounded in the scenario data.
- •Query regulatory documents — search 200+ pages of CCAR/DFAST guidance directly from the platform.
- •Rank by likelihood — quantitative scoring compares each scenario against current market conditions to surface the most relevant ones.
Contact
Questions, feedback, or partnership inquiries? Reach out to contact@stressgen.ai.