Elevate Your Risk Management
Stress Scenarios Rooted in Context, Not Conjecture
Every scenario passes through six layers of context — regulatory guidance, live market data, market intelligence, statistical validation, historical precedent, and likelihood intelligence — before it reaches your desk.
Every Scenario, Six Layers of Context
Context is not a feature. It is the methodology. Every scenario passes through six independent layers before it reaches your desk.
Regulatory Context
Scenarios are anchored in DFAST, CCAR, EBA, and PRA supervisory guidance. RAG retrieval extracts shock parameters directly from regulatory PDFs — not from training data.
Market Context
Live data from FRED, Yahoo Finance, OpenBB, and 15+ sources flows into every scenario. Credit spreads, yield curves, equity indices, and commodities provide the current baseline.
Market Intelligence
News sentiment, social signals, prediction markets, and SEC filings add forward-looking intelligence. The scenario is shaped not just by where markets are, but where they are heading.
Statistical Context
C-Vine copulas propagate primary shocks into secondary effects with statistical coherence. Every correlation is computed, not assumed. Every pathway is traceable.
Historical Context
20 years of risk factor data for calibration against historical distributions. Every shock is benchmarked against real precedent.
Likelihood Intelligence
Quantitative scoring compares each scenario against current market conditions across four signal dimensions. The result: a 0-100 likelihood score with confidence bands.
See the Output
Context-rooted scenarios with full shock tables, narrative documentation, and audit trail.
Fed Severely Adverse 2025
Severe global recession with sharp equity declines, rising unemployment, and flight to quality in US Treasuries.
SHOCK_TABLE
| FACTOR | CLASS | TYPE | MAGNITUDE |
|---|---|---|---|
| SP500 | Equity | PRIMARY | -40.00% |
| US_TREASURY_10Y | Rates | PRIMARY | -175.0 bps |
| EUR_USD | FX | PRIMARY | -12.50% |
| WTI_CRUDE | Commodities | PRIMARY | -55.00% |
| FED_FUNDS | Rates | PRIMARY | -350.0 bps |
| VIX | Volatility | SECONDARY | +250.00% |
| CDX_IG | Credit | SECONDARY | +225.0 bps |
| UNEMPLOYMENT | Macro | SECONDARY | +4.00% |
| GDP_GROWTH | Macro | SECONDARY | -6.50% |
| CPI | Macro | SECONDARY | +1.50% |
How Context Flows Through the Pipeline
Five stages, each adding a layer of context. From regulatory grounding to likelihood scoring, every stage enriches the scenario with verified, traceable intelligence.
RAG Analysis
Regulatory context extracted from your uploaded documents.
Economist Debate
Three AI economists debate primary shocks grounded in market context.
Copula Propagation
Statistical context via C-Vine copulas computes secondary shocks.
Output Generation
Validated shock tables with full provenance and audit trail.
Likelihood Ranking
Live market context scores each scenario for current-conditions alignment.
RAG Analysis
Regulatory context extracted from your uploaded documents.
Economist Debate
Three AI economists debate primary shocks grounded in market context.
Copula Propagation
Statistical context via C-Vine copulas computes secondary shocks.
Output Generation
Validated shock tables with full provenance and audit trail.
Likelihood Ranking
Live market context scores each scenario for current-conditions alignment.
Beyond Generation: Analyze, Query, Understand
Generating scenarios is step one. StressGen also lets you interrogate them, query the regulatory sources behind them, and understand how they relate to current market conditions.
Scenario Analysis
Ask questions about any generated scenario in natural language. Why was this shock chosen? How does it compare to 2008? What happens if the Fed cuts rates instead? The AI answers grounded in the scenario data, not general knowledge.
Regulatory Document Querying
Query your uploaded regulatory documents directly. Extract shock parameters, severity benchmarks, and scenario design constraints from primary regulatory sources — not from LLM training data.
Market Conditions Analysis
Understand what current market conditions mean for your scenarios. Live data from 15+ sources is synthesized into actionable intelligence: which scenarios are most likely, which signals are flashing, and what to watch next.
Market Context: 12+ Sources, One Coherent Signal
Real-time macro indicators, news sentiment, market data, and prediction markets — all feeding into every scenario as live context.
FRED
ECB
Federal Reserve
Tavily
Yahoo Finance
Kalshi
Polymarket
ChromaDB RAG
Twitter / X
Coming soonBloomberg
Coming soonReuters
Coming soonRegulatory Context: Built on Primary Sources
Alignment is not a badge — it is a methodology. Every scenario is calibrated against your uploaded regulatory documents, extracted via RAG, not training data.
Comprehensive Capital Analysis and Review — shock calibration follows Fed guidance on severely adverse scenarios.
Dodd-Frank Act Stress Testing — generates scenarios consistent with supervisory stress test methodology.
16 domestic macro variables and 12 international path variables as specified in the supervisory scenario design.
Nonbank financial stress pathways and forward-looking tail risk analysis beyond the core supervisory scenarios.
Risk Factor Coverage
- •76 risk factors across 8 categories
- •37 primary + 39 secondary factors
- •Equity, rates, FX, commodities, credit, volatility, macro, inflation
Cross-Asset Propagation
- •Archimedean copulas (Clayton, Gumbel, Student-t)
- •Primary → secondary shock transmission
- •Correlation-aware dependency modeling
Regulatory RAG
- •Vector search over your uploaded regulatory documents
- •Shock parameter extraction from CCAR/DFAST guidance
- •Severity benchmarks and scenario constraints
Methodology That Answers ‘Where Did This Number Come From?’
Every shock is debated, propagated through copulas, and documented with full provenance for regulatory examination.
Economist Debate
Three AI economists with distinct macro perspectives propose and challenge primary shocks over multiple rounds, converging on a consensus through structured argumentation.
C-Vine Copulas
Cross-asset dependency propagation using Archimedean copulas (Clayton, Gumbel, Student-t) to compute secondary shocks from primary factor movements.
Regulatory RAG
Vector search over ingested CCAR/DFAST guidance documents to extract shock parameters, severity benchmarks, and scenario design constraints.
Likelihood Ranking
Quantitative scoring compares each scenario against live market conditions across four signal dimensions to produce a 0-100 likelihood score with confidence bands.
PII Sanitization
All user data is sanitized before reaching LLM providers. No personally identifiable information leaves your environment.
Audit Trail
Full scenario provenance — every shock traced from economist proposal through copula propagation to final validation.
Risk Factors
Data Sources
Regulatory Pages Indexed
Generation
Regulatory Grounding
Every scenario is anchored in CCAR/DFAST supervisory guidance via RAG retrieval from primary sources.
Likelihood Ranking
Quantitative scoring ranks scenarios by how closely they match current market conditions.
Statistical Coherence
C-Vine copulas propagate shocks with computed correlations, not assumed dependencies.
Audit-Ready Provenance
Every number traces back to a source: regulatory document, market feed, or statistical model.
See Context-Rooted Scenarios for Your Portfolio
Schedule a technical demo with our team. We'll walk through scenario generation, regulatory alignment, and how context flows through every layer.