Stress Scenario Types — DFAST, EBA & Hypothetical

What Are Stress Scenarios?

A stress scenario describes a hypothetical economic event and its projected impact on financial markets. Think of it as a "what if" analysis: what happens to stock markets, interest rates, currencies, and commodities if a specific economic shock occurs?

StressGen generates a complete table of risk factor shocks for each scenario, showing how every tracked financial variable would be affected. These results are designed to meet regulatory requirements for bank stress testing submissions.

Every shock in a StressGen scenario comes with full provenance: which regulatory document informed the parameters, which market data feeds provided the baseline, and which statistical model propagated secondary effects. This traceability is what separates context-rooted scenarios from generic LLM output.

Scenario Types

StressGen supports four scenario types:

• Historical — Based on real historical events (e.g., the 2008 financial crisis, the 2020 COVID crash). The AI uses the actual market impacts as a reference for calibrating shocks.
• Regulatory — Aligned with DFAST, EBA, or PRA supervisory frameworks. These follow specific regulatory guidelines for risk factor coverage and severity.
• Hypothetical — Forward-looking, market-intelligence-driven scenarios. You define the event, and the AI generates shocks based on current conditions and historical patterns.
• Black Swan — Extreme tail-risk events with low probability but severe impact. Think pandemic, sovereign default, or unexpected geopolitical escalation.

Creating a Scenario

Every scenario starts with a description of the economic event you want to model. Write it in plain English — the AI will interpret your intent and determine the appropriate shocks.

Good scenario descriptions include:

• The triggering event (e.g., a central bank rate decision, geopolitical conflict, pandemic)
• Expected severity (mild correction vs. severe crisis)
• Time horizon and affected regions or sectors
• Any specific risk factors you want emphasized

Scenario Workflow

Every scenario follows a lifecycle with clear statuses:

Editing & Versioning

After generating a scenario, you can refine it:

• Edit description — Update the scenario narrative and regenerate shocks with the revised context.
• Adjust data sources — Toggle different data feeds on or off to see how they influence the results.
• Version history — Each regeneration creates a new version so you can track changes over time.

Comparing Scenarios

Use the comparison feature to view multiple scenarios side by side. This is especially useful for:

• Comparing regulatory baseline vs. severely adverse scenarios
• Evaluating how different trigger events affect the same risk factors
• Reviewing how scenario shocks change when different data sources are enabled

Interpreting Results

Each generated scenario includes:

• Shock table — The complete list of risk factor impacts, organized by asset class. Positive values indicate increases; negative values indicate declines.
• Confidence score — An indicator of how well the generated shocks align with historical patterns and regulatory precedent.
• Narrative summary — A plain-language explanation of the scenario's economic logic and why each shock was assigned its magnitude.
• Supporting data — The real-world data points (economic indicators, news events, market prices) that informed the AI's decisions.
• Likelihood ranking — How probable this scenario is given current market conditions, ranked against your other completed scenarios.

Exporting & Sharing

Scenarios can be exported for use in downstream systems or regulatory submissions. Export options include structured data formats suitable for risk management platforms, as well as presentation-ready summaries for stakeholder review.