Frequently Asked Questions

StressGen is an AI-augmented financial stress testing platform and proactive market risk manager for financial institutions. It generates historical, hypothetical, and black swan stress scenarios grounded in live market data, news intelligence, and prediction markets. It also monitors market signals continuously and auto-generates scenarios when user-configured thresholds are breached.

Yes. StressGen automates financial stress testing end to end: describe a scenario in plain language and the AI pipeline produces a complete stress scenario — shock tables across 90+ risk factors, copula-validated secondary effects, narrative documentation, and portfolio P&L impact. Scenarios are AI-augmented rather than fully automated: every shock carries provenance and rationale so risk teams can review, challenge, and adjust before sign-off.

StressGen uses a multi-agent AI workflow. An economist debate proposes primary shocks across macroeconomic variables, a quant validator computes secondary correlations using copula models, and a consistency checker validates the final scenario. All outputs are grounded in real-time data from 12+ live sources.

StressGen supports three scenario types: Historical (replay past crises like the 2008 GFC or COVID crash with historically-calibrated shocks), Hypothetical (forward-looking scenarios driven by live market intelligence, news sentiment, and prediction market signals), and Black Swan (extreme tail-risk events with low probability but severe market impact). Each type can be generated at baseline, adverse, or severely adverse severity levels.

StressGen covers 90+ risk factors across equities, interest rates, FX, commodities, credit spreads, volatility, and macroeconomic indicators. Primary factors (55) are proposed by AI economists, while secondary factors (39) are computed through copula-based correlation modeling to ensure statistical consistency.

StressGen supports three scenario types. Historical scenarios replay past crises (2008 GFC, COVID crash, eurozone debt crisis, 1994 bond rout) with historically-calibrated shocks. Hypothetical scenarios are forward-looking, driven by live market intelligence, news sentiment, and prediction market signals. Black Swan scenarios model extreme tail-risk events with low probability but severe market impact. Users can also upload their own documents into Knowledge Folders to ground any scenario in organisation-specific guidance.

StressGen integrates 12+ live data sources including FRED (Federal Reserve Economic Data), Yahoo Finance, ECB, Federal Reserve, multiple providers for news and web research, curated RSS feeds and GDELT for global news coverage, and Kalshi and Polymarket prediction markets for forward-looking indicators.

Each AI-augmented stress scenario passes through a multi-stage pipeline: context gathering from 12+ live data sources, an economist debate that proposes primary shocks with cited rationale, copula-based propagation of secondary shocks, and a consistency check before output. The result is a financial stress scenario with a full audit trail — every number traceable to the data and reasoning that produced it.

Three AI economist agents with distinct perspectives propose primary shock values through a structured debate of up to three rounds. Each economist justifies their projections using real-time data. A consensus mechanism synthesizes their proposals into coherent, defensible scenario parameters.

StressGen uses Archimedean copulas (Clayton, Gumbel, Student-t) to compute secondary risk factor shocks that maintain realistic statistical dependencies. When primary shocks are set by economists, copula models propagate consistent secondary effects across credit spreads, volatility indices, and emerging market currencies.

StressGen pulls real-time contract prices from Kalshi and Polymarket to capture market-implied probabilities of economic events. These forward-looking signals complement traditional macro data and news, providing a crowd-sourced perspective on potential stress scenarios and their likelihood.

Context-rooted means every scenario is grounded in real, verifiable data rather than arbitrary assumptions. StressGen synthesises macroeconomic indicators, market data, news, prediction markets, and user-uploaded knowledge documents to ensure scenarios reflect actual economic conditions and emerging risks.

StressGen uses AES-256 encryption at rest and TLS 1.3 in transit. Multi-tenant isolation ensures organizations cannot access each other's data. All personal information is automatically stripped via PII sanitization before reaching any LLM provider. StressGen never sells or shares customer data.

No. StressGen automatically sanitizes all personally identifiable information before any LLM call using a dedicated PII sanitizer. Names, account numbers, and other sensitive fields are stripped or replaced with safe placeholders, ensuring no client data reaches external AI providers.

All data is encrypted with AES-256 at rest and TLS 1.3 in transit. Database connections use SSL with certificate verification. API keys and secrets are stored in encrypted environment variables, never in source code or client-side storage.

StressGen is pay-per-scenario. 1 credit equals 1 fully-contextualised stress scenario. Credits start at $7.99 each, with bulk discounts up to 37% off. There are no subscriptions, seat licences, or monthly minimums.

No. Every new account gets 3 free credits — enough to generate three full scenarios with the entire pipeline (document RAG, market and macro context, news, prediction markets, agent debate). Credit card is only required when you buy more credits.

No. Credits never expire and there is no monthly minimum. Buy what you need now, generate when you want — the balance stays on your account indefinitely.

If the agent pipeline fails for any reason, the reserved credit is automatically refunded. You only pay for completed scenarios. Re-running a generated scenario with the same definition is also free.

Create a free account — no credit card required. Describe a stress scenario in plain language and StressGen generates a full, context-rooted scenario within minutes. Your 3 signup credits cover the first three runs.

Yes. Custom data feeds, on-prem deployment, dedicated support, and custom pricing libraries are available through Enterprise contracts. Contact sales for institutional terms.