Fix Unreliable Stress Testing in Finance with Claude AI

Use Claude to mine regulatory texts into concrete scenario requirements

Start by consolidating the key regulatory and supervisory documents that drive your stress-testing obligations—for example, internal risk appetite statements, central bank stress manuals, and relevant EBA/BaFin/ECB guidelines. Upload or connect these texts to Claude (via your chosen secure integration), and ask it to extract scenario design requirements, coverage expectations and documentation standards.

Example prompt:

You are a senior banking supervisor with expertise in stress testing.

Input:
- Internal Stress Testing Policy (PDF)
- ECB Stress Test Methodology 20XX (PDF)

Task:
1. Extract all explicit and implicit expectations regarding:
   - Types of scenarios (macro, market, idiosyncratic, combined)
   - Horizon, severity and frequencies
   - Required documentation and governance
2. Summarise them in a structured table with columns:
   - Source document and paragraph
   - Requirement
   - Implication for scenario design
3. Highlight any gaps or inconsistencies in our internal policy.

Expected outcome: a clear, audit-ready requirements list that your risk team can validate and use as a baseline for systematic scenario design.

Generate and refine scenario narratives before quantification

Many stress tests jump too quickly to numbers. Use Claude to first craft robust, internally consistent scenario narratives. Feed it your current scenario library, recent risk committee minutes, and macro research, then instruct it to propose additional stress scenarios with explicit economic and behavioural chains.

Example prompt:

You are a stress testing expert in a banking group.

Input:
- Our current scenario library (DOCX)
- Last 4 quarterly risk reports (PDF)
- Macro research on "stagflation" and "energy shock" (PDF)

Task:
1. Propose 5 new macroeconomic stress scenarios relevant to our portfolio.
2. For each scenario, describe:
   - Trigger events and narrative (max 200 words)
   - Key macro variables (GDP, unemployment, inflation, rates, FX)
   - Expected impacts on:
     * Wholesale funding costs
     * Retail credit quality
     * Market risk positions
3. Ensure scenarios are distinct from existing ones and cover tail risks.
4. Output in a table + short narratives for management.

Risk managers then review, challenge and select scenarios for quantification, significantly reducing the time spent on initial drafting.

Map scenarios systematically into P&L, balance sheet and cash flow drivers

To tackle the "propagation" problem, let Claude help you build and maintain a driver map between scenario variables and financial statement line items. Provide your existing ALM model documentation, P&L/balance sheet structures and any internal mapping documents.

Example prompt:

You are assisting with stress test model documentation.

Input:
- ALM/stress testing methodology document (PDF)
- Chart of accounts (XLSX export as text)
- Existing driver mapping notes (DOCX)

Task:
1. Create a mapping between stress variables and financial statement items:
   - Macro variables (GDP, unemployment, rates etc.)
   - Market variables (spreads, FX, equities)
   - Idiosyncratic variables (default of top 20 counterparties)
2. For each mapping, specify:
   - Direction of impact (positive/negative)
   - Main transmission channels
   - Relevant model or data source
3. Highlight any financial items without a clear driver linkage.

This produces a living document that supports both implementation and model governance, while revealing where your propagation logic is weak or missing.

Standardise scenario documentation and governance packs

Once scenarios are agreed, Claude can auto-generate consistent documentation for risk committees, internal audit and regulators. Define a documentation template covering narrative, assumptions, parameterisation, transmission channels, limitations and validation results. Then have Claude fill this based on your working files, meeting notes and model outputs.

Example prompt:

You are preparing governance documentation for a new stress scenario.

Input:
- Approved scenario narrative (DOCX)
- Parameter table (CSV as text)
- Excerpts from risk committee minutes (DOCX)

Task:
Using our internal "Scenario Governance Template" (section headings below), draft a complete document:
1. Scenario overview and rationale
2. Link to regulatory and internal requirements (cite sources)
3. Assumptions and parameters
4. Transmission channels into P&L, balance sheet and liquidity
5. Limitations and known weaknesses
6. Validation and backtesting evidence
7. Change log from previous version.

Ensure all claims are traceable back to the inputs and flag any missing information.

Expected outcome: governance packs that are consistent across scenarios, easier to review, and faster to update when assumptions change.

Use Claude as a QA layer on models, scenarios and results

Beyond generation, Claude is highly effective as a quality-assurance layer on your stress-testing framework. After a stress round, feed it the scenario definitions, key outputs and commentary, and ask it to challenge internal consistency and coverage against your documented risk profile.

Example prompt:

You are an internal model validation expert.

Input:
- Description of all scenarios used in the latest stress test (DOCX)
- Summary of portfolio risk profile (DOCX)
- Key stress test results (PDF)

Task:
1. Check whether the scenario set adequately covers:
   - Our main concentrations (by sector, region, product)
   - Funding and liquidity risks
   - Counterparty and concentration risks
2. Identify any obvious blind spots or underrepresented risk drivers.
3. Flag internal inconsistencies (e.g., narrative vs. parameter severity).
4. Suggest 3–5 targeted improvements for the next cycle.

This does not replace formal model validation, but provides a fast, documented challenge that can significantly improve quality between full validation cycles.

Integrate Claude into a secure, finance-ready workflow

For production use in finance, technical integration and security are non-negotiable. Work with IT and risk to route Claude through your approved infrastructure (e.g., private instance, API via controlled backend), enforce access controls, and implement logging of prompts and outputs for auditability.

Define a simple workflow: data preparation (anonymisation where needed), Claude interaction via pre-approved prompt templates, human review, and then storage of accepted outputs in your document management system. Reruption’s AI PoC approach can help you prototype this end-to-end flow on a contained use case—such as automating documentation for two key scenarios—before expanding to broader stress-testing tasks.

When implemented this way, finance teams typically see: 30–50% faster scenario documentation, significantly broader scenario coverage without extra headcount, and a noticeable reduction in findings during internal reviews of scenario and stress testing—while keeping risk ownership firmly with the first and second lines of defence.