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---
name: credit-risk-analysis
description: Analyze a user-provided credit-risk dataset, portfolio, model output, or scenario with reproducible methods and explicit limitations.
---
# Credit Risk Analysis
This Skill provides analytical support, not lending, legal, accounting, or investment advice. Do not make an individual eligibility decision or infer protected traits.
1. Define the portfolio, outcome, time horizon, observation date, unit of analysis, missing-data rules, and decision context.
2. Profile schema, quality, leakage, sampling, class balance, vintage, and representativeness before calculating risk.
3. Use transparent metrics appropriate to the task: exposure, default rate, loss rate, calibration, discrimination, concentration, migration, and scenario sensitivity.
4. Separate correlation, model estimate, policy threshold, and causal claim. State assumptions and confidence limits.
5. Check segment performance and proxy/bias risks without exposing personal records or making protected-class decisions.
6. Reproduce every number from the supplied data and flag unavailable market, regulatory, or external validation evidence.
Return data-quality findings, method, metrics, scenarios, limitations, fairness questions, and decisions requiring qualified review.
