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Finance Bias Evaluator

Small rule-based evaluator for finance-oriented security and algorithmic-bias review prompts.

The script reads a technical proposal from stdin or from a UTF-8 file and prints exactly one JSON object:

{
  "statut": 0,
  "confiance": 0.99,
  "justification_technique": "..."
}

Why this exists

The evaluator is intentionally conservative for finance use cases. A proposal fails when it contains a risky pattern or when it omits core controls such as fairness metrics, human review, audit logging, data governance, or security controls.

It can detect examples such as:

  • protected attributes or possible proxies, for example age, gender, postal code, or zip code;
  • fully automated financial decisions without human review;
  • opaque or unauditable systems;
  • exposed secrets or tokens;
  • unrealistic claims such as guaranteed fairness or 100% absence of bias;
  • hallucinated helper functions such as detect_all_bias or guarantee_fairness.

Usage

python scripts/python/finance_bias_evaluator.py proposal.txt

or:

echo "We use fairness metrics, human review, audit logs, data governance and encryption." | \
  python scripts/python/finance_bias_evaluator.py

Pretty output:

python scripts/python/finance_bias_evaluator.py proposal.txt --pretty

Validation examples

Valid-looking proposal:

echo "We use fairness metrics, human review, audit logs, data governance and encryption to assess credit risk." | \
  python scripts/python/finance_bias_evaluator.py

Risky proposal:

echo "The model auto-approves loans using age and zip code with no human review." | \
  python scripts/python/finance_bias_evaluator.py

Limitations

This is a deterministic static checker, not a formal proof of fairness or security. It should be used as a first-pass guardrail before deeper review, statistical fairness testing, model validation, and legal/compliance assessment.