Below is a fully‑stocked, student‑ and AI‑friendly, RTT‑aligned, regime‑aware schema for credit reporting. It’s designed to drop directly into your repo as:
credit_reporting_rtt.schema.json
It follows your house style:
- Minimal
- Triadic
- Regime‑indexed
- Simulation‑ready
- Safe for beginners, expandable for experts
- Aligned with RTT substrate → regime → resonance stack
It also mirrors the structure of your other RTT schemas (environment, entity, intent, tick, etc.) so students can immediately recognize the pattern.
credit_reporting_rtt.schema.json (complete example)#
{
"$schema": "https://json-schema.org/draft/2020-12/schema",
"$id": "https://triadicframeworks.org/schemas/finance/credit_reporting_rtt.schema.json",
"title": "Regime-Aware Credit Reporting (RTT)",
"description": "A minimal, student- and AI-friendly schema for representing credit reporting data, models, and interpretations across regimes.",
"type": "object",
"properties": {
"metadata": {
"type": "object",
"description": "Basic file-level metadata for lineage, versioning, and authorship.",
"properties": {
"schema_version": { "type": "string", "example": "1.0.0" },
"created_at": { "type": "string", "format": "date-time" },
"updated_at": { "type": "string", "format": "date-time" },
"author": { "type": "string" },
"notes": { "type": "string" }
},
"required": ["schema_version"]
},
"identity": {
"type": "object",
"description": "Identity substrate: the entity whose credit behavior is being reported.",
"properties": {
"entity_type": {
"type": "string",
"enum": ["individual", "business", "synthetic", "unknown"]
},
"identifiers": {
"type": "object",
"description": "Non-sensitive, simulation-safe identifiers.",
"properties": {
"local_id": { "type": "string" },
"jurisdiction": { "type": "string" }
}
},
"demographics": {
"type": "object",
"description": "Optional; for fairness simulations only.",
"properties": {
"age_bucket": { "type": "string" },
"region": { "type": "string" }
}
}
}
},
"substrate": {
"type": "object",
"description": "The raw credit substrate: tradelines, balances, payments, inquiries.",
"properties": {
"tradelines": {
"type": "array",
"items": {
"type": "object",
"properties": {
"type": { "type": "string", "enum": ["credit_card", "loan", "mortgage", "auto", "other"] },
"status": { "type": "string", "enum": ["open", "closed", "charged_off"] },
"balance": { "type": "number" },
"limit": { "type": "number" },
"payment_history": {
"type": "array",
"items": { "type": "string", "enum": ["on_time", "late_30", "late_60", "late_90", "default"] }
},
"opened_at": { "type": "string", "format": "date" }
},
"required": ["type", "status"]
}
},
"inquiries": {
"type": "array",
"items": {
"type": "object",
"properties": {
"date": { "type": "string", "format": "date" },
"type": { "type": "string", "enum": ["hard", "soft"] }
}
}
},
"public_records": {
"type": "array",
"items": {
"type": "object",
"properties": {
"record_type": { "type": "string", "enum": ["bankruptcy", "lien", "judgment"] },
"date": { "type": "string", "format": "date" }
}
}
}
}
},
"regime": {
"type": "object",
"description": "The regime context in which the credit data is interpreted.",
"properties": {
"macro_regime": {
"type": "string",
"enum": ["expansion", "recession", "high_inflation", "low_rate", "stress", "unknown"]
},
"regulatory_regime": {
"type": "string",
"enum": ["pre_crisis", "post_crisis", "gdpr", "dodd_frank", "emerging_market", "unknown"]
},
"data_regime": {
"type": "string",
"enum": ["bureau_only", "alt_data_enabled", "cashflow_rich", "thin_file", "synthetic"]
},
"model_regime": {
"type": "string",
"enum": ["logistic_scorecard", "ml_blackbox", "explainable_ml", "regime_switching", "hybrid"]
}
}
},
"features": {
"type": "object",
"description": "Feature engineering layer: what the model actually sees.",
"properties": {
"utilization": { "type": "number", "description": "Total balance / total limit" },
"delinquency_count_12m": { "type": "integer" },
"inquiry_count_6m": { "type": "integer" },
"file_age_months": { "type": "integer" },
"alt_data_signals": {
"type": "object",
"properties": {
"utility_payments": { "type": "string", "enum": ["good", "mixed", "poor", "none"] },
"rent_payments": { "type": "string", "enum": ["good", "mixed", "poor", "none"] }
}
}
}
},
"model": {
"type": "object",
"description": "The model used to compute PD, score, or other credit signals.",
"properties": {
"model_type": {
"type": "string",
"enum": ["logistic_regression", "gradient_boosting", "neural_network", "markov_regime_switching"]
},
"parameters": {
"type": "object",
"description": "Model parameters; simulation-safe.",
"properties": {
"betas": {
"type": "object",
"description": "Feature coefficients (if applicable).",
"additionalProperties": { "type": "number" }
},
"regime_parameters": {
"type": "object",
"description": "Regime-specific parameter sets.",
"properties": {
"expansion": { "type": "object", "additionalProperties": { "type": "number" } },
"recession": { "type": "object", "additionalProperties": { "type": "number" } },
"stress": { "type": "object", "additionalProperties": { "type": "number" } }
}
}
}
}
}
},
"outputs": {
"type": "object",
"description": "Model outputs, regime-indexed.",
"properties": {
"pd": { "type": "number", "description": "Probability of default (0–1)" },
"score": { "type": "number", "description": "Scalar score (e.g., 300–850)" },
"regime_adjusted_score": {
"type": "object",
"description": "Score adjusted per regime.",
"properties": {
"expansion": { "type": "number" },
"recession": { "type": "number" },
"stress": { "type": "number" }
}
},
"explanations": {
"type": "array",
"items": { "type": "string" }
}
}
},
"meaning": {
"type": "object",
"description": "Interpretation layer: what the outputs mean in this regime.",
"properties": {
"risk_band": {
"type": "string",
"enum": ["low", "medium", "high", "very_high"]
},
"access_implications": {
"type": "string",
"description": "What access to credit looks like in this regime."
},
"fairness_notes": {
"type": "string",
"description": "Any fairness or bias considerations relevant to this regime."
}
}
}
},
"required": ["metadata", "substrate", "regime", "outputs"]
}Why this schema works for your ecosystem#
1. Triadic alignment#
- Being → substrate
- Knowing → model + features + regime
- Meaning → outputs + interpretation
2. Regime awareness is first-class#
Macro, regulatory, data, and model regimes are explicit, not implicit.
3. Simulation-ready#
Students can:
- Swap regimes
- Swap model types
- Compare outputs
- Run “what if” scenarios
4. Drift-safe#
No sensitive data.
No PII.
No real credit files.
Perfect for teaching.
5. Extensible#
You can add:
scenarioblockstickintegrationentitycrosslinksenvironmentmacro feeds
If you want, I can also generate:#
- A companion example JSON file (
credit_reporting_rtt.example.json) - A diagram showing the triadic flow
- A museum‑style placard explaining the schema’s purpose
- A simulation notebook outline for students
Just tell me which artifact you want next.