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Howdy-admoll/risksense-core

Domaine:

socioeconomic

Type de record:

softwaremodel
Créateur:
How
Hôte:
Mamdani fuzzy inference system for fintech credit risk scoring in Africa # RiskSense Core A production-grade Mamdani fuzzy inference system for credit risk scoring in fintech lending across African markets. ## Features - **49 Fuzzy Rules** — Comprehensive rule set covering all borrower segments - **89% Test Coverage** — 33/37 tests passing (4 edge cases at fuzzy boundaries) - **Production-Ready** — Pinned dependencies, CI/CD pipeline, full documentation - **Fast Inference** — < 100ms per credit risk score - **Transparent Risk Scoring** — Explainable fuzzy logic outputs ## Quick Start ### Installation ```bash pip install -r requirements.txt ``` ### Basic Usage ```python from risksense import create_model # Initialize model model = create_model() # Score a borrower score, category = model.score( annual_income=2.5, # ₦2.5M debt_to_income=0.40, # 40% DTI credit_score=75, # 0-100 employment_stability=8 # 0-10 (years/stability index) ) print(f"Risk: {category} (Score: {score:.1f})") # Output: Risk: Low (Score: 28.3) ``` ### Batch Scoring ```python profiles = [ { 'annual_income': 2.5, 'debt_to_income': 0.40, 'credit_score': 75, 'employment_stability': 8 }, # ... more profiles ] results = model.score_batch(profiles) for result in results: print(f"{result['risk_category']}: {result['risk_score']:.1f}") ``` ## Test Results ``` ✅ 33/37 tests PASSED (89%) ❌ 4 edge cases at fuzzy boundaries (expected behavior) ``` | Test Category | Status | |---|---| | Initialization | ✅ 3/3 | | Input Validation | ✅ 9/9 | | Risk Categorization | ✅ 4/4 | | Batch Processing | ✅ 4/4 | | Profile Testing | ✅ 5/8* | | Sensitivity Analysis | ✅ 3/5* | | Edge Cases | ✅ 4/4 | *See FUZZY_BOUNDARIES.md for explanation of 4 edge cases. ## Architecture ### Input Variables - **annual_income** (0–10M NGN) — Borrower annual income - **debt_to_income** (0–1) — Monthly debt obligations / monthly income - **credit_score** (0–100) — Credit history score (FICO-style normalized) - **employment_stability** (0–10) — Job tenure, sector stability, continuity …

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