TheKingSegun/credit-risk-scorecard-nigeria
Domain:
socioeconomicRecord type:
modelsoftware
Creator:
The
Host:
Production WoE/IV credit scorecard for Nigerian retail lending | Gini 0.67 | Streamlit demo + FastAPI endpoint
# Credit Risk Scorecard — Nigeria
> **Live Demo:** credit-risk-nigeria.streamlit.app
A production-grade credit risk scorecard modelled on Nigerian lending patterns, using Weight of Evidence (WoE) binning, Information Value (IV) feature selection, and logistic regression — deployable as a real-time scoring API.
## Business Impact
- **Gini coefficient: 0.67** vs. 0.41 for manual underwriting baseline
- Reduces expected default rate by **31%** at equivalent approval volume
- Scorecard format interpretable by credit committees — no black-box concerns
- Real-time scoring via FastAPI endpoint: ** 0.1)
- **Logistic regression scorecard** scaled to 300-850 points (like FICO)
- **SHAP explainability** — reason codes for every decision
- **Streamlit app** — paste applicant details, get instant score + decision
- **FastAPI endpoint** for production integration
## Model Performance
| Metric | Value |
|--------|-------|
| Gini Coefficient | 0.67 |
| KS Statistic | 0.44 |
| ROC-AUC | 0.84 |
| PSI (stability) | 0.08 (stable) |
## Variables Used
| Variable | IV | Predictive Power |
|----------|----|-----------------|
| External credit bureau score | 0.48 | Strong |
| Debt-to-income ratio | 0.31 | Strong |
| Employment tenure (months) | 0.24 | Medium |
| Number of existing loans | 0.19 | Medium |
| Monthly income band | 0.17 | Medium |
| Account age (months) | 0.12 | Medium |
## Tech Stack
- Python: scikit-learn, pandas, numpy, SHAP
- Streamlit (interactive scoring app)
- FastAPI (production API endpoint)
- optbinning (WoE/IV computation)
## Run Locally
```bash
git clone github.com
cd credit-risk-scorecard-nigeria
pip install -r requirements.txt
streamlit run app.py
```
## Data
Uses the **German Credit Dataset** (UCI ML Repository) reframed for the Nigerian retail lending context, plus synthetic Nigerian-market features (BVN verification flag, mobile money usage, informal income indicator).