# WIA-FIN-020: Credit Scoring Standard 📊

**Status:** Final
**Version:** 2.0
**Category:** Finance/Economy
**Emoji:** 📊

> 홍익인간 (弘益人間) (홍익인간) · Benefit All Humanity

## Overview

The WIA-FIN-020 Credit Scoring Standard defines a comprehensive framework for building fair, accurate, and explainable AI-powered credit assessment systems. This standard addresses the critical need for modern credit scoring that combines traditional bureau data with alternative sources while ensuring regulatory compliance and fairness.

## 🎯 Key Features

- **AI/ML Models**: XGBoost, LightGBM, and neural networks achieving 0.85+ AUC
- **Alternative Data**: Integration with bank transactions, rent, utilities, employment
- **Real-Time Scoring**: Sub-100ms decisioning with instant explanations
- **Fairness Built-In**: Bias detection, mitigation, and regular fairness audits
- **Regulatory Compliance**: FCRA, ECOA, GDPR, Model Risk Management (SR 11-7)
- **Explainable AI**: SHAP-based factor analysis with consumer-friendly explanations

## 📁 Repository Structure

```
credit-scoring/
├── index.html              # Landing page with overview
├── simulator/              # Interactive credit scoring simulator
│   └── index.html         # 5-tab simulator (Overview, Testing, Validation, Results, Integration)
├── ebook/                 # Comprehensive implementation guides
│   ├── en/                # English version (9 files)
│   │   ├── index.html
│   │   └── chapter1-8.html
│   └── ko/                # Korean version (9 files)
│       ├── index.html
│       └── chapter1-8.html
├── spec/                  # Technical specifications
│   ├── WIA-FIN-020-spec-v1.0.md
│   ├── WIA-FIN-020-spec-v1.1.md
│   ├── WIA-FIN-020-spec-v1.2.md
│   └── WIA-FIN-020-spec-v2.0.md
├── api/                   # SDK implementations
│   └── typescript/
│       ├── package.json
│       └── src/
│           ├── types.ts
│           └── index.ts
└── README.md             # This file
```

## 🚀 Quick Start

### 1. Explore the Standard

Visit the [landing page](./index.html) to see an overview of the credit scoring standard.

### 2. Try the Simulator

Open [simulator/index.html](./simulator/index.html) to:
- Test different applicant profiles
- See real-time score calculations
- Understand factor impacts
- View fairness metrics
- Test API integration

### 3. Read the Guide

Choose your language:
- **English:** [ebook/en/index.html](./ebook/en/index.html)
- **Korean:** [ebook/ko/index.html](./ebook/ko/index.html)

### 4. Integrate the API

Install the TypeScript SDK:

```bash
npm install @wia/credit-scoring
```

```typescript
import { CreditScoringClient } from '@wia/credit-scoring';

const client = new CreditScoringClient({
  apiKey: 'your-api-key',
  environment: 'production'
});

const result = await client.score({
  applicant: {
    firstName: 'John',
    lastName: 'Doe',
    ssn: '***-**-1234',
    dateOfBirth: '1990-01-15'
  },
  employment: {
    annualIncome: 75000,
    employmentStatus: 'full-time'
  },
  loanRequest: {
    amount: 25000,
    purpose: 'debt_consolidation'
  }
});

console.log(`Score: ${result.score}`);
console.log(`Decision: ${result.decision.outcome}`);
console.log(`Factors:`, result.factors);
```

## 📊 Standard Components

### Architecture

The standard defines a 4-phase architecture:

1. **Data Collection & Integration**
   - Credit bureau APIs (Experian, Equifax, TransUnion)
   - Alternative data sources (Plaid, Yodlee, etc.)
   - Open Banking integrations
   - Real-time validation

2. **AI Model Processing & Scoring**
   - Ensemble models (XGBoost + Neural Networks)
   - 500+ engineered features
   - Automated feature selection
   - SHAP-based explainability

3. **Risk Assessment & Decision Engine**
   - Configurable risk thresholds
   - Credit policy rules
   - Automated approval workflows
   - Fraud detection integration

4. **Monitoring & Continuous Learning**
   - Real-time performance tracking
   - Data and model drift detection
   - Automated retraining pipelines
   - Fairness audits

### Performance Requirements

- **Accuracy:** AUC-ROC ≥ 0.82
- **Latency:** < 100ms score calculation
- **Uptime:** 99.99% SLA
- **Fairness:** Disparate impact ratio ≥ 0.85
- **Explainability:** Top 3-5 factors for every decision

## 🔐 Compliance & Fairness

### Regulatory Compliance

- ✅ **FCRA** (Fair Credit Reporting Act)
- ✅ **ECOA** (Equal Credit Opportunity Act)
- ✅ **GDPR** (General Data Protection Regulation)
- ✅ **SR 11-7** (Model Risk Management)
- ✅ **SOC 2 Type II** (Security)

### Fairness Metrics

- **Demographic Parity:** Approval rates consistent across protected groups
- **Equal Opportunity:** True positive rates balanced
- **Calibration:** Predicted probabilities match actual outcomes
- **Disparate Impact:** Ratio ≥ 0.85 for all protected classes

## 📖 Documentation

### Specifications

- **[v1.0](./spec/WIA-FIN-020-spec-v1.0.md)** - Initial release (2025-01-15)
- **[v1.1](./spec/WIA-FIN-020-spec-v1.1.md)** - Alternative data guidelines (2025-03-01)
- **[v1.2](./spec/WIA-FIN-020-spec-v1.2.md)** - Open Banking integration (2025-06-15)
- **[v2.0](./spec/WIA-FIN-020-spec-v2.0.md)** - Blockchain & continuous scoring (2025-12-01)

### Implementation Guides

**English:**
- [Chapter 1: Introduction to Credit Scoring](./ebook/en/chapter1.html)
- [Chapter 2: Credit Scoring Models](./ebook/en/chapter2.html)
- [Chapter 3: Data Sources & Feature Engineering](./ebook/en/chapter3.html)
- [Chapter 4: Implementation Guide](./ebook/en/chapter4.html)
- [Chapter 5: AI/ML Model Development](./ebook/en/chapter5.html)
- [Chapter 6: Fairness & Regulatory Compliance](./ebook/en/chapter6.html)
- [Chapter 7: Case Studies](./ebook/en/chapter7.html)
- [Chapter 8: Future of Credit Scoring](./ebook/en/chapter8.html)

**Korean:** [목차](./ebook/ko/index.html)

## 🎓 Use Cases

### Traditional Banking
- Personal loans
- Auto loans
- Mortgages
- Credit cards

### Fintech Applications
- Buy-now-pay-later (BNPL)
- Peer-to-peer lending
- Digital wallets with credit
- Embedded finance

### Commercial Lending
- Small business loans
- Invoice financing
- Working capital loans
- Merchant cash advances

### Financial Inclusion
- Thin-file consumer scoring
- Alternative data assessment
- Refugee and immigrant credit
- Microfinance applications

## 🔧 Technology Stack

### ML/AI Frameworks
- XGBoost / LightGBM
- TensorFlow / PyTorch
- SHAP (explainability)
- Scikit-learn

### Data Processing
- Apache Spark
- Pandas / NumPy
- Feature engineering pipelines

### Infrastructure
- Kubernetes
- Docker
- AWS / GCP / Azure
- PostgreSQL / MongoDB / Redis

### Monitoring
- Prometheus + Grafana
- ELK Stack
- DataDog
- Sentry

## 📈 Performance Benchmarks

| Metric | Traditional FICO | WIA-FIN-020 |
|--------|-----------------|-------------|
| AUC-ROC | 0.74 | 0.86 |
| Approval Rate | 62% | 74% (+12%) |
| Default Rate | 3.5% | 3.2% (-0.3%) |
| Decision Time | 45 days | < 1 day |
| Thin-File Coverage | 0% | 85% |
| Fairness (DI Ratio) | 0.72 | 0.87 |

## 🤝 Contributing

We welcome contributions to improve this standard! Please see our [contribution guidelines](https://github.com/WIA-Official/wia-standards/blob/main/CONTRIBUTING.md).

## 📝 License

This standard is published under the MIT License. See [LICENSE](../../LICENSE) for details.

## 🔗 Related Standards

- **WIA-FIN-001:** Digital Payment Systems
- **WIA-FIN-002:** Blockchain Finance
- **WIA-FIN-003:** Cryptocurrency Standard
- **WIA-FIN-017:** AI Trading Standard
- **WIA-INTENT:** Intent Expression Standard

## 📞 Support & Contact

- **GitHub:** [WIA-Official/wia-standards](https://github.com/WIA-Official/wia-standards)
- **Website:** [wia.org](https://wia.org)
- **Email:** standards@wia.org
- **Discord:** [WIA Community](https://discord.gg/wia-official)

## 🏛️ Governance

This standard is maintained by the **World Certification Industry Association (WIA)** under SmileStory Inc.

### Philosophy

홍익인간 (弘益人間) (홍익인간) - Benefit All Humanity

Our mission is to create financial technology standards that:
- Expand access to affordable credit
- Reduce bias and discrimination
- Protect consumer privacy
- Enable innovation
- Maintain financial stability

---

## 📅 Version History

- **v2.0** (2025-12-01) - Blockchain integration, continuous scoring, enhanced fairness
- **v1.2** (2025-06-15) - Open Banking integration, consumer dashboard
- **v1.1** (2025-03-01) - Alternative data guidelines, enhanced metrics
- **v1.0** (2025-01-15) - Initial release

---

**© 2025 SmileStory Inc. / WIA - World Certification Industry Association**

홍익인간 (弘益人間) (홍익인간) · Benefit All Humanity