# Manya-Parse-KE 🇰🇪
**Open-source M-Pesa PDF statement parser with transparent financial health scoring.**
Built by Manya Firm Technologies Ltd — Building Africa's Digital Future.
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## The Problem
Over **10 million Kenyans** are blacklisted or underscored by credit systems that use black-box algorithms. These systems penalize users for:
- **Fuliza cycles** — even when caused by stock cycles, not bad behavior
- **Off-net transfers** — sending money to Airtel, treated as "unstable cash flow"
- **Non-financial metadata** — phone battery level, number of contacts, GPS location
- **Ghost debts** — loans already repaid but still listed on CRB reports
Under the **CBK's Draft Financial Consumer Protection Framework (2026)** and the **ODPC Data Protection Act 2019**, every Kenyan has the right to know how an automated system made a decision about them. Yet the tools to exercise that right don't exist.
Until now.
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## What Manya-Parse-KE Does
Turns a messy M-Pesa PDF statement into a clean, structured JSON with:
- ✅ **Transaction categorization** — Utilities, Savings, Loans, Suppliers, Income, Airtime, Betting, Government
- ✅ **Manya Health Score** (300–850) — a fully transparent, cash-flow-centric alternative score
- ✅ **Ghost debt detection** — finds CRB errors with receipt-level evidence
- ✅ **Auto-generated dispute letters** — citing the Data Protection Act 2019
- ✅ **Suggested credit limit** — based on actual cash flow, not metadata proxies
- âś… **Plain English + Swahili explanations** for every score point
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## Quick Start
```bash
# Install
npm install -g manya-parse-ke
# Parse a statement
manya-parse-ke my-mpesa-statement.pdf
# Save full JSON output
manya-parse-ke my-mpesa-statement.pdf --json --out result.json
# Auto-generate CRB dispute letters
manya-parse-ke my-mpesa-statement.pdf --dispute
```
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## Example Output
```json
{
"manya_health_score": 720,
"score_grade": {
"letter": "B",
"label": "Very Good",
"swahili": "Nzuri Sana"
},
"insight …