Mfana/african-device-financing-risk-analytics

End-to-end telecom and fintech analytics platform using synthetic African smartphone financing data. # African Device Financing Risk Analytics ## Overview This project simulates an end-to-end telecom and fintech analytics platform for African smartphone financing markets. The platform demonstrates: - Synthetic telecom-fintech data generation - Data quality validation frameworks - ETL transformation pipelines - Executive KPI reporting - Risk segmentation analytics - CI/CD-ready project structure - Data engineering best practices --- ## Business Context Smartphone financing is a major driver of digital inclusion across African telecom markets. This project simulates how mobile network operators and fintech partners can use alternative data sources to analyze: - Customer repayment behavior - Credit risk exposure - Device financing performance - Market-level portfolio health - Financial inclusion trends Markets simulated include: - South Africa - Tanzania - Mozambique - DRC - Lesotho - Kenya - Ethiopia - Egypt --- ## Project Architecture ``` african-device-financing-risk-analytics/ │ ├── data/ │ ├── device_financing_data.csv │ └── processed_device_financing_data.csv │ ├── docs/ │ ├── notebooks/ │ ├── src/ │ ├── generate_data.py │ ├── data_quality.py │ ├── etl_pipeline.py │ └── kpi_dashboard.py │ ├── tests/ │ ├── requirements.txt └── README.md ``` --- ## Data Engineering Components ### 1. Synthetic Data Generation Generates telecom-fintech customer financing data using Python, NumPy, Pandas, and Faker. ### 2. Data Quality Validation Implements governance checks including: - Null validation - Domain validation - Financial consistency checks - Risk category validation ### 3. ETL Pipeline Transforms raw financing data into analytics-ready datasets with engineered features such as: - Deposit ratio - Loan-to-income ratio - Default flags - High-risk indicators ### 4. KPI Dashboard Produces executive-level portfolio insights including: - Total loan book - Default rates - Market performance - Risk segmentation --- ## Technologies Used - Python …