AfriScore

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  AfriScore Portfolio Analytics View

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  AfriScore Dashboard

Inspiration

Millions of Africans are credit-invisible despite being financially responsible. We built AfriScore to help banks make fair, explainable, and privacy-first lending decisions using alternative financial data.

What it does

AfriScore uses AI to generate transparent credit scores from alternative financial signals, helping lenders assess applicants with little or no traditional credit history through an easy-to-integrate API.

How we built it

We built AfriScore with Python, Gradio, Plotly, Pandas, and explainable AI techniques, creating an interactive dashboard, scoring engine, API demo, and business impact simulator.

Challenges we ran into

Balancing AI accuracy with explainability and designing a solution that is both bank-ready and easy for non-technical users to understand.

Accomplishments that we're proud of

Built a working AI credit-scoring platform. Added explainable AI for transparent decisions. Created a banking-focused dashboard and API demo. Designed with privacy and financial inclusion in mind.

What we learned

Great AI products need trust, transparency, and seamless integration, not just accurate predictions.

What's next for AfriScore

Pilot AfriScore with a financial institution, improve the scoring model with real-world data, and expand access to responsible credit across Africa.

Built With

• api
• banking
• gradio
• javascript
• pandas
• privacy
• python
• shap