Inspiration

Millions of Africans remain excluded from formal credit due to limited credit histories. AfriScore was created to enable fair, explainable, and privacy-first credit assessment using alternative financial data.

What it does

AfriScore is an AI-powered credit scoring platform that helps financial institutions evaluate credit-invisible applicants through transparent risk scoring, explainable insights, and an integration-ready API.

How we built it

We developed AfriScore using Python, Gradio, Plotly, Pandas, and explainable AI techniques, combining an interactive dashboard, AI scoring engine, business impact analysis, and API demonstration into a unified platform.

Challenges we ran into

Our primary challenge was balancing predictive performance with explainability while designing a solution that aligns with banking workflows and responsible AI principles.

Accomplishments that we're proud of

Built a functional AI-powered credit scoring platform. Implemented explainable AI for transparent lending decisions. Designed a bank-ready dashboard with API integration. Demonstrated measurable business value through ROI analysis.

What we learned

We learned that trust, transparency, and seamless integration are just as important as model performance when building AI solutions for financial services.

What's next for AfriScore

Our next step is to validate AfriScore through pilot partnerships with financial institutions, refine the scoring model using real-world data, and expand access to responsible credit across Africa.

Built With

Share this project:

Updates

Submission history