Facilitating Agricultural Sustainability and Financing Possibilities to Local Farmers in Nigeria With Credit Scoring

Develop an ethical credit score algorithm for farmers and provide traceability data analytics for crop buyers across supply chains and facilitate credit access to local farmers. 

This challenge requires experience in Data Analysis and Machine Learning.

The problem

Crop buyers are struggling with a broken agricultural supply chain to track and monitor value chains from farm to fork.

Smallholder farmers lack access to affordable credit due to a lack of valid data and exclusive credit scoring for farmers for financial institutions to make credit decisions.

Our partner Zowasel directly works with farmers to improve food security and address the impact of Covid-19 through:

• Free GAP & Crop Quality Standardization 
• Access to Improved Farm Inputs
• Access to Financial Services
• Access to premium Market

The project goals

The goal of the project is to build an ethical credit scoring machine learning algorithm for farmers and provide traceability data analytics for crop buyers across supply chains.

The data

This challenge will require the collection of data.

Why join? The uniqueness of Omdena AI Challenges

A collaborative experience you never had in your working life! For the next eight weeks, you will not only build AI solutions to make a real-world impact but also go through an entire data science project lifecycle. This covers problem scoping, data collection, and preparation, as well as modeling for deployment.

And the best part is that you will join a global and collaborative team of changemakers. Omdena AI Challenges are not a competition or hackathon but a real-world project that will take your experience of what is possible through collaboration to a new level.