The training session explores innovative, data-driven approaches to financing agriculture and agribusiness, moving beyond traditional collateral-based models. It introduces participants to the use of financial technology (fintech) and artificial intelligence (AI) in assessing creditworthiness, managing risk, and enabling access to finance for smallholder farmers and agribusinesses.
Participants will learn how alternative data sources—such as satellite imagery, weather patterns, mobile transactions, e-wallet activity, input purchases, and supply chain data—can be leveraged to build digital credit profiles. The session will highlight AI-powered credit scoring models, digital platforms, and embedded finance solutions that support timely and tailored financing throughout the agricultural value chain.
Through case studies and interactive discussions, the session will showcase successful models in different regions and equip financial institutions, and fintech innovators, with the tools to design scalable, inclusive, and sustainable agri-finance solutions.
Key Topics:
- The nature of AgTechs and the kind of services AgTechs can provide to financial institutions.
- Benchmark of AgTech services against the six pillar model developed by IFC and how AgTechs can reduce cost to serve and de-risk lending for financial institutions
- Case Study on how SOWIT, Morocco, de-risks lending for their partner financial institutions along with a demonstration of the type of data the AgTech can provide to a financial institution.
- Case Study on how Adapta creates farm scores solely using data, which are provided as input to credit scoring algorithms for financial institutions
