Apollo Agriculture leverages on advances in machine learning, remote sensing, and mobile money to deliver input finance and agronomic advice to smallholders at a dramatically lower cost than current solutions. Apollo’s digital approach reduces costs and enables rapid scale. Apollo builds machine learning models that process satellite data to infer characteristics of individual farms, such as estimated yields, and uses these models to assess credit risk. For the millions of smallholders dependent on agriculture, these models provide a detailed picture of their economic life.
Apollo uses a digital approach to smallholder agricultural finance. Their first product is a customized bundle of fertilizer and maize seed on credit, along with farming advice delivered via automated voice calls (“IVR”) and SMS. They charge a flat-fee with flexible payment terms, meaning that customers receive inputs at the start of the season and advice throughout, and repay as they have cash available, to align with the cash flows of farmers. Loans are due two weeks after harvest, and the product has an average APR of 20%.
Apollo’s key innovation is the delivery of a proven product - bundled seed, fertilizer, insurance and advice on credit - through a digital, vertically integrated, and cost-effective approach. This starts with the use of high-resolution satellite imagery and machine learning to develop credit profiles for smallholder farmers who otherwise have no financial personality. Complementing this is automated processes from customer acquisition to repayment, that radically reduces the cost of acquiring and serving smallholder customers. In addition, the company’s commission-based rural task force automatically managed through a mobile app gives Apollo a low-cost, as needed customer touch point for in-person interactions like GPS mapping, soil sampling, and harvest measurement. Finally, Apollo provides voice trainings in recognition that their average customer is 50 years old and does not engage effectively via SMS.