Research & Analysis
Publication

Using Satellite Data in Financial Inclusion

Financial services providers that see an opportunity to reach financially excluded people in rural areas can use new technology to remotely gather and analyze data on potential customers.

High-quality satellite data are becoming increasingly available. By leveraging advances in machine learning—the ability of computers to analyze data quickly and at scale—providers can gain valuable insights into customers’ economic, environmental, and demographic characteristics. This guide explains foundational concepts of machine learning and how financial services providers can apply those methods to leverage information contained in satellite images for the purpose of credit scoring.

This guide focuses on smallholder finance, but providers may find it useful for other applications as well, such as estimating local infrastructure, housing, and income levels; assessing the effectiveness of farming practices; crop insurance and risk calculations; and forecasting yields to combat food security problems.

Resources

Publication

Financial services providers can improve their businesses by using segmentation to develop a more accurate understanding of their customers. This guide shows providers how they can use data analytics to understand their customers by performing more complex analyses and extracting insights that were previously hidden.
Publication

Statistical models can help lenders in emerging markets standardize and improve their lending decisions. This guide emphasizes that the effectiveness of data analytics approaches often involves building a broader data-driven corporate culture.