Paper short abstract:

Our paper discusses the datafication of smallholder finance in Kenya. We focus in particular on the embeddedness of financial services into digital platforms that provide farmers with end-to-end services. We argue that the platforms' business model risk entrenching pre-existing inequalities.

Paper long abstract:

Our paper discusses the datafication of smallholder finance in Kenya. We focus in particular on the embeddedness of financial service providers into platforms that provide farmers with end-to-end solutions, from credit scoring to advisory support and input distribution. We argue that, in so doing, digital platforms recalibrate the risk-assessment procedures to underwrite agricultural loans and construct an ideal type of farmer whose financial behaviours can be predicted and credit-worthiness calculated.

Access to credit is a critical challenge for Kenyan small-holder farmers. Financial service providers are often reluctant to lend to smallholders because of a mix of factors, including price volatility of inputs and outputs in domestic and international markets, erratic weather patterns, lack of written records and contracts between producers and buyers and transaction amounts too small to justify investments in rural areas. MFIs and saving groups have only partially addressed their unmet demand, mostly helping borrowers smooth consumption and address unexpected needs.

In recent years, however, a new breed of digital service providers has appeared on the Kenyan market. By using transactional and behavioural data to generate a digital footprint, these Fintechs 'de-risk' smallholder finance and are thus able to provide loans, insurance and other financial services via mobile phone.

Based on a qualitative study of agricultural platforms in Kenya, our paper argues that the growing emphasis placed by financial actors on data analytics for increased predictive power risks compounding pre-existing inequalities rooted in geography, social networks, value chains.