Bundling crop insurance with digital credit to boost agricultural investments: Findings from a randomized trial in two states in India

Smallholder farmers are among the most vulnerable to extreme weather events due to high dependence on rainfed agriculture, constrained financial resources, and the absence of insurance and safety nets. Unable to meet the collateral and land title requirements set by credit bureaus, female farmers, tenant farmers, and sharecroppers are often turned away from borrowing, limiting their ability to expand production and invest in modern inputs. “KhetScore” is a novel digital credit-scoring approach that utilizes remote sensing and machine learning to assess creditworthiness based on the expected productivity of a plot rather than the profile of a borrower. Using a cluster randomized trial in two states of India, we evaluate the effect of KhetScore in unlocking farmers’ access to credit and the impact of bundling KhetScore credit with insurance in mitigating borrowing risks and protecting farmers from default. Results reveal that offering KhetScore credit alone significantly crowds in borrowing from formal sources without driving borrowers into indebtedness. We hypothesize that bundling KhetScore credit with insurance can additionally protect farmers from indebtedness, but we cannot speak to the effect due to few insurance payouts being triggered. Improved access to credit through KhetScore credit-scoring is found to be effective in expanding agricultural production mainly at the extensive margin through increasing the area cultivated, especially in the Rabi (dry) season when land is often left fallow due to limited access to irrigation.