Index-based insurance provides a scalable instrument for managing agricultural risk under increasing climate variability. By linking payouts to observable environmental indices such as rainfall or temperature, these contracts reduce the high monitoring costs and information asymmetries associated with traditional indemnity insurance. However, their effectiveness is fundamentally constrained by basis risk, defined as the mismatch between realised losses and index-based payouts. This mismatch reduces contract reliability, limits income protection and adoption by farmers, especially under evolving climate conditions.
This study develops an improved optimization model for the design of index insurance contracts. The model is formulated to directly account for the discrepancy between realized losses and insurance payouts within the objective function. A regularization term is introduced in the model to penalize both the magnitude and variability of the mismatch between losses and payouts. This enables more precise control over payout performance and income stability while preserving the economic structure of standard index insurance models.
Preliminary results indicate that the proposed model improves the alignment between payouts and realized losses as compared to classical models. These findings suggest that incorporating this mismatch directly into the optimization process can enhance contract reliability. This study contributes to the development of more climate-resilient financial instruments by providing a tractable and practically relevant approach to index insurance design, with potential implications for improving income protection in agriculture under climate risk.