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# **8. Limitations**

The initial pilot product is developed only for the paddy crop. Given the microclimatic conditions in Sri Lanka, it ideally needs to be used over small geographic areas. Additionally, a single product is applicable for a single crop in a season, for a given district – necessitating the development of multiple products as needed.

An issue faced in general for index insurance and particularly for a hybrid product, is the high dependence on several sources of data where limitations in data infrastructure hinder robust product development. For an index based on rainfall, reliable historical rainfall data and a continuous supply of contemporary data are needed to measure product performance. Apart from rainfall, the hybrid product will need tank level data, which, for example in Sri Lanka are usually from several sources, given that the tanks could be managed either by regional level bodies or national level ones.

The hybrid index product addresses negative basis risk associated with irrigated farmlands only to an extent. It is no doubt an improvement on the rainfall index. However, there still remains a residual negative basis risk for irrigated farmlands due to factors like their distance from the tanks – some may be very far away, some very close, and this affects their relative benefits from the tanks. Due to the lack of granular data on individual farm distances from tanks, along with other variables, the impact of such risk cannot be incorporated. Ongoing pilot efforts by IFC in digitization of data, may provide an opportunity to cluster farms in different groups, i.e. by specific irrigation types, their distances from tanks, etc. Once such information is available, the product can be modified to capture these additional parameters, which can further contribute to reducing negative basis risk.

Another limitation of the model itself is that storage capacity can be affected by factors such as a buildup of sediment, tampering with the irrigation infrastructure by external parties, etc. These operational limitations exist, but they can be mitigated to some extent by the structuring of the product. It could be designed using tank storage level as the relevant parameter and not the discharge level. Further, the trigger level of the storage capacity can be set in a way that makes it difficult to manipulate externally, and to take the effect of sedimentation into account. Also, the deviation from the ‘normal’ storage level for a specific period can be considered, instead of absolute storage levels. So, regardless of the amount of water discharged (which can be affected by water management decisions and negligence), there is a strong probability that drought has taken place if, for instance, the tank’s effective storage is found to be low. In districts with multiple tanks (e.g. Anuradhapura) it could also be made possible to use the levels of nearby major tanks as a countercheck if suspicious fluctuation in a particular tank’s storage level is noticed. The tank water level will be a contingency check on whether a claim pay-out is eligible or not, but the actual calculation of the pay-out can be based on the rainfall levels.