Our analytics engine enables crop insurance companies in crop risk assessment at customised administrative levels and helps determine crop insurance premiums based on real-time data analytics. Yield estimation technologies at the farm level allow crop insurance companies to settle claims efficiently while reducing their operating costs.
Using our proprietary android mobile application, we can identify the concerned land plot and calculate it's area. Once georeferenced, DER's data fusion technologies can extract information from satellite and weather data that pertains to that georeferenced parcel.
Dvara E-Registry has developed Machine Learning Models that can identify the crop that is being grown on a land parcel. This is a unique technology which verifies whether the crop insured is growing in a particular land plot. Machine Learning approach by using statistics, dynamic weather and satellite data and crop yield data can maximise farmers' satisfaction and optimise loss ratio while keeping premiums within a limit. The yield estimates arrived at by these models can be used to assess insurance claims at a land parcel level.
As opposed to the existing practice of averaging out indices over larger regions like Gram Panchayats or Districts, the indices we use are calculated using only the data pertaining to a specific land parcel. Hence, it's much more representative of the yield on the land parcel and helps reduce basis risk.
The mobile app developed by Dvara E-Registry allows for images of the same field to be taken at different times during the crop season. This allows for a time series of land parcel specific images over the entire crop cycle that can also be used to judge the level of the insurance payout.
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